WorldWideScience

Sample records for model-referenced adaptive control

  1. Hybrid Adaptive Flight Control with Model Inversion Adaptation

    Science.gov (United States)

    Nguyen, Nhan

    2011-01-01

    This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

  2. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    Science.gov (United States)

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  3. Predictor-Based Model Reference Adaptive Control

    Science.gov (United States)

    Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

    2010-01-01

    This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

  4. Multiple model adaptive control with mixing

    Science.gov (United States)

    Kuipers, Matthew

    Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

  5. Adaptive PID and Model Reference Adaptive Control Switch Controller for Nonlinear Hydraulic Actuator

    Directory of Open Access Journals (Sweden)

    Xin Zuo

    2017-01-01

    Full Text Available Nonlinear systems are modeled as piecewise linear systems at multiple operating points, where the operating points are modeled as switches between constituent linearized systems. In this paper, adaptive piecewise linear switch controller is proposed for improving the response time and tracking performance of the hydraulic actuator control system, which is essentially piecewise linear. The controller composed of PID and Model Reference Adaptive Control (MRAC adaptively chooses the proportion of these two components and makes the designed system have faster response time at the transient phase and better tracking performance, simultaneously. Then, their stability and tracking performance are analyzed and evaluated by the hydraulic actuator control system, the hydraulic actuator is controlled by the electrohydraulic system, and its model is built, which has piecewise linear characteristic. Then the controller results are compared between PID and MRAC and the switch controller designed in this paper is applied to the hydraulic actuator; it is obvious that adaptive switch controller has better effects both on response time and on tracking performance.

  6. Postural Control Can Be Well Maintained by Healthy, Young Adults in Difficult Visual Task, Even in Sway-Referenced Dynamic Conditions.

    Science.gov (United States)

    Lions, Cynthia; Bucci, Maria Pia; Bonnet, Cédrick

    2016-01-01

    To challenge the validity of existing cognitive models of postural control, we recorded eye movements and postural sway during two visual tasks (a control free-viewing task and a difficult searching task), and two postural tasks (one static task in which the platform was maintained stable and a dynamic task in which the platform moved in a sway-referenced manner.) We expected these models to be insufficient to predict the results in postural control both in static-as already shown in the literature reports-and in dynamic platform conditions. Twelve healthy, young adults (17.3 to 34.1 years old) participated in this study. Postural performances were evaluated using the Multitest platform (Framiral®) and ocular recording was performed with Mobile T2 (e(ye)BRAIN®). In the free-viewing task, the participants had to look at an image, without any specific instruction. In the searching task, the participants had to look at an image and also to locate the position of an object in the scene. Postural sway was only significantly higher in the dynamic free-viewing condition than in the three other conditions with no significant difference between these three other conditions. Visual task performance was slightly higher in dynamic than in static conditions. As expected, our results did not confirm the main assumption of the current cognitive models of postural control-i.e. that the limited attentional resources of the brain should explain changes in postural control in our conditions. Indeed, 1) the participants did not sway significantly more in the sway-referenced dynamic searching condition than in any other condition; 2) the participants swayed significantly less in both static and dynamic searching conditions than in the dynamic free-viewing condition. We suggest that a new cognitive model illustrating the adaptive, functional role of the brain to control upright stance is necessary for future studies.

  7. Postural Control Can Be Well Maintained by Healthy, Young Adults in Difficult Visual Task, Even in Sway-Referenced Dynamic Conditions.

    Directory of Open Access Journals (Sweden)

    Cynthia Lions

    Full Text Available To challenge the validity of existing cognitive models of postural control, we recorded eye movements and postural sway during two visual tasks (a control free-viewing task and a difficult searching task, and two postural tasks (one static task in which the platform was maintained stable and a dynamic task in which the platform moved in a sway-referenced manner. We expected these models to be insufficient to predict the results in postural control both in static-as already shown in the literature reports-and in dynamic platform conditions.Twelve healthy, young adults (17.3 to 34.1 years old participated in this study. Postural performances were evaluated using the Multitest platform (Framiral® and ocular recording was performed with Mobile T2 (e(yeBRAIN®. In the free-viewing task, the participants had to look at an image, without any specific instruction. In the searching task, the participants had to look at an image and also to locate the position of an object in the scene.Postural sway was only significantly higher in the dynamic free-viewing condition than in the three other conditions with no significant difference between these three other conditions. Visual task performance was slightly higher in dynamic than in static conditions.As expected, our results did not confirm the main assumption of the current cognitive models of postural control-i.e. that the limited attentional resources of the brain should explain changes in postural control in our conditions. Indeed, 1 the participants did not sway significantly more in the sway-referenced dynamic searching condition than in any other condition; 2 the participants swayed significantly less in both static and dynamic searching conditions than in the dynamic free-viewing condition. We suggest that a new cognitive model illustrating the adaptive, functional role of the brain to control upright stance is necessary for future studies.

  8. Functional Dual Adaptive Control with Recursive Gaussian Process Model

    International Nuclear Information System (INIS)

    Prüher, Jakub; Král, Ladislav

    2015-01-01

    The paper deals with dual adaptive control problem, where the functional uncertainties in the system description are modelled by a non-parametric Gaussian process regression model. Current approaches to adaptive control based on Gaussian process models are severely limited in their practical applicability, because the model is re-adjusted using all the currently available data, which keeps growing with every time step. We propose the use of recursive Gaussian process regression algorithm for significant reduction in computational requirements, thus bringing the Gaussian process-based adaptive controllers closer to their practical applicability. In this work, we design a bi-criterial dual controller based on recursive Gaussian process model for discrete-time stochastic dynamic systems given in an affine-in-control form. Using Monte Carlo simulations, we show that the proposed controller achieves comparable performance with the full Gaussian process-based controller in terms of control quality while keeping the computational demands bounded. (paper)

  9. Tensor Product Model Transformation Based Adaptive Integral-Sliding Mode Controller: Equivalent Control Method

    Directory of Open Access Journals (Sweden)

    Guoliang Zhao

    2013-01-01

    Full Text Available This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

  10. Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

    Directory of Open Access Journals (Sweden)

    Peng Song

    2012-01-01

    Full Text Available Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.

  11. Adaptive Control with Reference Model Modification

    Science.gov (United States)

    Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

  12. Nonlinear adaptive inverse control via the unified model neural network

    Science.gov (United States)

    Jeng, Jin-Tsong; Lee, Tsu-Tian

    1999-03-01

    In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

  13. Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

    Science.gov (United States)

    Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

    2010-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

  14. Model reference adaptive control and adaptive stability augmentation

    DEFF Research Database (Denmark)

    Henningsen, Arne; Ravn, Ole

    1993-01-01

    A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...... stability augmented model reference design is proposed. By utilizing the closed-loop control error, a simple auxiliary controller is tuned, using a normalized MIT rule for the parameter adjustment. The MIT adjustment is protected against the effects of unmodelled dynamics by lowpass filtering...... of the gradient. The proposed method is verified through simulation results indicating that the method may lead to an improvement of the model reference controller in the presence of unmodelled dynamics...

  15. Evaluation-Function-based Model-free Adaptive Fuzzy Control

    Directory of Open Access Journals (Sweden)

    Agus Naba

    2016-12-01

    Full Text Available Designs of adaptive fuzzy controllers (AFC are commonly based on the Lyapunov approach, which requires a known model of the controlled plant. They need to consider a Lyapunov function candidate as an evaluation function to be minimized. In this study these drawbacks were handled by designing a model-free adaptive fuzzy controller (MFAFC using an approximate evaluation function defined in terms of the current state, the next state, and the control action. MFAFC considers the approximate evaluation function as an evaluative control performance measure similar to the state-action value function in reinforcement learning. The simulation results of applying MFAFC to the inverted pendulum benchmark verified the proposed scheme’s efficacy.

  16. A measured-ZMP(Zero-Moment-Point)-referenced control of biped locomotion robots

    International Nuclear Information System (INIS)

    Kume, Etsuo; Akimoto, Masayuki

    1994-01-01

    For the control of biped locomotion, the model-referenced-control or programmed control method is widely used. In this method, the instantaneous torque of actuator equipped at each joint is controlled so as to equalize measured angle to input joint angle based on the prescribed motion. The drawback is that this method can not deal with the dynamic change of walking such as that due to unknown external force. To resolve such the drawback, we propose a new control method as follows: given a prescribed motion as a set of gait, namely gait of starting walk, cyclic walk, and stopping walk including a standard trajectory of the Zero-Moment-Point (ZMP), the trunk motion to compensate the legs' motion is generated in real time using the current ZMP measured by sensing device. The proposed method will be validated through some numerical simulations. (author)

  17. PI controller based model reference adaptive control for nonlinear

    African Journals Online (AJOL)

    user

    Keywords: Model Reference Adaptive Controller (MRAC), Artificial Neural ... attention, and many new approaches have been applied to practical process .... effectiveness of proposed method, it is compared with the simulation results of the ...

  18. Modeling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.

    System concepts

    In Chapters 1 and 2 an overview of the problem formulation

  19. Fuzzy Adaptive Model Following Speed Control for Vector Controlled Permanent Magnet Synchronous Motor

    Directory of Open Access Journals (Sweden)

    Baghdad BELABES

    2008-12-01

    Full Text Available In this paper a hybrid controller combining a linear model following controller (LMFC and fuzzy logic control (FLC for speed vector controlled permanent magnet synchronous motor (PMSM is described on this study. The FLC is introduced at the adaptive mechanism level. First, an LMFC system is designed to allow the plant states to be controlled to follow the states produced by a reference model. In the nominal conditions, the model following is perfect and the adaptive mechanism based on the fuzzy logic is idle. Secondly, when parameter variations or external disturbances occur, an augmented signal will be generated by FLC mechanism to preserve the desired model following control performance. The effectiveness and robustness of the proposed controller is demonstrated by some simulation results.

  20. Smooth Adaptive Internal Model Control Based on U Model for Nonlinear Systems with Dynamic Uncertainties

    Directory of Open Access Journals (Sweden)

    Li Zhao

    2016-01-01

    Full Text Available An improved smooth adaptive internal model control based on U model control method is presented to simplify modeling structure and parameter identification for a class of uncertain dynamic systems with unknown model parameters and bounded external disturbances. Differing from traditional adaptive methods, the proposed controller can simplify the identification of time-varying parameters in presence of bounded external disturbances. Combining the small gain theorem and the virtual equivalent system theory, learning rate of smooth adaptive internal model controller has been analyzed and the closed-loop virtual equivalent system based on discrete U model has been constructed as well. The convergence of this virtual equivalent system is proved, which further shows the convergence of the complex closed-loop discrete U model system. Finally, simulation and experimental results on a typical nonlinear dynamic system verified the feasibility of the proposed algorithm. The proposed method is shown to have lighter identification burden and higher control accuracy than the traditional adaptive controller.

  1. Design of a Model Reference Adaptive Controller for an Unmanned Air Vehicle

    Science.gov (United States)

    Crespo, Luis G.; Matsutani, Megumi; Annaswamy, Anuradha M.

    2010-01-01

    This paper presents the "Adaptive Control Technology for Safe Flight (ACTS)" architecture, which consists of a non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off nominal ones. The design and implementation procedures of both controllers are presented. The aim of these procedures, which encompass both theoretical and practical considerations, is to develop a controller suitable for flight. The ACTS architecture is applied to the Generic Transport Model developed by NASA-Langley Research Center. The GTM is a dynamically scaled test model of a transport aircraft for which a flight-test article and a high-fidelity simulation are available. The nominal controller at the core of the ACTS architecture has a multivariable LQR-PI structure while the adaptive one has a direct, model reference structure. The main control surfaces as well as the throttles are used as control inputs. The inclusion of the latter alleviates the pilot s workload by eliminating the need for cancelling the pitch coupling generated by changes in thrust. Furthermore, the independent usage of the throttles by the adaptive controller enables their use for attitude control. Advantages and potential drawbacks of adaptation are demonstrated by performing high fidelity simulations of a flight-validated controller and of its adaptive augmentation.

  2. Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

    Science.gov (United States)

    Aprasoff, Jonathan; Donchin, Opher

    2012-04-01

    Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

  3. A Direct Adaptive Control Approach in the Presence of Model Mismatch

    Science.gov (United States)

    Joshi, Suresh M.; Tao, Gang; Khong, Thuan

    2009-01-01

    This paper considers the problem of direct model reference adaptive control when the plant-model matching conditions are violated due to abnormal changes in the plant or incorrect knowledge of the plant's mathematical structure. The approach consists of direct adaptation of state feedback gains for state tracking, and simultaneous estimation of the plant-model mismatch. Because of the mismatch, the plant can no longer track the state of the original reference model, but may be able to track a new reference model that still provides satisfactory performance. The reference model is updated if the estimated plant-model mismatch exceeds a bound that is determined via robust stability and/or performance criteria. The resulting controller is a hybrid direct-indirect adaptive controller that offers asymptotic state tracking in the presence of plant-model mismatch as well as parameter deviations.

  4. Multiple Model Adaptive Attitude Control of LEO Satellite with Angular Velocity Constraints

    Science.gov (United States)

    Shahrooei, Abolfazl; Kazemi, Mohammad Hosein

    2018-04-01

    In this paper, the multiple model adaptive control is utilized to improve the transient response of attitude control system for a rigid spacecraft. An adaptive output feedback control law is proposed for attitude control under angular velocity constraints and its almost global asymptotic stability is proved. The multiple model adaptive control approach is employed to counteract large uncertainty in parameter space of the inertia matrix. The nonlinear dynamics of a low earth orbit satellite is simulated and the proposed control algorithm is implemented. The reported results show the effectiveness of the suggested scheme.

  5. Referencing academic assignments.

    Science.gov (United States)

    Gopee, N

    External examiners often identify inaccurate referencing as a weakness in scripts submitted for assessment. This article explores the main aspects of referencing, and offers a protocol for referencing founded on the Harvard (name-date) system.

  6. Multiple Model Adaptive Control Using Dual Youla-Kucera Factorisation

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    2012-01-01

    We propose a multi-model adaptive control scheme for uncertain linear plants based on the concept of model unfalsification. The approach relies on examining the ability of a pre-computed set of plant-controller candidates and choosing the one that is best able to reproduce observed in- and output...

  7. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    Science.gov (United States)

    Nguyen, Nhan T.

    2009-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

  8. Adaptive control for a PWR using a self-tuning reference model concept

    International Nuclear Information System (INIS)

    Miley, G.H.; Park, G.T.; Kim, B.S.

    1992-01-01

    Possible applications of an adaptive control method to a pressurized-water reactor nuclear power plant are investigated. The self-tuning technique with a reference model concept is employed. This control algorithm is developed by combining the self-tuning controller with the model reference adaptive control. This approach overcomes the difficulties in choosing the appropriate weighting polynomials in the cost function of the self-tuning control

  9. Analytic Model Predictive Control of Uncertain Nonlinear Systems: A Fuzzy Adaptive Approach

    Directory of Open Access Journals (Sweden)

    Xiuyan Peng

    2015-01-01

    Full Text Available A fuzzy adaptive analytic model predictive control method is proposed in this paper for a class of uncertain nonlinear systems. Specifically, invoking the standard results from the Moore-Penrose inverse of matrix, the unmatched problem which exists commonly in input and output dimensions of systems is firstly solved. Then, recurring to analytic model predictive control law, combined with fuzzy adaptive approach, the fuzzy adaptive predictive controller synthesis for the underlying systems is developed. To further reduce the impact of fuzzy approximation error on the system and improve the robustness of the system, the robust compensation term is introduced. It is shown that by applying the fuzzy adaptive analytic model predictive controller the rudder roll stabilization system is ultimately uniformly bounded stabilized in the H-infinity sense. Finally, simulation results demonstrate the effectiveness of the proposed method.

  10. Modeling, Control and Simulation of Three-Dimensional Robotic Systems with Applications to Biped Locomotion.

    Science.gov (United States)

    Zheng, Yuan-Fang

    A three-dimensional, five link biped system is established. Newton-Euler state space formulation is employed to derive the equations of the system. The constraint forces involved in the equations can be eliminated by projection onto a smaller state space system for deriving advanced control laws. A model-referenced adaptive control scheme is developed to control the system. Digital computer simulations of point to point movement are carried out to show that the model-referenced adaptive control increases the dynamic range and speeds up the response of the system in comparison with linear and nonlinear feedback control. Further, the implementation of the controller is simpler. Impact effects of biped contact with the environment are modeled and studied. The instant velocity change at the moment of impact is derived as a function of the biped state and contact speed. The effects of impact on the state, as well as constraints are studied in biped landing on heels and toes simultaneously or on toes first. Rate and nonlinear position feedback are employed for stability of the biped after the impact. The complex structure of the foot is properly modeled. A spring and dashpot pair is suggested to represent the action of plantar fascia during the impact. This action prevents the arch of the foot from collapsing. A mathematical model of the skeletal muscle is discussed. A direct relationship between the stimulus rate and the active state is established. A piecewise linear relation between the length of the contractile element and the isometric force is considered. Hill's characteristic equation is maintained for determining the actual output force during different shortening velocities. A physical threshold model is proposed for recruitment which encompasses the size principle, its manifestations and exceptions to the size principle. Finally the role of spindle feedback in stability of the model is demonstrated by study of a pair of muscles.

  11. Neural network-based model reference adaptive control system.

    Science.gov (United States)

    Patino, H D; Liu, D

    2000-01-01

    In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

  12. Comparison of model reference and map based control method for vehicle stability enhancement

    NARCIS (Netherlands)

    Baek, S.; Son, M.; Song, J.; Boo, K.; Kim, H.

    2012-01-01

    A map based controller method to improve a vehicle lateral stability is proposed in this study and compared with the conventional method, a model referenced controller. A model referenced controller to determine compensated yaw moment uses the sliding mode method, but the proposed map based

  13. A Nonlinear Dynamic Inversion Predictor-Based Model Reference Adaptive Controller for a Generic Transport Model

    Science.gov (United States)

    Campbell, Stefan F.; Kaneshige, John T.

    2010-01-01

    Presented here is a Predictor-Based Model Reference Adaptive Control (PMRAC) architecture for a generic transport aircraft. At its core, this architecture features a three-axis, non-linear, dynamic-inversion controller. Command inputs for this baseline controller are provided by pilot roll-rate, pitch-rate, and sideslip commands. This paper will first thoroughly present the baseline controller followed by a description of the PMRAC adaptive augmentation to this control system. Results are presented via a full-scale, nonlinear simulation of NASA s Generic Transport Model (GTM).

  14. Nonlinear model-based robust control of a nuclear reactor using adaptive PIF gains and variable structure controller

    International Nuclear Information System (INIS)

    Park, Moon Ghu; Cho, Nam Zin

    1993-01-01

    A Nonlinear model-based Hybrid Controller (NHC) is developed which consists of the adaptive proportional-integral-feedforward (PIF) gains and variable structure controller. The controller has the robustness against modeling uncertainty and is applied to the trajectory tracking control of single-input, single-output nonlinear systems. The essence of the scheme is to divide the control into four different terms. Namely, the adaptive P-I-F gains and variable structure controller are used to accomplish the specific control actions by each terms. The robustness of the controller is guaranteed by the feedback of estimated uncertainty and the performance specification given by the adaptation of PIF gains using the second method of Lyapunov. The variable structure controller is incorporated to regulate the initial peak of the tracking error during the parameter adaptation is not settled yet. The newly developed NHC method is applied to the power tracking control of a nuclear reactor and the simulation results show great improvement in tracking performance compared with the conventional model-based control methods. (Author)

  15. Adaptive control using neural networks and approximate models.

    Science.gov (United States)

    Narendra, K S; Mukhopadhyay, S

    1997-01-01

    The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods are used for realizing the neural controllers to overcome computational complexity. In this paper, we introduce two classes of models which are approximations to the NARMA model, and which are linear in the control input. The latter fact substantially simplifies both the theoretical analysis as well as the practical implementation of the controller. Extensive simulation studies have shown that the neural controllers designed using the proposed approximate models perform very well, and in many cases even better than an approximate controller designed using the exact NARMA model. In view of their mathematical tractability as well as their success in simulation studies, a case is made in this paper that such approximate input-output models warrant a detailed study in their own right.

  16. Development of model reference adaptive control theory for electric power plant control applications

    Energy Technology Data Exchange (ETDEWEB)

    Mabius, L.E.

    1982-09-15

    The scope of this effort includes the theoretical development of a multi-input, multi-output (MIMO) Model Reference Control (MRC) algorithm, (i.e., model following control law), Model Reference Adaptive Control (MRAC) algorithm and the formulation of a nonlinear model of a typical electric power plant. Previous single-input, single-output MRAC algorithm designs have been generalized to MIMO MRAC designs using the MIMO MRC algorithm. This MRC algorithm, which has been developed using Command Generator Tracker methodologies, represents the steady state behavior (in the adaptive sense) of the MRAC algorithm. The MRC algorithm is a fundamental component in the MRAC design and stability analysis. An enhanced MRC algorithm, which has been developed for systems with more controls than regulated outputs, alleviates the MRC stability constraint of stable plant transmission zeroes. The nonlinear power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows. An application of the MRC algorithm to a linearization of this model demonstrates its applicability to power plant systems. In particular, the generated power changes at 7% per minute while throttle pressure and temperature, reheat temperature and drum level are held constant with a reasonable level of control. The enhanced algorithm reduces significantly control fluctuations without modifying the output response.

  17. Model and experiments to optimize co-adaptation in a simplified myoelectric control system.

    Science.gov (United States)

    Couraud, M; Cattaert, D; Paclet, F; Oudeyer, P Y; de Rugy, A

    2018-04-01

    To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this approach to more complex and functional

  18. Model and experiments to optimize co-adaptation in a simplified myoelectric control system

    Science.gov (United States)

    Couraud, M.; Cattaert, D.; Paclet, F.; Oudeyer, P. Y.; de Rugy, A.

    2018-04-01

    Objective. To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. Approach. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. Results. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. Significance. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this

  19. Multi-Model Adaptive Fuzzy Controller for a CSTR Process

    Directory of Open Access Journals (Sweden)

    Shubham Gogoria

    2015-09-01

    Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.

  20. New fuzzy approximate model for indirect adaptive control of distributed solar collectors

    KAUST Repository

    Elmetennani, Shahrazed

    2014-06-01

    This paper studies the problem of controlling a parabolic solar collectors, which consists of forcing the outlet oil temperature to track a set reference despite possible environmental disturbances. An approximate model is proposed to simplify the controller design. The presented controller is an indirect adaptive law designed on the fuzzy model with soft-sensing of the solar irradiance intensity. The proposed approximate model allows the achievement of a simple low dimensional set of nonlinear ordinary differential equations that reproduces the dynamical behavior of the system taking into account its infinite dimension. Stability of the closed loop system is ensured by resorting to Lyapunov Control functions for an indirect adaptive controller.

  1. New fuzzy approximate model for indirect adaptive control of distributed solar collectors

    KAUST Repository

    Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem

    2014-01-01

    This paper studies the problem of controlling a parabolic solar collectors, which consists of forcing the outlet oil temperature to track a set reference despite possible environmental disturbances. An approximate model is proposed to simplify the controller design. The presented controller is an indirect adaptive law designed on the fuzzy model with soft-sensing of the solar irradiance intensity. The proposed approximate model allows the achievement of a simple low dimensional set of nonlinear ordinary differential equations that reproduces the dynamical behavior of the system taking into account its infinite dimension. Stability of the closed loop system is ensured by resorting to Lyapunov Control functions for an indirect adaptive controller.

  2. Summary: Update to ASTM guide E 1523 to charge control and charge referencing techniques in x-ray photoelectron spectroscopy

    International Nuclear Information System (INIS)

    Baer, D.R.

    2005-01-01

    An updated version of the American Society for Testing and Materials (ASTM) guide E 1523 to the methods to charge control and charge referencing techniques in x-ray photoelectron spectroscopy has been released by ASTM [Annual Book of ASTM Standards Surface Analysis (American Society for Testing and Materials, West Conshohocken, PA, 2004), Vol. 03.06]. The guide is meant to acquaint x-ray photoelectron spectroscopy (XPS) users with the various charge control and charge referencing techniques that are and have been used in the acquisition and interpretation of XPS data from surfaces of insulating specimens. The current guide has been expanded to include new references as well as recommendations for reporting information on charge control and charge referencing. The previous version of the document had been published in 1997 [D. R. Baer and K. D. Bomben, J. Vac. Sci. Technol. A 16, 754 (1998)

  3. Collaborative Referencing between Individuals with Aphasia and Routine Communication Partners.

    Science.gov (United States)

    Hengst, Julie A.

    2003-01-01

    This study examined how four adults with aphasia collaborated with routine communication partners. Overall, these pairs completed the referencing task trials with accuracy and displayed referencing processes that conformed to the collaborative referencing model of communication. However, the pairs also used diverse verbal and nonverbal resources,…

  4. An Adaptive Supervisory Sliding Fuzzy Cerebellar Model Articulation Controller for Sensorless Vector-Controlled Induction Motor Drive Systems

    Directory of Open Access Journals (Sweden)

    Shun-Yuan Wang

    2015-03-01

    Full Text Available This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC in the speed sensorless vector control of an induction motor (IM drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.

  5. Adaptive control of servo system based on LuGre model

    Science.gov (United States)

    Jin, Wang; Niancong, Liu; Jianlong, Chen; Weitao, Geng

    2018-03-01

    This paper established a mechanical model of feed system based on LuGre model. In order to solve the influence of nonlinear factors on the system running stability, a nonlinear single observer is designed to estimate the parameter z in the LuGre model and an adaptive friction compensation controller is designed. Simulink simulation results show that the control method can effectively suppress the adverse effects of friction and external disturbances. The simulation show that the adaptive parameter kz is between 0.11-0.13, and the value of gamma1 is between 1.9-2.1. Position tracking error reaches level 10-3 and is stabilized near 0 values within 0.3 seconds, the compensation method has better tracking accuracy and robustness.

  6. Adaptions of ArcGIS' Linear Referencing System to the Coastal Environment

    DEFF Research Database (Denmark)

    Balstrøm, Thomas

    2008-01-01

    For many years it has been problematic to store information for the coastal environment in a GIS. However, a system named "Linear referencing System" based upon a dynamic segmentation principle implemented in ESRIs ArcGIS 9 software has now made it possible to store and analyze information...

  7. Academic Practice, APA Referencing Style

    DEFF Research Database (Denmark)

    Nielsen, Sandro; Heine, Carmen

    kildeangivelse og referencer i henhold til APA referencing system.Vejledning i at undgå plagiering ved at følge de normer, der gælder for good academic practice. Dette indebærer at man angiver kilder korrekt, og når det er nødvendigt, og at man har en korrekt udformet fortegnelse over referencer. Vejledningen...... indeholder konkrete eksempler på korrekt kildeangivelse og referencer i henhold til APA referencing system....

  8. Geometry Modeling and Adaptive Control of Air-Breathing Hypersonic Vehicles

    Science.gov (United States)

    Vick, Tyler Joseph

    Air-breathing hypersonic vehicles have the potential to provide global reach and affordable access to space. Recent technological advancements have made scramjet-powered flight achievable, as evidenced by the successes of the X-43A and X-51A flight test programs over the last decade. Air-breathing hypersonic vehicles present unique modeling and control challenges in large part due to the fact that scramjet propulsion systems are highly integrated into the airframe, resulting in strongly coupled and often unstable dynamics. Additionally, the extreme flight conditions and inability to test fully integrated vehicle systems larger than X-51 before flight leads to inherent uncertainty in hypersonic flight. This thesis presents a means to design vehicle geometries, simulate vehicle dynamics, and develop and analyze control systems for hypersonic vehicles. First, a software tool for generating three-dimensional watertight vehicle surface meshes from simple design parameters is developed. These surface meshes are compatible with existing vehicle analysis tools, with which databases of aerodynamic and propulsive forces and moments can be constructed. A six-degree-of-freedom nonlinear dynamics simulation model which incorporates this data is presented. Inner-loop longitudinal and lateral control systems are designed and analyzed utilizing the simulation model. The first is an output feedback proportional-integral linear controller designed using linear quadratic regulator techniques. The second is a model reference adaptive controller (MRAC) which augments this baseline linear controller with an adaptive element. The performance and robustness of each controller are analyzed through simulated time responses to angle-of-attack and bank angle commands, while various uncertainties are introduced. The MRAC architecture enables the controller to adapt in a nonlinear fashion to deviations from the desired response, allowing for improved tracking performance, stability, and

  9. Model-free adaptive control of advanced power plants

    Science.gov (United States)

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  10. A model-referenced procedure to support adversarial decision processes

    International Nuclear Information System (INIS)

    Bunn, D.W.; Vlahos, K.

    1992-01-01

    In public enquiries concerning major facilities, such as the construction of a new electric power plant, it is observed that a useable decision model should be made commonly available alongside the open provision of data and assumptions. The protagonist, eg the electric utility, generally makes use of a complex, proprietary model for detailed evaluation of options. A simple emulator of this, based upon a regression analysis of numerous scenarios, and validated by further simulations is shown to be feasible and potentially attractive. It would be in the interests of the utility to make such a model-referenced decision support method generally available. The approach is considered in relation to the recent Hinkley Point C public enquiry for a new nuclear power plant in the UK. (Author)

  11. Direct Model Reference Adaptive Control for a Magnetic Bearing

    Energy Technology Data Exchange (ETDEWEB)

    Durling, Mike [Rensselaer Polytechnic Inst., Troy, NY (United States)

    1999-11-01

    A Direct Model Reference Adaptive Controller (DMRAC) is applied to a magnetic bearing test stand. The bearing of interest is the MBC 500 Magnetic Bearing System manufactured by Magnetic Moments, LLC. The bearing model is presented in state space form and the system transfer function is measured directly using a closed-loop swept sine technique. Next, the bearing models are used to design a phase-lead controller, notch filter and then a DMRAC. The controllers are tuned in simulations and finally are implemented using a combination of MATLAB, SIMULINK and dSPACE. The results show a successful implementation of a DMRAC on the magnetic bearing hardware.

  12. Functional requirements for a comprehensive transportation location referencing system

    Science.gov (United States)

    2000-06-01

    Transportation agencies manage data that is referenced in one, two, three, and four dimensions. Location referencing system (LRS) data models vary across transportation agencies and often within organizations as well. This has resulted in failed atte...

  13. Model Reference Adaptive Control of the Air Flow Rate of Centrifugal Compressor Using State Space Method

    International Nuclear Information System (INIS)

    Han, Jaeyoung; Jung, Mooncheong; Yu, Sangseok; Yi, Sun

    2016-01-01

    In this study, a model reference adaptive controller is developed to regulate the outlet air flow rate of centrifugal compressor for automotive supercharger. The centrifugal compressor is developed using the analytical based method to predict the transient behavior of operating and the designed model is validated with experimental data to confirm the system accuracy. The model reference adaptive control structure consists of a compressor model and a MRAC(model reference adaptive control) mechanism. The feedback control do not robust with variation of system parameter but the applied adaptive control is robust even if the system parameter is changed. As a result, the MRAC was regulated to reference air flow rate. Also MRAC was found to be more robust control compared with the feedback control even if the system parameter is changed.

  14. Model Reference Adaptive Control of the Air Flow Rate of Centrifugal Compressor Using State Space Method

    Energy Technology Data Exchange (ETDEWEB)

    Han, Jaeyoung; Jung, Mooncheong; Yu, Sangseok [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Yi, Sun [North Carolina A and T State Univ., Raleigh (United States)

    2016-08-15

    In this study, a model reference adaptive controller is developed to regulate the outlet air flow rate of centrifugal compressor for automotive supercharger. The centrifugal compressor is developed using the analytical based method to predict the transient behavior of operating and the designed model is validated with experimental data to confirm the system accuracy. The model reference adaptive control structure consists of a compressor model and a MRAC(model reference adaptive control) mechanism. The feedback control do not robust with variation of system parameter but the applied adaptive control is robust even if the system parameter is changed. As a result, the MRAC was regulated to reference air flow rate. Also MRAC was found to be more robust control compared with the feedback control even if the system parameter is changed.

  15. Adaptive control of robotic manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.

  16. Development of Power Controller System based on Model Reference Adaptive Control for a Nuclear Reactor

    International Nuclear Information System (INIS)

    Mohd Sabri Minhat; Izhar Abu Hussin; Ridzuan Abdul Mutalib

    2014-01-01

    The Reactor TRIGA PUSPATI (RTP)-type TRIGA Mark II was installed in the year 1982. The Power Controller System (PCS) or Automated Power Controller System (APCS) is very important for reactor operation and safety reasons. It is a function of controlled reactivity and reactor power. The existing power controller system is under development and due to slow response, low accuracy and low stability on reactor power control affecting the reactor safety. The nuclear reactor is a nonlinear system in nature, and it is power increases continuously with time. The reactor parameters vary as a function of power, fuel burnup and control rod worth. The output power value given by the power control system is not exactly as real value of reactor power. Therefore, controller system design is very important, an adaptive controller seems to be inevitable. The method chooses is a linear controller by using feedback linearization, for example Model Reference Adaptive Control. The developed APCS for RTP will be design by using Model Reference Adaptive Control (MRAC). The structured of RTP model to produce the dynamic behaviour of RTP on entire operating power range from 0 to 1MWatt. The dynamic behavior of RTP model is produced by coupling of neutronic and thermal-hydraulics. It will be developed by using software MATLAB/Simulink and hardware module card to handle analog input signal. A new algorithm for APCS is developed to control the movement of control rods with uniformity and orderly for RTP. Before APCS test to real plant, simulation results shall be obtained from RTP model on reactor power, reactivity, period, control rod positions, fuel and coolant temperatures. Those data are comparable with the real data for validation. After completing the RTP model, APCS will be tested to real plant on power control system performance by using real signal from RTP including fail-safe operation, system reliable, fast response, stability and accuracy. The new algorithm shall be a satisfied

  17. Neural Control and Adaptive Neural Forward Models for Insect-like, Energy-Efficient, and Adaptable Locomotion of Walking Machines

    Directory of Open Access Journals (Sweden)

    Poramate eManoonpong

    2013-02-01

    Full Text Available Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs and sensory feedback (afferent-based control but also on internal forward models (efference copies. They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.

  18. Multivariable robust adaptive controller using reduced-order model

    Directory of Open Access Journals (Sweden)

    Wei Wang

    1990-04-01

    Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.

  19. Second-order sliding mode controller with model reference adaptation for automatic train operation

    Science.gov (United States)

    Ganesan, M.; Ezhilarasi, D.; Benni, Jijo

    2017-11-01

    In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.

  20. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C

    2009-01-01

    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  1. Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model.

    Science.gov (United States)

    Markowitz, Jared; Krishnaswamy, Pavitra; Eilenberg, Michael F; Endo, Ken; Barnhart, Chris; Herr, Hugh

    2011-05-27

    Control schemes for powered ankle-foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle-tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle-foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs.

  2. Adaptive relative pose control of spacecraft with model couplings and uncertainties

    Science.gov (United States)

    Sun, Liang; Zheng, Zewei

    2018-02-01

    The spacecraft pose tracking control problem for an uncertain pursuer approaching to a space target is researched in this paper. After modeling the nonlinearly coupled dynamics for relative translational and rotational motions between two spacecraft, position tracking and attitude synchronization controllers are developed independently by using a robust adaptive control approach. The unknown kinematic couplings, parametric uncertainties, and bounded external disturbances are handled with adaptive updating laws. It is proved via Lyapunov method that the pose tracking errors converge to zero asymptotically. Spacecraft close-range rendezvous and proximity operations are introduced as an example to validate the effectiveness of the proposed control approach.

  3. Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling

    Science.gov (United States)

    Brakebill, J.W.; Wolock, D.M.; Terziotti, S.E.

    2011-01-01

    Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

  4. An adaptive Cartesian control scheme for manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

  5. Unemployment estimation: Spatial point referenced methods and models

    KAUST Repository

    Pereira, Soraia; Turkman, Kamil Feridun; Correia, Luis; Rue, Haavard

    2017-01-01

    Portuguese Labor force survey, from 4th quarter of 2014 onwards, started geo-referencing the sampling units, namely the dwellings in which the surveys are carried. This opens new possibilities in analysing and estimating unemployment and its spatial

  6. Near-real-time feedback control system for liver thermal ablations based on self-referenced temperature imaging

    International Nuclear Information System (INIS)

    Keserci, Bilgin M.; Kokuryo, Daisuke; Suzuki, Kyohei; Kumamoto, Etsuko; Okada, Atsuya; Khankan, Azzam A.; Kuroda, Kagayaki

    2006-01-01

    Our challenge was to design and implement a dedicated temperature imaging feedback control system to guide and assist in a thermal liver ablation procedure in a double-donut 0.5T open MR scanner. This system has near-real-time feedback capability based on a newly developed 'self-referenced' temperature imaging method using 'moving-slab' and complex-field-fitting techniques. Two phantom validation studies and one ex vivo experiment were performed to compare the newly developed self-referenced method with the conventional subtraction method and evaluate the ability of the feedback control system in the same MR scanner. The near-real-time feedback system was achieved by integrating the following primary functions: (1) imaging of the moving organ temperature; (2) on-line needle tip tracking; (3) automatic turn-on/off the heating devices; (4) a Windows operating system-based novel user-interfaces. In the first part of the validation studies, microwave heating was applied in an agar phantom using a fast spoiled gradient recalled echo in a steady state sequence. In the second part of the validation and ex vivo study, target visualization, treatment planning and monitoring, and temperature and thermal dose visualization with the graphical user interface of the thermal ablation software were demonstrated. Furthermore, MR imaging with the 'self-referenced' temperature imaging method has the ability to localize the hot spot in the heated region and measure temperature elevation during the experiment. In conclusion, we have demonstrated an interactively controllable feedback control system that offers a new method for the guidance of liver thermal ablation procedures, as well as improving the ability to assist ablation procedures in an open MR scanner

  7. A new adaptive control scheme based on the interacting multiple model (IMM) estimation

    International Nuclear Information System (INIS)

    Afshari, Hamed H.; Al-Ani, Dhafar; Habibi, Saeid

    2016-01-01

    In this paper, an Interacting multiple model (IMM) adaptive estimation approach is incorporated to design an optimal adaptive control law for stabilizing an Unmanned vehicle. Due to variations of the forward velocity of the Unmanned vehicle, its aerodynamic derivatives are constantly changing. In order to stabilize the unmanned vehicle and achieve the control objectives for in-flight conditions, one seeks for an adaptive control strategy that can adjust itself to varying flight conditions. In this context, a bank of linear models is used to describe the vehicle dynamics in different operating modes. Each operating mode represents a particular dynamic with a different forward velocity. These models are then used within an IMM filter containing a bank of Kalman filters (KF) in a parallel operating mechanism. To regulate and stabilize the vehicle, a Linear quadratic regulator (LQR) law is designed and implemented for each mode. The IMM structure determines the particular mode based on the stored models and in-flight input-output measurements. The LQR controller also provides a set of controllers; each corresponds to a particular flight mode and minimizes the tracking error. Finally, the ultimate control law is obtained as a weighted summation of all individual controllers whereas weights are obtained using mode probabilities of each operating mode.

  8. Discrete Model Reference Adaptive Control for Gimbal Servosystem of Control Moment Gyro with Harmonic Drive

    Directory of Open Access Journals (Sweden)

    Bangcheng Han

    2013-01-01

    Full Text Available The double-gimbal control moment gyro (DGCMG demands that the gimbal servosystem should have fast response and small overshoot. But due to the low and nonlinear torsional stiffness of harmonic drive, the gimbal servo-system has poor dynamic performance with large overshoot and low bandwidth. In order to improve the dynamic performance of gimbal servo-system, a model reference adaptive control (MRAC law is introduced in this paper. The model of DGCMG gimbal servo-system with harmonic drive is established, and the adaptive control law based on POPOV super stable theory is designed. The MATLAB simulation results are provided to verify the effectiveness of the proposed control algorithm. The experimental results indicate that the MRAC could increase the bandwidth of gimbal servo-system to 3 Hz and improve the dynamic performance with small overshoot.

  9. Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

    Directory of Open Access Journals (Sweden)

    Zhenhao Tang

    2017-01-01

    Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

  10. Career success criteria and locus of control as indicators of adaptive readiness in the career adaptation model.

    OpenAIRE

    Zhou, W.; Guan, Y.; Xin, L.; Mak, M.C.K.; Deng, Y.

    2016-01-01

    The present research had two goals. The first goal was to identify additional individual characteristics that may contribute to adaptive readiness. The second goal was to test if these characteristics fit the career adaptation model of readiness to resources to responses. We examined whether career success criteria (measured at Time 1) and career locus of control (measured at Time 1) would contribute to adaptivity and predict university students’ career decision-making self-efficacy (measured...

  11. Adaptive Extremum Control and Wind Turbine Control

    DEFF Research Database (Denmark)

    Ma, Xin

    1997-01-01

    This thesis is divided into two parts, i.e., adaptive extremum control and modelling and control of a wind turbine. The rst part of the thesis deals with the design of adaptive extremum controllers for some processes which have the behaviour that process should have as high e ciency as possible...... in parameters, and thus directly lends itself to parameter estimation and adaptive control. The extremum control law is derived based on static optimization of a performance function. For a process with nonlinearity at output the intermediate signal between the linear part and nonlinear part plays an important....... Firstly, it is assumed that the nonlinear processes can be divided into a dynamic linear part and static nonlinear part. Consequently the processes with input nonlinearity and output nonlinearity are treated separately. With the nonlinearity at the input it is easy to set up a model which is linear...

  12. Intercalated Injection, Target Model Construction and H 2 Performance of Retrospective Cost Adaptive Control

    Science.gov (United States)

    Rahman, Yousaf

    This dissertation extends retrospective cost adaptive control (RCAC) by devel- oping a novel interpretation of RCAC, wherein the retrospective cost minimization uses intercalated injection between the controller numerator and denominator to fit a specific closed-loop transfer function to a target model. The target model thus incor- porates the modeling information required by RCAC. To demonstrate the effect of the target model on closed-loop performance, RCAC is applied to a collection of problems that demonstrate adaptive pole placement, where the target model is used to place closed-loop poles; adaptive PID control, where RCAC adaptively tunes PID gains; and LQG cost minimization, where the optimality and closed-loop frequency response of RCAC is compared with the performance of discrete-time LQG controllers. Next, RCAC is applied to plants that are difficult to control using fixed gain con- trollers, including an aircraft lateral dynamics model that has an unknown transition from minimum-phase to nonminimum-phase (NMP) dynamics, as well as plants with severely limited achievable gain and delay margin. xvi. Methods are developed to control NMP plants without knowledge of the NMP zero. Specifically, a decentralized feedback-feedforward architecture as well as quasi- FIR controllers are considered, where the FIR controller operates in parallel with an internal model controller in order to follow commands for NMP plants without knowledge of the NMP zeros. Next, the following question is considered: Are all full-order dynamic compen- sators observer-based? It is shown that the only case where a dynamic compensator is not observer-based is the case where n is odd and the closed-loop spectrum has no real eigenvalues. Since this is the case, such controllers are necessarily suboptimal in the sense of LQG. This question is relevant to understanding the closed-loop pole locations arising from full-order RCAC compensators. Finally, retrospective cost model refinement (RCMR

  13. The adaptive cruise control vehicles in the cellular automata model

    International Nuclear Information System (INIS)

    Jiang Rui; Wu Qingsong

    2006-01-01

    This Letter presented a cellular automata model where the adaptive cruise control vehicles are modelled. In this model, the constant time headway policy is adopted. The fundamental diagram is presented. The simulation results are in good agreement with the analytical ones. The mixture of ACC vehicles with manually driven vehicles is investigated. It is shown that with the introduction of ACC vehicles, the jam can be suppressed

  14. Adaptive Disturbance Estimation for Offset-Free SISO Model Predictive Control

    DEFF Research Database (Denmark)

    Huusom, Jakob Kjøbsted; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay

    2011-01-01

    Offset free tracking in Model Predictive Control requires estimation of unmeasured disturbances or the inclusion of an integrator. An algorithm for estimation of an unknown disturbance based on adaptive estimation with time varying forgetting is introduced and benchmarked against the classical...

  15. Efficient speed control of induction motor using RBF based model reference adaptive control method

    OpenAIRE

    Kilic, Erdal; Ozcalik, Hasan Riza; Yilmaz, Saban

    2017-01-01

    This paper proposes a model reference adaptive speed controller based on artificial neural network for induction motor drives. The performance of traditional feedback controllers has been insufficient in speed control of induction motors due to nonlinear structure of the system, changing environmental conditions, and disturbance input effects. A successful speed control of induction motor requires a nonlinear control system. On the other hand, in recent years, it has been demonstrated that ar...

  16. Model reference adaptive vector control for induction motor without speed sensor

    Directory of Open Access Journals (Sweden)

    Bo Fan

    2017-01-01

    Full Text Available The wide applications of vector control improve the high-accuracy performance of alternating current (AC adjustable speed system. In order to obverse the full-order flux and calculate the real-time speed, this article introduces the motor T equivalent circuit to build a full-order flux observer model, where the current and flux variables of stator and rotor are adopted. Model reference adaptive control is introduced to build the AC motor flux observer. The current output is used as feedback to build the feedback matrix. The calculation method of motor speed, which is part of the inputs of flux observation, is applied to realize the adaptive control. The concept of characteristic function is introduced to calculate the flux, of which the foundation is the variables of composite form of voltage and current models. The characteristic function is deduced as a relative-state variable function. The feedback matrix is improved and designed to ensure the motor flux observer is a smooth switch between current and voltage model in low and high speeds, respectively. Experimental results show that the feedback and characteristic model are feasible, and the vector control with speed sensorless based on the full-order flux observer has better performance and anti-disturbance.

  17. Decision models for use with criterion-referenced tests

    NARCIS (Netherlands)

    van der Linden, Willem J.

    1980-01-01

    The problem of mastery decisions and optimizing cutoff scores on criterion-referenced tests is considered. This problem can be formalized as an (empirical) Bayes problem with decisions rules of a monotone shape. Next, the derivation of optimal cutoff scores for threshold, linear, and normal ogive

  18. Memory for details with self-referencing.

    Science.gov (United States)

    Serbun, Sarah J; Shih, Joanne Y; Gutchess, Angela H

    2011-11-01

    Self-referencing benefits item memory, but little is known about the ways in which referencing the self affects memory for details. Experiment 1 assessed whether the effects of self-referencing operate only at the item, or general, level or whether they also enhance memory for specific visual details of objects. Participants incidentally encoded objects by making judgements in reference to the self, a close other (one's mother), or a familiar other (Bill Clinton). Results indicate that referencing the self or a close other enhances both specific and general memory. Experiments 2 and 3 assessed verbal memory for source in a task that relied on distinguishing between different mental operations (internal sources). The results indicate that self-referencing disproportionately enhances source memory, relative to conditions referencing other people, semantic, or perceptual information. We conclude that self-referencing not only enhances specific memory for both visual and verbal information, but can also disproportionately improve memory for specific internal source details.

  19. Model-free adaptive speed control on travelling wave ultrasonic motor

    Science.gov (United States)

    Di, Sisi; Li, Huafeng

    2018-01-01

    This paper introduced a new data-driven control (DDC) method for the speed control of ultrasonic motor (USM). The model-free adaptive control (MFAC) strategy was presented in terms of its principles, algorithms, and parameter selection. To verify the efficiency of the proposed method, a speed-frequency-time model, which contained all the measurable nonlinearity and uncertainties based on experimental data was established for simulation to mimic the USM operation system. Furthermore, the model was identified using particle swarm optimization (PSO) method. Then, the control of the simulated system using MFAC was evaluated under different expectations in terms of overshoot, rise time and steady-state error. Finally, the MFAC results were compared with that of proportion iteration differentiation (PID) to demonstrate its advantages in controlling general random system.

  20. An implicit adaptation algorithm for a linear model reference control system

    Science.gov (United States)

    Mabius, L.; Kaufman, H.

    1975-01-01

    This paper presents a stable implicit adaptation algorithm for model reference control. The constraints for stability are found using Lyapunov's second method and do not depend on perfect model following between the system and the reference model. Methods are proposed for satisfying these constraints without estimating the parameters on which the constraints depend.

  1. Unemployment estimation: Spatial point referenced methods and models

    KAUST Repository

    Pereira, Soraia

    2017-06-26

    Portuguese Labor force survey, from 4th quarter of 2014 onwards, started geo-referencing the sampling units, namely the dwellings in which the surveys are carried. This opens new possibilities in analysing and estimating unemployment and its spatial distribution across any region. The labor force survey choose, according to an preestablished sampling criteria, a certain number of dwellings across the nation and survey the number of unemployed in these dwellings. Based on this survey, the National Statistical Institute of Portugal presently uses direct estimation methods to estimate the national unemployment figures. Recently, there has been increased interest in estimating these figures in smaller areas. Direct estimation methods, due to reduced sampling sizes in small areas, tend to produce fairly large sampling variations therefore model based methods, which tend to

  2. Adaptive hybrid control of manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.

  3. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  4. Direct adaptive control of manipulators in Cartesian space

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

  5. Adaptive control method for core power control in TRIGA Mark II reactor

    Science.gov (United States)

    Sabri Minhat, Mohd; Selamat, Hazlina; Subha, Nurul Adilla Mohd

    2018-01-01

    The 1MWth Reactor TRIGA PUSPATI (RTP) Mark II type has undergone more than 35 years of operation. The existing core power control uses feedback control algorithm (FCA). It is challenging to keep the core power stable at the desired value within acceptable error bands to meet the safety demand of RTP due to the sensitivity of nuclear research reactor operation. Currently, the system is not satisfied with power tracking performance and can be improved. Therefore, a new design core power control is very important to improve the current performance in tracking and regulate reactor power by control the movement of control rods. In this paper, the adaptive controller and focus on Model Reference Adaptive Control (MRAC) and Self-Tuning Control (STC) were applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, adaptive controller model, and control rods selection programming. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The adaptive control model was presented using Lyapunov method to ensure stable close loop system and STC Generalised Minimum Variance (GMV) Controller was not necessary to know the exact plant transfer function in designing the core power control. The performance between proposed adaptive control and FCA will be compared via computer simulation and analysed the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

  6. Modeling and Control of Magnetic Fluid Deformable Mirrors for Adaptive Optics Systems

    CERN Document Server

    Wu, Zhizheng; Ben Amara, Foued

    2013-01-01

    Modeling and Control of Magnetic Fluid Deformable Mirrors for Adaptive Optics Systems presents a novel design of wavefront correctors based on magnetic fluid deformable mirrors (MFDM) as well as corresponding control algorithms. The presented wavefront correctors are characterized by their linear, dynamic response. Various mirror surface shape control algorithms are presented along with experimental evaluations of the performance of the resulting adaptive optics systems. Adaptive optics (AO) systems are used in various fields of application to enhance the performance of optical systems, such as imaging, laser, free space optical communication systems, etc. This book is intended for undergraduate and graduate students, professors, engineers, scientists and researchers working on the design of adaptive optics systems and their various emerging fields of application. Zhizheng Wu is an associate professor at Shanghai University, China. Azhar Iqbal is a research associate at the University of Toronto, Canada. Foue...

  7. Temperature uniformity control in RTP using multivariable adaptive control

    Energy Technology Data Exchange (ETDEWEB)

    Morales, S.; Dahhou, B.; Dilhac, J.M. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Morales, S.

    1995-12-31

    In Rapid Thermal Processing (RTP) control of the wafer temperature during all processing to get good trajectory following, together with spatial temperature uniformity, is essential. It is well know as RTP process is nonlinear, classical control laws are not very efficient. In this work, the authors aim at studying the applicability of MIMO (Multiple Inputs Multiple Outputs) adaptive techniques to solve the temperature control problems in RTP. A multivariable linear discrete time CARIMA (Controlled Auto Regressive Integrating Moving Average) model of the highly non-linear process is identified on-line using a robust identification technique. The identified model is used to compute an infinite time LQ (Linear Quadratic) based control law, with a partial state reference model. This reference model smooths the original setpoint sequence, and at the same time gives a tracking capability to the LQ control law. After an experimental open-loop investigation, the results of the application of the adaptive control law are presented. Finally, some comments on the future difficulties and developments of the application of adaptive control in RTP are given. (author) 13 refs.

  8. Modelling and L1 Adaptive Control of pH in Bioethanol Enzymatic Process

    DEFF Research Database (Denmark)

    Prunescu, Remus Mihail; Blanke, Mogens; Sin, Gürkan

    2013-01-01

    for pH level regulation: one is a classical PI controller; the other an L1 adaptive output feedback controller. Model-based feed-forward terms are added to the controllers to enhance their performances. A new tuning method of the L1 adaptive controller is also proposed. Further, a new performance...... function is formulated and tailored to this type of processes and is used to monitor the performances of the process in closed loop. The L1 design is found to outperform the PI controller in all tests....

  9. Trajectory Planning and Optimized Adaptive Control for a Class of Wheeled Inverted Pendulum Vehicle Models.

    Science.gov (United States)

    Yang, Chenguang; Li, Zhijun; Li, Jing

    2013-02-01

    In this paper, we investigate optimized adaptive control and trajectory generation for a class of wheeled inverted pendulum (WIP) models of vehicle systems. Aiming at shaping the controlled vehicle dynamics to be of minimized motion tracking errors as well as angular accelerations, we employ the linear quadratic regulation optimization technique to obtain an optimal reference model. Adaptive control has then been developed using variable structure method to ensure the reference model to be exactly matched in a finite-time horizon, even in the presence of various internal and external uncertainties. The minimized yaw and tilt angular accelerations help to enhance the vehicle rider's comfort. In addition, due to the underactuated mechanism of WIP, the vehicle forward velocity dynamics cannot be controlled separately from the pendulum tilt angle dynamics. Inspired by the control strategy of human drivers, who usually manipulate the tilt angle to control the forward velocity, we design a neural-network-based adaptive generator of implicit control trajectory (AGICT) of the tilt angle which indirectly "controls" the forward velocity such that it tracks the desired velocity asymptotically. The stability and optimal tracking performance have been rigorously established by theoretic analysis. In addition, simulation studies have been carried out to demonstrate the efficiency of the developed AGICT and optimized adaptive controller.

  10. A Geo-referenced 3D model of the Juan de Fuca Slab and associated seismicity

    Science.gov (United States)

    Blair, J.L.; McCrory, P.A.; Oppenheimer, D.H.; Waldhauser, F.

    2011-01-01

    We present a Geographic Information System (GIS) of a new 3-dimensional (3D) model of the subducted Juan de Fuca Plate beneath western North America and associated seismicity of the Cascadia subduction system. The geo-referenced 3D model was constructed from weighted control points that integrate depth information from hypocenter locations and regional seismic velocity studies. We used the 3D model to differentiate earthquakes that occur above the Juan de Fuca Plate surface from earthquakes that occur below the plate surface. This GIS project of the Cascadia subduction system supersedes the one previously published by McCrory and others (2006). Our new slab model updates the model with new constraints. The most significant updates to the model include: (1) weighted control points to incorporate spatial uncertainty, (2) an additional gridded slab surface based on the Generic Mapping Tools (GMT) Surface program which constructs surfaces based on splines in tension (see expanded description below), (3) double-differenced hypocenter locations in northern California to better constrain slab location there, and (4) revised slab shape based on new hypocenter profiles that incorporate routine depth uncertainties as well as data from new seismic-reflection and seismic-refraction studies. We also provide a 3D fly-through animation of the model for use as a visualization tool.

  11. An Adaptive Critic Approach to Reference Model Adaptation

    Science.gov (United States)

    Krishnakumar, K.; Limes, G.; Gundy-Burlet, K.; Bryant, D.

    2003-01-01

    Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

  12. Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center

    Science.gov (United States)

    Zia, Omar

    1989-01-01

    The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.

  13. A Nonlinear Ship Manoeuvering Model: Identification and adaptive control with experiments for a model ship

    Directory of Open Access Journals (Sweden)

    Roger Skjetne

    2004-01-01

    Full Text Available Complete nonlinear dynamic manoeuvering models of ships, with numerical values, are hard to find in the literature. This paper presents a modeling, identification, and control design where the objective is to manoeuver a ship along desired paths at different velocities. Material from a variety of references have been used to describe the ship model, its difficulties, limitations, and possible simplifications for the purpose of automatic control design. The numerical values of the parameters in the model is identified in towing tests and adaptive manoeuvering experiments for a small ship in a marine control laboratory.

  14. Differential flatness properties and adaptive control of the hypothalamic-pituitary-adrenal axis model

    Science.gov (United States)

    Rigatos, Gerasimos

    2016-12-01

    It is shown that the model of the hypothalamic-pituitary-adrenal gland axis is a differentially flat one and this permits to transform it to the so-called linear canonical form. For the new description of the system's dynamics the transformed control inputs contain unknown terms which depend on the system's parameters. To identify these terms an adaptive fuzzy approximator is used in the control loop. Thus an adaptive fuzzy control scheme is implemented in which the unknown or unmodeled system dynamics is approximated by neurofuzzy networks and next this information is used by a feedback controller that makes the state variables (CRH - corticotropin releasing hormone, adenocortocotropic hormone - ACTH, cortisol) of the hypothalamic-pituitary-adrenal gland axis model converge to the desirable levels (setpoints). This adaptive control scheme is exclusively implemented with the use of output feedback, while the state vector elements which are not directly measured are estimated with the use of a state observer that operates in the control loop. The learning rate of the adaptive fuzzy system is suitably computed from Lyapunov analysis, so as to assure that both the learning procedure for the unknown system's parameters, the dynamics of the observer and the dynamics of the control loop will remain stable. The performed Lyapunov stability analysis depends on two Riccati equations, one associated with the feedback controller and one associated with the state observer. Finally, it is proven that for the control scheme that comprises the feedback controller, the state observer and the neurofuzzy approximator, an H-infinity tracking performance can be succeeded.

  15. Neural Control and Adaptive Neural Forward Models for Insect-like, Energy-Efficient, and Adaptable Locomotion of Walking Machines

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin

    2013-01-01

    such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast...... on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models...... allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show...

  16. Reference-shaping adaptive control by using gradient descent optimizers.

    Directory of Open Access Journals (Sweden)

    Baris Baykant Alagoz

    Full Text Available This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC method for several test scenarios. An experimental study demonstrates application of method for rotor control.

  17. Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

    Science.gov (United States)

    Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

    2015-02-01

    The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

  18. Correlations in state space can cause sub-optimal adaptation of optimal feedback control models

    OpenAIRE

    Aprasoff, Jonathan; Donchin, Opher

    2011-01-01

    Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedb...

  19. Adaptive control of discrete-time chaotic systems: a fuzzy control approach

    International Nuclear Information System (INIS)

    Feng Gang; Chen Guanrong

    2005-01-01

    This paper discusses adaptive control of a class of discrete-time chaotic systems from a fuzzy control approach. Using the T-S model of discrete-time chaotic systems, an adaptive control algorithm is developed based on some conventional adaptive control techniques. The resulting adaptively controlled chaotic system is shown to be globally stable, and its robustness is discussed. A simulation example of the chaotic Henon map control is finally presented, to illustrate an application and the performance of the proposed control algorithm

  20. Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

    Science.gov (United States)

    Nguyen, Nhan T.

    2012-01-01

    This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

  1. The cost of model reference adaptive control - Analysis, experiments, and optimization

    Science.gov (United States)

    Messer, R. S.; Haftka, R. T.; Cudney, H. H.

    1993-01-01

    In this paper the performance of Model Reference Adaptive Control (MRAC) is studied in numerical simulations and verified experimentally with the objective of understanding how differences between the plant and the reference model affect the control effort. MRAC is applied analytically and experimentally to a single degree of freedom system and analytically to a MIMO system with controlled differences between the model and the plant. It is shown that the control effort is sensitive to differences between the plant and the reference model. The effects of increased damping in the reference model are considered, and it is shown that requiring the controller to provide increased damping actually decreases the required control effort when differences between the plant and reference model exist. This result is useful because one of the first attempts to counteract the increased control effort due to differences between the plant and reference model might be to require less damping, however, this would actually increase the control effort. Optimization of weighting matrices is shown to help reduce the increase in required control effort. However, it was found that eventually the optimization resulted in a design that required an extremely high sampling rate for successful realization.

  2. Adaptive Control Algorithm of the Synchronous Generator

    Directory of Open Access Journals (Sweden)

    Shevchenko Victor

    2017-01-01

    Full Text Available The article discusses the the problem of controlling a synchronous generator, namely, maintaining the stability of the control object in the conditions of occurrence of noise and disturbances in the regulatory process. The model of a synchronous generator is represented by a system of differential equations of Park-Gorev, where state variables are computed relative to synchronously rotating d, q-axis. Management of synchronous generator is proposed to organize on the basis of the position-path control using algorithms to adapt with the reference model. Basic control law directed on the stabilizing indicators the frequency generated by the current and the required power level, which is achieved by controlling the mechanical torque on the shaft of the turbine and the value of the excitation voltage of the synchronous generator. Modification of the classic adaptation algorithm using the reference model, allowing to minimize the error of the reference regulation and the model under investigation within the prescribed limits, produced by means of the introduction of additional variables controller adaptation in the model. Сarried out the mathematical modeling of control provided influence on the studied model of continuous nonlinear and unmeasured the disturbance. Simulation results confirm the high level accuracy of tracking and adaptation investigated model with respect to the reference, and the present value of the loop error depends on parameters performance of regulator.

  3. Speed Sensorless Control of PMSM using Model Reference Adaptive System and RBFN

    OpenAIRE

    Wei Gao; Zhirong Guo

    2013-01-01

    In the speed sensorless vector control system, the amended method of estimating the rotor speed about model reference adaptive system (MRAS) based on radial basis function neural network (RBFN) for PMSM sensorless vector control system was presented. Based on the PI regulator, the radial basis function neural network which is more prominent learning efficiency and performance is combined with MRAS. The reference model and the adjust model are the PMSM itself and the PMSM current, respectively...

  4. A fuzzy model based adaptive PID controller design for nonlinear and uncertain processes.

    Science.gov (United States)

    Savran, Aydogan; Kahraman, Gokalp

    2014-03-01

    We develop a novel adaptive tuning method for classical proportional-integral-derivative (PID) controller to control nonlinear processes to adjust PID gains, a problem which is very difficult to overcome in the classical PID controllers. By incorporating classical PID control, which is well-known in industry, to the control of nonlinear processes, we introduce a method which can readily be used by the industry. In this method, controller design does not require a first principal model of the process which is usually very difficult to obtain. Instead, it depends on a fuzzy process model which is constructed from the measured input-output data of the process. A soft limiter is used to impose industrial limits on the control input. The performance of the system is successfully tested on the bioreactor, a highly nonlinear process involving instabilities. Several tests showed the method's success in tracking, robustness to noise, and adaptation properties. We as well compared our system's performance to those of a plant with altered parameters with measurement noise, and obtained less ringing and better tracking. To conclude, we present a novel adaptive control method that is built upon the well-known PID architecture that successfully controls highly nonlinear industrial processes, even under conditions such as strong parameter variations, noise, and instabilities. © 2013 Published by ISA on behalf of ISA.

  5. Adaptive control system having hedge unit and related apparatus and methods

    Science.gov (United States)

    Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

    2007-01-01

    The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

  6. Theoretical model for ultracold molecule formation via adaptive feedback control

    OpenAIRE

    Poschinger, Ulrich; Salzmann, Wenzel; Wester, Roland; Weidemueller, Matthias; Koch, Christiane P.; Kosloff, Ronnie

    2006-01-01

    We investigate pump-dump photoassociation of ultracold molecules with amplitude- and phase-modulated femtosecond laser pulses. For this purpose a perturbative model for the light-matter interaction is developed and combined with a genetic algorithm for adaptive feedback control of the laser pulse shapes. The model is applied to the formation of 85Rb2 molecules in a magneto-optical trap. We find for optimized pulse shapes an improvement for the formation of ground state molecules by more than ...

  7. Adaptive neural network motion control for aircraft under uncertainty conditions

    Science.gov (United States)

    Efremov, A. V.; Tiaglik, M. S.; Tiumentsev, Yu V.

    2018-02-01

    We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

  8. Model-free adaptive control optimization using a chaotic particle swarm approach

    Energy Technology Data Exchange (ETDEWEB)

    Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br; Rodrigues Coelho, Antonio Augusto [Department of Automation and Systems, Federal University of Santa Catarina, Box 476, 88040-900 Florianopolis, Santa Catarina (Brazil)], E-mail: aarc@das.ufsc.br

    2009-08-30

    It is well known that conventional control theories are widely suited for applications where the processes can be reasonably described in advance. However, when the plant's dynamics are hard to characterize precisely or are subject to environmental uncertainties, one may encounter difficulties in applying the conventional controller design methodologies. Despite the difficulty in achieving high control performance, the fine tuning of controller parameters is a tedious task that always requires experts with knowledge in both control theory and process information. Nowadays, more and more studies have focused on the development of adaptive control algorithms that can be directly applied to complex processes whose dynamics are poorly modeled and/or have severe nonlinearities. In this context, the design of a Model-Free Learning Adaptive Control (MFLAC) based on pseudo-gradient concepts and optimization procedure by a Particle Swarm Optimization (PSO) approach using constriction coefficient and Henon chaotic sequences (CPSOH) is presented in this paper. PSO is a stochastic global optimization technique inspired by social behavior of bird flocking. The PSO models the exploration of a problem space by a population of particles. Each particle in PSO has a randomized velocity associated to it, which moves through the space of the problem. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed CPSOH introduces chaos mapping which introduces some flexibility in particle movements in each iteration. The chaotic sequences allow also explorations at early stages and exploitations at later stages during the search procedure of CPSOH. Motivation for application of CPSOH approach is to overcome the limitation of the conventional MFLAC design, which cannot guarantee satisfactory control performance when the plant has different gains for the operational range when designed by trial-and-error by user. Numerical results of the MFLAC with

  9. Model-free adaptive control optimization using a chaotic particle swarm approach

    International Nuclear Information System (INIS)

    Santos Coelho, Leandro dos; Rodrigues Coelho, Antonio Augusto

    2009-01-01

    It is well known that conventional control theories are widely suited for applications where the processes can be reasonably described in advance. However, when the plant's dynamics are hard to characterize precisely or are subject to environmental uncertainties, one may encounter difficulties in applying the conventional controller design methodologies. Despite the difficulty in achieving high control performance, the fine tuning of controller parameters is a tedious task that always requires experts with knowledge in both control theory and process information. Nowadays, more and more studies have focused on the development of adaptive control algorithms that can be directly applied to complex processes whose dynamics are poorly modeled and/or have severe nonlinearities. In this context, the design of a Model-Free Learning Adaptive Control (MFLAC) based on pseudo-gradient concepts and optimization procedure by a Particle Swarm Optimization (PSO) approach using constriction coefficient and Henon chaotic sequences (CPSOH) is presented in this paper. PSO is a stochastic global optimization technique inspired by social behavior of bird flocking. The PSO models the exploration of a problem space by a population of particles. Each particle in PSO has a randomized velocity associated to it, which moves through the space of the problem. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed CPSOH introduces chaos mapping which introduces some flexibility in particle movements in each iteration. The chaotic sequences allow also explorations at early stages and exploitations at later stages during the search procedure of CPSOH. Motivation for application of CPSOH approach is to overcome the limitation of the conventional MFLAC design, which cannot guarantee satisfactory control performance when the plant has different gains for the operational range when designed by trial-and-error by user. Numerical results of the MFLAC with CPSOH

  10. Psychoanalytic theory and loving God concepts: parent referencing versus self-referencing.

    Science.gov (United States)

    Buri, J R; Mueller, R A

    1993-01-01

    We investigated the relationship of college students' conceptions of the wrathfulness-kindliness of God to their parents' nurturance, their parents' permissiveness, authoritarianism, and authoritativeness, and the students' own self-esteem. Although parents' nurturance, authoritarianism, and authoritativeness were related to participants' conceptions of God (thus providing some support for psychoanalytic assertions), the variable of self-esteem far outweighed all other variables in accounting for the variance in God concepts. These results suggest that self-referencing explanations better account for individuals' conceptions of God than do parent referencing (i.e., psychoanalytic) explanations.

  11. Direct model reference adaptive control with application to flexible robots

    Science.gov (United States)

    Steinvorth, Rodrigo; Kaufman, Howard; Neat, Gregory W.

    1992-01-01

    A modification to a direct command generator tracker-based model reference adaptive control (MRAC) system is suggested in this paper. This modification incorporates a feedforward into the reference model's output as well as the plant's output. Its purpose is to eliminate the bounded model following error present in steady state when previous MRAC systems were used. The algorithm was evaluated using the dynamics for a single-link flexible-joint arm. The results of these simulations show a response with zero steady state model following error. These results encourage further use of MRAC for various types of nonlinear plants.

  12. Adaptive control of a Stewart platform-based manipulator

    Science.gov (United States)

    Nguyen, Charles C.; Antrazi, Sami S.; Zhou, Zhen-Lei; Campbell, Charles E., Jr.

    1993-01-01

    A joint-space adaptive control scheme for controlling noncompliant motion of a Stewart platform-based manipulator (SPBM) was implemented in the Hardware Real-Time Emulator at Goddard Space Flight Center. The six-degrees of freedom SPBM uses two platforms and six linear actuators driven by dc motors. The adaptive control scheme is based on proportional-derivative controllers whose gains are adjusted by an adaptation law based on model reference adaptive control and Liapunov direct method. It is concluded that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.

  13. Model-free adaptive control of supercritical circulating fluidized-bed boilers

    Science.gov (United States)

    Cheng, George Shu-Xing; Mulkey, Steven L

    2014-12-16

    A novel 3-Input-3-Output (3.times.3) Fuel-Air Ratio Model-Free Adaptive (MFA) controller is introduced, which can effectively control key process variables including Bed Temperature, Excess O2, and Furnace Negative Pressure of combustion processes of advanced boilers. A novel 7-input-7-output (7.times.7) MFA control system is also described for controlling a combined 3-Input-3-Output (3.times.3) process of Boiler-Turbine-Generator (BTG) units and a 5.times.5 CFB combustion process of advanced boilers. Those boilers include Circulating Fluidized-Bed (CFB) Boilers and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  14. Adaptive Control Of Remote Manipulator

    Science.gov (United States)

    Seraji, Homayoun

    1989-01-01

    Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

  15. Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

    Science.gov (United States)

    Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

    2018-01-01

    This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

  16. Model-Free Adaptive Control Algorithm with Data Dropout Compensation

    Directory of Open Access Journals (Sweden)

    Xuhui Bu

    2012-01-01

    Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.

  17. Influence of Electrotactile Tongue Feedback on Controlling Upright Stance during Rotational and/or Translational Sway-referencing with Galvanic Vestibular Stimulation

    Science.gov (United States)

    Wood, Scott J.; Tyler, Mitchell E.; Bach-y-Rita, Paul; MacDougall, Hamish G.; Moore, Steven T.; Stallings, Valerie L.; Paloski, William H.; Black, F. Owen

    2007-01-01

    Integration of multi-sensory inputs to detect tilts relative to gravity is critical for sensorimotor control of upright orientation. Displaying body orientation using electrotactile feedback to the tongue has been developed by Bach-y-Rita and colleagues as a sensory aid to maintain upright stance with impaired vestibular feedback. MacDougall et al. (2006) recently demonstrated that unpredictably varying Galvanic vestibular stimulation (GVS) significantly increased anterior-posterior (AP) sway during rotational sway referencing with eyes closed. The purpose of this study was to assess the influence of electrotactile feedback on postural control performance with pseudorandom binaural bipolar GVS. Postural equilibrium was measured with a computerized hydraulic platform in 10 healthy adults (6M, 4F, 24-65 y). Tactile feedback (TF) of pitch and roll body orientation was derived from a two-axis linear accelerometer mounted on a torso belt and displayed on a 144-point electrotactile array held against the anterior dorsal tongue (BrainPort, Wicab, Inc., Middleton, WI). Subjects were trained to use TF by voluntarily swaying to draw figures on their tongue, both with and without GVS. Subjects were required to keep the intraoral display in their mouths on all trials, including those that did not provide TF. Subjects performed 24 randomized trials (20 s duration with eyes closed) including four support surface conditions (fixed, rotational sway-referenced, translating the support surface proportional to AP sway, and combined rotational-translational sway-referencing), each repeated twice with and without GVS, and with combined GVS and TF. Postural performance was assessed using deviations from upright (peak-to-peak and RMS sway) and convergence toward stability limits (time and distance to base of support boundaries). Postural stability was impaired with GVS in all platform conditions, with larger decrements in performance during trials with rotation sway-referencing

  18. Robust adaptive control modeling of human arm movements subject to altered gravity and mechanical loads

    Science.gov (United States)

    Tryfonidis, Michail

    It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that

  19. Dual RBFNNs-Based Model-Free Adaptive Control With Aspen HYSYS Simulation.

    Science.gov (United States)

    Zhu, Yuanming; Hou, Zhongsheng; Qian, Feng; Du, Wenli

    2017-03-01

    In this brief, we propose a new data-driven model-free adaptive control (MFAC) method with dual radial basis function neural networks (RBFNNs) for a class of discrete-time nonlinear systems. The main novelty lies in that it provides a systematic design method for controller structure by the direct usage of I/O data, rather than using the first-principle model or offline identified plant model. The controller structure is determined by equivalent-dynamic-linearization representation of the ideal nonlinear controller, and the controller parameters are tuned by the pseudogradient information extracted from the I/O data of the plant, which can deal with the unknown nonlinear system. The stability of the closed-loop control system and the stability of the training process for RBFNNs are guaranteed by rigorous theoretical analysis. Meanwhile, the effectiveness and the applicability of the proposed method are further demonstrated by the numerical example and Aspen HYSYS simulation of distillation column in crude styrene produce process.

  20. A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

    Science.gov (United States)

    Arabi, Ehsan; Gruenwald, Benjamin C.; Yucelen, Tansel; Nguyen, Nhan T.

    2018-05-01

    Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.

  1. Extended Model-Based Feedforward Compensation in L1 Adaptive Control for Mechanical Manipulators: Design and Experiments

    Directory of Open Access Journals (Sweden)

    Moussab eBennehar

    2015-12-01

    Full Text Available This paper deals with a new control scheme for Parallel Kinematic Manipulators (PKMs based on the L1 adaptive control theory. The original L1 adaptive controller is extended by including an adaptive loop based on the dynamics of the PKM. The additional model-based term is in charge of the compensation of the modeled nonlinear dynamics in the aim of improving the tracking performance. Moreover, the proposed controller is enhanced to reduce the internal forces, which may appear in the case of Redundantly Actuated PKMs (RA-PKMs. The generated control inputs are first regulated through a projection mechanism that reduces the antagonistic internal forces, before being applied to the manipulator. To validate the proposed controller and to show its effectiveness, real-time experiments are conducted on a new four degrees-of-freedom (4-DOFs RA-PKM developed in our laboratory.

  2. Assessment of Model Predictive and Adaptive Glucose Control Strategies for People with Type 1 Diabetes

    DEFF Research Database (Denmark)

    Boiroux, Dimitri; Duun-Henriksen, Anne Katrine; Schmidt, Signe

    2014-01-01

    This paper addresses overnight blood glucose stabilization in people with type 1 diabetes using a Model Predictive Controller (MPC). We use a control strategy based on an adaptive ARMAX model in which we use a Recursive Extended Least Squares (RELS) method to estimate parameters of the stochastic...... and reduce the risk of hypoglycemia. We test our control strategies on a virtual clinic of 100 randomly generated patients with a representative inter-subject variability. This virtual clinic is based on the Hovorka model. We consider the case where only half of the meal bolus is administered at mealtime......, and the case where the insulin sensitivity varies during the night. The simulation results demonstrate that the adaptive control strategy can reduce the risks of hypoglycemia and hyperglycemia during the night....

  3. Adaptive Flight Control Research at NASA

    Science.gov (United States)

    Motter, Mark A.

    2008-01-01

    A broad overview of current adaptive flight control research efforts at NASA is presented, as well as some more detailed discussion of selected specific approaches. The stated objective of the Integrated Resilient Aircraft Control Project, one of NASA s Aviation Safety programs, is to advance the state-of-the-art of adaptive controls as a design option to provide enhanced stability and maneuverability margins for safe landing in the presence of adverse conditions such as actuator or sensor failures. Under this project, a number of adaptive control approaches are being pursued, including neural networks and multiple models. Validation of all the adaptive control approaches will use not only traditional methods such as simulation, wind tunnel testing and manned flight tests, but will be augmented with recently developed capabilities in unmanned flight testing.

  4. Adaptive Nonsingular Terminal Sliding Model Control and Its Application to Permanent Magnet Synchronous Motor Drive System

    OpenAIRE

    Liu Yue; Zhou Shuo

    2016-01-01

    To improve the dynamic performance of permanent magnet synchronous motor(PMSM) drive system, a adaptive nonsingular terminal sliding model control((NTSMC) strategy was proposed. The proposed control strategy presents an adaptive variable-rated exponential reaching law which the L1 norm of state variables is introduced. Exponential and constant approach speed can adaptively adjust according to the state variables’ distance to the equilibrium position.The proposed scheme can shorten the reachin...

  5. Dynamic optimization and adaptive controller design

    Science.gov (United States)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  6. Adaptive PI Controller for a Nonlinear System

    Directory of Open Access Journals (Sweden)

    D. Rathikarani

    2009-10-01

    Full Text Available Most of the industrial processes are inherently nonlinear in their behaviour. Designs of controllers for these nonlinear processes are difficult, as they do not follow superposition theorem. Adaptive controller can change its behaviour in response to changes in the dynamics of the process and disturbances. Hence adaptive controller can be used to control nonlinear processes. Direct Model Reference Adaptive Control is a technique, in which a reference model involving the desired performances is specified. In the present work, a DMRAC is designed and implemented to achieve satisfactory control of a nonlinear system in all its local linear operating regions. The closed loop system is made BIBO stable by proper control techniques. The controller is designed through simulation in Matlab platform and is validated in real time by conducting experiments on the laboratory Air Flow Control System using the dSPACE interface.

  7. Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

    Science.gov (United States)

    Nandola, Naresh N.; Rivera, Daniel E.

    2011-01-01

    This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

  8. An adaptive nonlinear internal-model control for the speed control of homopolar salient-pole BLDC motor

    Science.gov (United States)

    CheshmehBeigi, Hassan Moradi

    2018-05-01

    In this paper, a novel speed control method for Homopolar Brushless DC (HBLDC) motor based on the adaptive nonlinear internal-model control (ANIMC) is presented. Rotor position information is obtained online by the Hall-Effect sensors placed on the motor's shaft, and is used to calculate the accurate model and accurate inverse model of the HBLDC motor. The online inverse model of the motor is used in the controller structure. To suppress the reference ? error, the negative feedback of difference between the motor speed and its model output ? is applied in the proposed controller. An appropriate signal is the output of the controller, which drives the power switches to converge the motor speed to the constant desired speed. Simulations and experiments are carried out on a ? three-phase HBLDC motor. The proposed drive system operates well in the speed response and has good robustness with respect to the disturbances. To validate the theoretical analysis, several experimental results are discussed in this paper.

  9. Enzymatic Synthesis of Ampicillin: Nonlinear Modeling, Kinetics Estimation, and Adaptive Control

    Directory of Open Access Journals (Sweden)

    Monica Roman

    2012-01-01

    Full Text Available Nowadays, the use of advanced control strategies in biotechnology is quite low. A main reason is the lack of quality of the data, and the fact that more sophisticated control strategies must be based on a model of the dynamics of bioprocesses. The nonlinearity of the bioprocesses and the absence of cheap and reliable instrumentation require an enhanced modeling effort and identification strategies for the kinetics. The present work approaches modeling and control strategies for the enzymatic synthesis of ampicillin that is carried out inside a fed-batch bioreactor. First, a nonlinear dynamical model of this bioprocess is obtained by using a novel modeling procedure for biotechnology: the bond graph methodology. Second, a high gain observer is designed for the estimation of the imprecisely known kinetics of the synthesis process. Third, by combining an exact linearizing control law with the on-line estimation kinetics algorithm, a nonlinear adaptive control law is designed. The case study discussed shows that a nonlinear feedback control strategy applied to the ampicillin synthesis bioprocess can cope with disturbances, noisy measurements, and parametric uncertainties. Numerical simulations performed with MATLAB environment are included in order to test the behavior and the performances of the proposed estimation and control strategies.

  10. Applications of adaptive filters in active noise control

    Science.gov (United States)

    Darlington, Paul

    The active reduction of acoustic noise is achieved by the addition of a cancelling acoustic signal to the unwanted sound. Successful definition of the cancelling signal amounts to a system identification problem. Recent advances in adaptive signal processing have allowed this problem to be tackled using adaptive filters, which offer significant advantages over conventional solutions. The extension of adaptive noise cancelling techniques, which were developed in the electrical signal conditioning context, to the control of acoustic systems is studied. An analysis is presented of the behavior of the Widrow-Hoff LMS adaptive noise canceller with a linear filter in its control loop. The active control of plane waves propagating axially in a hardwalled duct is used as a motivating model problem. The model problem also motivates the study of the effects of feedback around an LMS adaptive filter. An alternative stochastic gradient algorithm for controlling adaptive filters in the presence of feedback is presented.

  11. Control-oriented modeling and adaptive backstepping control for a nonminimum phase hypersonic vehicle.

    Science.gov (United States)

    Ye, Linqi; Zong, Qun; Tian, Bailing; Zhang, Xiuyun; Wang, Fang

    2017-09-01

    In this paper, the nonminimum phase problem of a flexible hypersonic vehicle is investigated. The main challenge of nonminimum phase is the prevention of dynamic inversion methods to nonlinear control design. To solve this problem, we make research on the relationship between nonminimum phase and backstepping control, finding that a stable nonlinear controller can be obtained by changing the control loop on the basis of backstepping control. By extending the control loop to cover the internal dynamics in it, the internal states are directly controlled by the inputs and simultaneously serve as virtual control for the external states, making it possible to guarantee output tracking as well as internal stability. Then, based on the extended control loop, a simplified control-oriented model is developed to enable the applicability of adaptive backstepping method. It simplifies the design process and releases some limitations caused by direct use of the no simplified control-oriented model. Next, under proper assumptions, asymptotic stability is proved for constant commands, while bounded stability is proved for varying commands. The proposed method is compared with approximate backstepping control and dynamic surface control and is shown to have superior tracking accuracy as well as robustness from the simulation results. This paper may also provide a beneficial guidance for control design of other complex systems. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Model reference adaptive control (MRAC)-based parameter identification applied to surface-mounted permanent magnet synchronous motor

    Science.gov (United States)

    Zhong, Chongquan; Lin, Yaoyao

    2017-11-01

    In this work, a model reference adaptive control-based estimated algorithm is proposed for online multi-parameter identification of surface-mounted permanent magnet synchronous machines. By taking the dq-axis equations of a practical motor as the reference model and the dq-axis estimation equations as the adjustable model, a standard model-reference-adaptive-system-based estimator was established. Additionally, the Popov hyperstability principle was used in the design of the adaptive law to guarantee accurate convergence. In order to reduce the oscillation of identification result, this work introduces a first-order low-pass digital filter to improve precision regarding the parameter estimation. The proposed scheme was then applied to an SPM synchronous motor control system without any additional circuits and implemented using a DSP TMS320LF2812. For analysis, the experimental results reveal the effectiveness of the proposed method.

  13. Rail Vehicle Vibrations Control Using Parameters Adaptive PID Controller

    Directory of Open Access Journals (Sweden)

    Muzaffer Metin

    2014-01-01

    Full Text Available In this study, vertical rail vehicle vibrations are controlled by the use of conventional PID and parameters which are adaptive to PID controllers. A parameters adaptive PID controller is designed to improve the passenger comfort by intuitional usage of this method that renews the parameters online and sensitively under variable track inputs. Sinusoidal vertical rail misalignment and measured real rail irregularity are considered as two different disruptive effects of the system. Active vibration control is applied to the system through the secondary suspension. The active suspension application of rail vehicle is examined by using 5-DOF quarter-rail vehicle model by using Manchester benchmark dynamic parameters. The new parameters of adaptive controller are optimized by means of genetic algorithm toolbox of MATLAB. Simulations are performed at maximum urban transportation speed (90 km/h of the rail vehicle with ±5% load changes of rail vehicle body to test the robustness of controllers. As a result, superior performance of parameters of adaptive controller is determined in time and frequency domain.

  14. Adaptive control using a hybrid-neural model: application to a polymerisation reactor

    Directory of Open Access Journals (Sweden)

    Cubillos F.

    2001-01-01

    Full Text Available This work presents the use of a hybrid-neural model for predictive control of a plug flow polymerisation reactor. The hybrid-neural model (HNM is based on fundamental conservation laws associated with a neural network (NN used to model the uncertain parameters. By simulations, the performance of this approach was studied for a peroxide-initiated styrene tubular reactor. The HNM was synthesised for a CSTR reactor with a radial basis function neural net (RBFN used to estimate the reaction rates recursively. The adaptive HNM was incorporated in two model predictive control strategies, a direct synthesis scheme and an optimum steady state scheme. Tests for servo and regulator control showed excellent behaviour following different setpoint variations, and rejecting perturbations. The good generalisation and training capacities of hybrid models, associated with the simplicity and robustness characteristics of the MPC formulations, make an attractive combination for the control of a polymerisation reactor.

  15. A model-referenced procedure to support adversarial decision processes; Application to electricity planning

    Energy Technology Data Exchange (ETDEWEB)

    Bunn, D.W.; Vlahos, K. (London Business School (United Kingdom))

    1992-10-01

    In public enquiries concerning major facilities, such as the construction of a new electric power plant, it is observed that a useable decision model should be made commonly available alongside the open provision of data and assumptions. The protagonist, eg the electric utility, generally makes use of a complex, proprietary model for detailed evaluation of options. A simple emulator of this, based upon a regression analysis of numerous scenarios, and validated by further simulations is shown to be feasible and potentially attractive. It would be in the interests of the utility to make such a model-referenced decision support method generally available. The approach is considered in relation to the recent Hinkley Point C public enquiry for a new nuclear power plant in the UK. (Author).

  16. Referencing web pages and e-journals.

    Science.gov (United States)

    Bryson, David

    2013-12-01

    One of the areas that can confuse students and authors alike is how to reference web pages and electronic journals (e-journals). The aim of this professional development article is to go back to first principles for referencing and see how with examples these should be referenced.

  17. Adaptive Robot Control – An Experimental Comparison

    Directory of Open Access Journals (Sweden)

    Francesco Alonge

    2012-11-01

    Full Text Available This paper deals with experimental comparison between stable adaptive controllers of robotic manipulators based on Model Based Adaptive, Neural Network and Wavelet -Based control. The above control methods were compared with each other in terms of computational efficiency, need for accurate mathematical model of the manipulator and tracking performances. An original management algorithm of the Wavelet Network control scheme has been designed, with the aim of constructing the net automatically during the trajectory tracking, without the need to tune it to the trajectory itself. Experimental tests, carried out on a planar two link manipulator, show that the Wavelet-Based control scheme, with the new management algorithm, outperforms the conventional Model-Based schemes in the presence of structural uncertainties in the mathematical model of the robot, without pre-training and more efficiently than the Neural Network approach.

  18. Enhanced vaccine control of epidemics in adaptive networks

    Science.gov (United States)

    Shaw, Leah B.; Schwartz, Ira B.

    2010-04-01

    We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

  19. Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

    Science.gov (United States)

    Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

    2009-01-01

    This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

  20. Effect of vergence adaptation on convergence-accommodation: model simulations.

    Science.gov (United States)

    Sreenivasan, Vidhyapriya; Bobier, William R; Irving, Elizabeth L; Lakshminarayanan, Vasudevan

    2009-10-01

    Several theoretical control models depict the adaptation effects observed in the accommodation and vergence mechanisms of the human visual system. Two current quantitative models differ in their approach of defining adaptation and in identifying the effect of controller adaptation on their respective cross-links between the vergence and accommodative systems. Here, we compare the simulation results of these adaptation models with empirical data obtained from emmetropic adults when they performed sustained near task through + 2D lens addition. The results of our experimental study showed an initial increase in exophoria (a divergent open-loop vergence position) and convergence-accommodation (CA) when viewing through +2D lenses. Prolonged fixation through the near addition lenses initiated vergence adaptation, which reduced the lens-induced exophoria and resulted in a concurrent reduction of CA. Both models showed good agreement with empirical measures of vergence adaptation. However, only one model predicted the experimental time course of reduction in CA. The pattern of our empirical results seem to be best described by the adaptation model that indicates the total vergence response to be a sum of two controllers, phasic and tonic, with the output of phasic controller providing input to the cross-link interactions.

  1. Fuzzy Adaptation Algorithms’ Control for Robot Manipulators with Uncertainty Modelling Errors

    Directory of Open Access Journals (Sweden)

    Yongqing Fan

    2018-01-01

    Full Text Available A novel fuzzy control scheme with adaptation algorithms is developed for robot manipulators’ system. At the beginning, one adjustable parameter is introduced in the fuzzy logic system, the robot manipulators system with uncertain nonlinear terms as the master device and a reference model dynamic system as the slave robot system. To overcome the limitations such as online learning computation burden and logic structure in conventional fuzzy logic systems, a parameter should be used in fuzzy logic system, which composes fuzzy logic system with updated parameter laws, and can be formed for a new fashioned adaptation algorithms controller. The error closed-loop dynamical system can be stabilized based on Lyapunov analysis, the number of online learning computation burdens can be reduced greatly, and the different kinds of fuzzy logic systems with fuzzy rules or without any fuzzy rules are also suited. Finally, effectiveness of the proposed approach has been shown in simulation example.

  2. Full Gradient Solution to Adaptive Hybrid Control

    Science.gov (United States)

    Bean, Jacob; Schiller, Noah H.; Fuller, Chris

    2017-01-01

    This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

  3. Model-Based Evolution of a Fast Hybrid Fuzzy Adaptive Controller for a Pneumatic Muscle Actuator

    Directory of Open Access Journals (Sweden)

    Alexander Hošovský

    2012-07-01

    Full Text Available Pneumatic artificial muscle-based robotic systems usually necessitate the use of various nonlinear control techniques in order to improve their performance. Their robustness to parameter variation, which is generally difficult to predict, should also be tested. Here a fast hybrid adaptive control is proposed, where a conventional PD controller is placed into the feedforward branch and a fuzzy controller is placed into the adaptation branch. The fuzzy controller compensates for the actions of the PD controller under conditions of inertia moment variation. The fuzzy controller of Takagi-Sugeno type is evolved through a genetic algorithm using the dynamic model of a pneumatic muscle actuator. The results confirm the capability of the designed system to provide robust performance under the conditions of varying inertia.

  4. The Cost of Being Accountable: An Objective-Referenced Program Cost Model for Educational Management--A Maryland Perspective.

    Science.gov (United States)

    Holowenzak, Stephen P.; Stagmer, Robert A.

    This publication describes in detail an objective-referenced program cost model for educational management that was developed by the Maryland State Department of Education. Primary purpose of the publication is to aid educational decision-makers in developing and refining their own method of cost-pricing educational programs for use in state and…

  5. Adaptive Backstepping Flight Control for Modern Fighter Aircraft

    NARCIS (Netherlands)

    Sonneveldt, L.

    2010-01-01

    The main goal of this thesis is to investigate the potential of the nonlinear adaptive backstepping control technique in combination with online model identification for the design of a reconfigurable flight control system for a modern fighter aircraft. Adaptive backstepping is a recursive,

  6. All-Coefficient Adaptive Control of Dual-Motor Driving Servo System

    Directory of Open Access Journals (Sweden)

    Zhao Haibo

    2017-01-01

    Full Text Available Backlash nonlinearity and friction nonlinearity exist in dual-motor driving servo system, which reducing system response speed, steady accuracy and anti-interference ability. In order to diminish the adverse effects of backlash and friction nonlinearity to system, we proposed a new all-coefficient adaptive control method. Firstly, we introduced the dynamic model of backlash and friction nonlinearity respectively. Then on this basis, we established the characteristic model when backlash and friction nonlinearity coexist. We used recursive least square method for parameter estimation. Finally we designed the all-coefficient adaptive controller. On the basis of simplex all-coefficient adaptive controller, we designed a feedforward all-coefficient adaptive controller. The simulations of feedforward all-coefficient adaptive control and simplex all-coefficient adaptive control were compared. The results show that the former has quicker response speed, higher steady accuracy, stronger anti-interference performance and better robustness, which validating the efficacy of the proposed control strategy.

  7. Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

    Science.gov (United States)

    Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

    2014-07-01

    Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This

  8. Adaptive Nonsingular Terminal Sliding Model Control and Its Application to Permanent Magnet Synchronous Motor Drive System

    Directory of Open Access Journals (Sweden)

    Liu Yue

    2016-01-01

    Full Text Available To improve the dynamic performance of permanent magnet synchronous motor(PMSM drive system, a adaptive nonsingular terminal sliding model control((NTSMC strategy was proposed. The proposed control strategy presents an adaptive variable-rated exponential reaching law which the L1 norm of state variables is introduced. Exponential and constant approach speed can adaptively adjust according to the state variables’ distance to the equilibrium position.The proposed scheme can shorten the reaching time and weaken system chatting. The method was applied to the PMSM speed servo system, and compared with the traditional terminal-sliding-mode regulator and PI regulator. Simulation results show that the proposed control strategy can improve dynamic, steady performance and robustness.

  9. System identification and adaptive control theory and applications of the neurofuzzy and fuzzy cognitive network models

    CERN Document Server

    Boutalis, Yiannis; Kottas, Theodore; Christodoulou, Manolis A

    2014-01-01

    Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented.  Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model  stems  from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering s...

  10. An overview of adaptive model theory: solving the problems of redundancy, resources, and nonlinear interactions in human movement control.

    Science.gov (United States)

    Neilson, Peter D; Neilson, Megan D

    2005-09-01

    Adaptive model theory (AMT) is a computational theory that addresses the difficult control problem posed by the musculoskeletal system in interaction with the environment. It proposes that the nervous system creates motor maps and task-dependent synergies to solve the problems of redundancy and limited central resources. These lead to the adaptive formation of task-dependent feedback/feedforward controllers able to generate stable, noninteractive control and render nonlinear interactions unobservable in sensory-motor relationships. AMT offers a unified account of how the nervous system might achieve these solutions by forming internal models. This is presented as the design of a simulator consisting of neural adaptive filters based on cerebellar circuitry. It incorporates a new network module that adaptively models (in real time) nonlinear relationships between inputs with changing and uncertain spectral and amplitude probability density functions as is the case for sensory and motor signals.

  11. Tracking Control of Hysteretic Piezoelectric Actuator using Adaptive Rate-Dependent Controller.

    Science.gov (United States)

    Tan, U-Xuan; Latt, Win Tun; Widjaja, Ferdinan; Shee, Cheng Yap; Riviere, Cameron N; Ang, Wei Tech

    2009-03-16

    With the increasing popularity of actuators involving smart materials like piezoelectric, control of such materials becomes important. The existence of the inherent hysteretic behavior hinders the tracking accuracy of the actuators. To make matters worse, the hysteretic behavior changes with rate. One of the suggested ways is to have a feedforward controller to linearize the relationship between the input and output. Thus, the hysteretic behavior of the actuator must first be modeled by sensing the relationship between the input voltage and output displacement. Unfortunately, the hysteretic behavior is dependent on individual actuator and also environmental conditions like temperature. It is troublesome and costly to model the hysteresis regularly. In addition, the hysteretic behavior of the actuators also changes with age. Most literature model the actuator using a cascade of rate-independent hysteresis operators and a dynamical system. However, the inertial dynamics of the structure is not the only contributing factor. A complete model will be complex. Thus, based on the studies done on the phenomenological hysteretic behavior with rate, this paper proposes an adaptive rate-dependent feedforward controller with Prandtl-Ishlinskii (PI) hysteresis operators for piezoelectric actuators. This adaptive controller is achieved by adapting the coefficients to manipulate the weights of the play operators. Actual experiments are conducted to demonstrate the effectiveness of the adaptive controller. The main contribution of this paper is its ability to perform tracking control of non-periodic motion and is illustrated with the tracking control ability of a couple of different non-periodic waveforms which were created by passing random numbers through a low pass filter with a cutoff frequency of 20Hz.

  12. Strategies for Controlling Item Exposure in Computerized Adaptive Testing with the Generalized Partial Credit Model

    Science.gov (United States)

    Davis, Laurie Laughlin

    2004-01-01

    Choosing a strategy for controlling item exposure has become an integral part of test development for computerized adaptive testing (CAT). This study investigated the performance of six procedures for controlling item exposure in a series of simulated CATs under the generalized partial credit model. In addition to a no-exposure control baseline…

  13. Referencing handbook: OSCOLA

    OpenAIRE

    Williams, Helen

    2016-01-01

    University of Lincoln approved guide to OSCOLA referencing. Providing guidelines on how to reference UK, EU and International primary sources of law and secondary sources. The handbook provides examples and annotated diagrams to help you reference sources in the OSCOLA style.

  14. Referencing handbook: Harvard

    OpenAIRE

    Elkin, Judith; Ortega, Marishona; Williams, Helen

    2016-01-01

    University of Lincoln approved guide to Harvard referencing. Providing guidelines on how to reference 75 sources of information. The second edition includes extended guidance on how to reference, all new examples, additional annotated diagrams and an index to help you locate sources.

  15. Adaptive control of a PWR core power using neural networks

    International Nuclear Information System (INIS)

    Arab-Alibeik, H.; Setayeshi, S.

    2005-01-01

    Reactor power control is important because of safety concerns and the call for regular and appropriate operation of nuclear power plants. It seems that the load-follow operation of these plants will be unavoidable in the future. Discrepancies between the real plant and the model used in controller design for load-follow operation encourage one to use auto-tuning and (or) adaptive techniques. Neural network technology shows great promise for addressing many problems in non-model-based adaptive control methods. Also, there has been a great attention to inverse control especially in the neural and fuzzy control context. Fortunately, online adaptation eliminates some limitations of inverse control and its shortcomings for real world applications. We use a neural adaptive inverse controller to control the power of a PWR reactor. The stability of the system and convergence of the controller parameters are guaranteed during online adaptation phase provided the controller is near the plant's real inverse after offline training period. The performance of the controller is verified using nonlinear simulations in diverse operating conditions

  16. Adaptive Sliding Mode Control for Hydraulic Drives

    DEFF Research Database (Denmark)

    Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.

    2013-01-01

    This paper presents a new adaptive sliding mode controller generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD’s). The proposed control scheme requires limited knowledge on system parameters, and employs only piston- and valve spool position feedback...... employing parameter adaption through a recursive algorithm is presented. This is based on a reduced order model approximation of a VCD with unmatched valve flow- and cylinder asymmetries. Bounds on parameters are obtained despite lack of parameter knowledge, and the proposed controller demonstrates improved...

  17. Nutrient-dependent/pheromone-controlled adaptive evolution: a model

    Directory of Open Access Journals (Sweden)

    James Vaughn Kohl

    2013-06-01

    Full Text Available Background: The prenatal migration of gonadotropin-releasing hormone (GnRH neurosecretory neurons allows nutrients and human pheromones to alter GnRH pulsatility, which modulates the concurrent maturation of the neuroendocrine, reproductive, and central nervous systems, thus influencing the development of ingestive behavior, reproductive sexual behavior, and other behaviors. Methods: This model details how chemical ecology drives adaptive evolution via: (1 ecological niche construction, (2 social niche construction, (3 neurogenic niche construction, and (4 socio-cognitive niche construction. This model exemplifies the epigenetic effects of olfactory/pheromonal conditioning, which alters genetically predisposed, nutrient-dependent, hormone-driven mammalian behavior and choices for pheromones that control reproduction via their effects on luteinizing hormone (LH and systems biology. Results: Nutrients are metabolized to pheromones that condition behavior in the same way that food odors condition behavior associated with food preferences. The epigenetic effects of olfactory/pheromonal input calibrate and standardize molecular mechanisms for genetically predisposed receptor-mediated changes in intracellular signaling and stochastic gene expression in GnRH neurosecretory neurons of brain tissue. For example, glucose and pheromones alter the hypothalamic secretion of GnRH and LH. A form of GnRH associated with sexual orientation in yeasts links control of the feedback loops and developmental processes required for nutrient acquisition, movement, reproduction, and the diversification of species from microbes to man. Conclusion: An environmental drive evolved from that of nutrient ingestion in unicellular organisms to that of pheromone-controlled socialization in insects. In mammals, food odors and pheromones cause changes in hormones such as LH, which has developmental affects on pheromone-controlled sexual behavior in nutrient-dependent reproductively

  18. Empowering Student Learning Through Rubric-Referenced Self-Assessment*

    Science.gov (United States)

    He, Xiaohua; Canty, Anne

    2012-01-01

    Purpose: The purpose of this study was to investigate the effect of rubric-referenced self-assessment on performance of anatomy assignments in a group of chiropractic students. Methods: Participants (N = 259) were first-quarter students who were divided into a treatment group (n = 130) and a comparison group (n = 129). The intervention for both groups involved the use of rubrics to complete the first draft of assignments. General feedback was given by the instructor, and then the students had the opportunity to amend the assignments before resubmission (second draft). The treatment group, however, was also asked to perform rubric-referenced self-assessment of their assignments during their second draft. Although the comparison group was also provided with the identical rubrics for the assignments, the students in this group did not perform rubric-referenced self-assessment. Results: The results revealed that the students in the treatment group who used a rubric-referenced self-assessment learning tool received statistically significant higher scores than the comparison group, who did not use this rubric-referenced self-assessment tool. Conclusion: This study suggests that practicing rubric-referenced self-assessment enhances student performance on assignments. However, educators continue to face the challenge of developing practical and useful rubric tools for student self-assessment PMID:22778527

  19. Adaptive MPC based on MIMO ARX-Laguerre model.

    Science.gov (United States)

    Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

    2017-03-01

    This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Switching Adaptability in Human-Inspired Sidesteps: A Minimal Model.

    Science.gov (United States)

    Fujii, Keisuke; Yoshihara, Yuki; Tanabe, Hiroko; Yamamoto, Yuji

    2017-01-01

    Humans can adapt to abruptly changing situations by coordinating redundant components, even in bipedality. Conventional adaptability has been reproduced by various computational approaches, such as optimal control, neural oscillator, and reinforcement learning; however, the adaptability in bipedal locomotion necessary for biological and social activities, such as unpredicted direction change in chase-and-escape, is unknown due to the dynamically unstable multi-link closed-loop system. Here we propose a switching adaptation model for performing bipedal locomotion by improving autonomous distributed control, where autonomous actuators interact without central control and switch the roles for propulsion, balancing, and leg swing. Our switching mobility model achieved direction change at any time using only three actuators, although it showed higher motor costs than comparable models without direction change. Our method of evaluating such adaptation at any time should be utilized as a prerequisite for understanding universal motor control. The proposed algorithm may simply explain and predict the adaptation mechanism in human bipedality to coordinate the actuator functions within and between limbs.

  1. Qualitative Analysis of Integration Adapter Modeling

    OpenAIRE

    Ritter, Daniel; Holzleitner, Manuel

    2015-01-01

    Integration Adapters are a fundamental part of an integration system, since they provide (business) applications access to its messaging channel. However, their modeling and configuration remain under-represented. In previous work, the integration control and data flow syntax and semantics have been expressed in the Business Process Model and Notation (BPMN) as a semantic model for message-based integration, while adapter and the related quality of service modeling were left for further studi...

  2. Multivariable adaptive control of bio process

    Energy Technology Data Exchange (ETDEWEB)

    Maher, M.; Bahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Maher, M. [Faculte des Sciences, Rabat (Morocco). Lab. de Physique

    1995-12-31

    This paper presents a multivariable adaptive control of a continuous-flow fermentation process for the alcohol production. The linear quadratic control strategy is used for the regulation of substrate and ethanol concentrations in the bioreactor. The control inputs are the dilution rate and the influent substrate concentration. A robust identification algorithm is used for the on-line estimation of linear MIMO model`s parameters. Experimental results of a pilot-plant fermenter application are reported and show the control performances. (authors) 8 refs.

  3. Discrete Second-Order Sliding Mode Adaptive Controller Based on Characteristic Model for Servo Systems

    Directory of Open Access Journals (Sweden)

    Zhihong Wang

    2015-01-01

    Full Text Available Considering the varying inertia and load torque in high speed and high accuracy servo systems, a novel discrete second-order sliding mode adaptive controller (DSSMAC based on characteristic model is proposed, and a command observer is also designed. Firstly, the discrete characteristic model of servo systems is established. Secondly, the recursive least square algorithm is adopted to identify time-varying parameters in characteristic model, and the observer is applied to predict the command value of next sample time. Furthermore, the stability of the closed-loop system and the convergence of the observer are analyzed. The experimental results show that the proposed method not only can adapt to varying inertia and load torque, but also has good disturbance rejection ability and robustness to uncertainties.

  4. A Modified Model Reference Adaptive Control for a Single Motor of Latch Type Control Element Drive Mechanism

    International Nuclear Information System (INIS)

    Park, Bae Jeong

    2016-01-01

    A modified Model Reference Adaptive Control (MRAC) for a single motor of latch type Control Element Drive Mechanism (CEDM) is described herein. The CEDM has complicated dynamic characteristics including electrical, mechanical, and magnetic effects. The previous control system has utilized a Proportional-Integral (PI) controller, and the control performance is limited according to nonlinear dynamic characteristics and environmental conditions. The modified MRAC using system identification (ID) technique improves the control performance in the operating condition such as model parameter variation and environmental condition change. The modified MRAC using the identified reference model with feed-forward gain and 180Hz noise reduction filter presents better performance under normal and/or abnormal condition. The simplified reference model can make H/W implementation more practical on the viewpoint of less computation and good performance. Actually, the CEDM controller shall be capable of controlling 101 control element assemblies (CEAs) individually in the nuclear power plant. Because the load conditions and the environmental condition around the 101 CEAs are all different minutely, the proposed modified MRAC can be a good practice. The modified MRAC controller will be applied in the real nuclear power plant later and this will overcome some weak point of PI controller

  5. Bayesian nonparametric adaptive control using Gaussian processes.

    Science.gov (United States)

    Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A

    2015-03-01

    Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.

  6. Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

    Science.gov (United States)

    Frost, Susan A.; Balas, Mark J.

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

  7. Determination Of Adaptive Control Parameter Using Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    Omur Can Ozguney

    2017-08-01

    Full Text Available The robot industry has developed along with the increasing the use of robots in industry. This has led to increase the studies on robots. The most important part of these studies is that the robots must be work with minimum tracking trajectory error. But it is not easy for robots to track the desired trajectory because of the external disturbances and parametric uncertainty. Therefore adaptive and robust controllers are used to decrease tracking error. The aim of this study is to increase the tracking performance of the robot and minimize the trajectory tracking error. For this purpose adaptive control law for robot manipulator is identified and fuzzy logic controller is applied to find the accurate values for adaptive control parameter. Based on the Lyapunov theory stability of the uncertain system is guaranteed. In this study robot parameters are assumed to be unknown. This controller is applied to a robot model and the results of simulations are given. Controller with fuzzy logic and without fuzzy logic are compared with each other. Simulation results show that the fuzzy logic controller has improved the results.

  8. Neural network based adaptive control for nonlinear dynamic regimes

    Science.gov (United States)

    Shin, Yoonghyun

    Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.

  9. Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

    Science.gov (United States)

    Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

    2017-10-01

    The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

  10. Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?

    Science.gov (United States)

    Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.

    2015-01-01

    Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.

  11. Neuro-adaptive control in beating heart surgery based on the viscoelastic tissue model

    Directory of Open Access Journals (Sweden)

    Setareh Rezakhani

    2014-04-01

    Full Text Available In this paper, the problem of 3D heart motion in beating heart surgery is resolved by proposing a parallel force-motion controller. Motion controller is designed based on neuro-adaptive approach to compensate 3D heart motion and deal with uncertainity in dynamic parameters, while an implicit force control is implemented by considering a viscoelastic tissue model. Stability analysis is proved through Lypanov’s stability theory and Barballet’s lemma. Simulation results, for D2M2 robot, which is done in nominal case and viscoelastic parameter mismatches demonstrate the robust performance of the controller.

  12. Adaptive Controller Effects on Pilot Behavior

    Science.gov (United States)

    Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

    2014-01-01

    Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

  13. Adaptive Control of a Utility-Scale Wind Turbine Operating in Region 3

    Science.gov (United States)

    Frost, Susan A.; Balas, Mark J.; Wright, Alan D.

    2009-01-01

    Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. The turbulent and unpredictable conditions in which wind turbines operate create many challenges for their operation. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility scale, variable-speed horizontal axis wind turbine. The objective of the adaptive pitch controller in Region 3 is to regulate generator speed and reject step disturbances. The control objective is accomplished by collectively pitching the turbine blades. We use an extension of the Direct Model Reference Adaptive Control (DMRAC) approach to track a reference point and to reject persistent disturbances. The turbine simulation models the Controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine which has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a bas celliansesical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the baseline PI pitch controller and it demonstrated robustness to modeling errors.

  14. Adaptive fuzzy PID control for a quadrotor stabilisation

    Science.gov (United States)

    Cherrat, N.; Boubertakh, H.; Arioui, H.

    2018-02-01

    This paper deals with the design of an adaptive fuzzy PID control law for attitude and altitude stabilization of a quadrotor despite the system model uncertainties and disturbances. To this end, a PID control with adaptive gains is used in order to approximate a virtual ideal control previously designed to achieve the predefined objective. Specifically, the control gains are estimated and adjusted by mean of a fuzzy system whose parameters are adjusted online via a gradient descent-based adaptation law. The analysis of the closed-loop system is given by the Lyapunov approach. The simulation results are presented to illustrate the efficiency of the proposed approach.

  15. Self-referencing Mach-Zehnder interferometer as a laser system diagnostic: Active and adaptive optical systems

    International Nuclear Information System (INIS)

    Feldman, M.; Mockler, D.J.; English, R.E. Jr.; Byrd, J.L.; Salmon, J.T.

    1991-01-01

    We are incorporating a novel self-referencing Mach-Zehnder interferometer into a large scale laser system as a real time, interactive diagnostic tool for wavefront measurement. The instrument is capable of absolute wavefront measurements accurate to better than λ/10 pv over a wavelength range > 300 nm without readjustment of the optical components. This performance is achieved through the design of both refractive optics and catadioptric collimator to achromatize the Mach-Zehnder reference arm. Other features include polarization insensitivity through the use of low angles of incidence on all beamsplitters as well as an equal path length configuration that allows measurement of either broad-band or closely spaced laser-line sources. Instrument accuracy is periodically monitored in place by means of a thermally and mechanically stable wavefront reference source that is calibrated off-line with a phase conjugate interferometer. Video interferograms are analyzed using Fourier transform techniques on a computer that includes dedicated array processor. Computer and video networks maintain distributed interferometers under the control of a single analysis computer with multiple user access. 7 refs., 11 figs

  16. Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid

    Directory of Open Access Journals (Sweden)

    Xiaogang Guo

    2018-01-01

    Full Text Available In this paper, an adaptively constrained stochastic model predictive control (MPC is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs in a microgrid (MG. Besides the economic objective of MG operation, the limits of state-of-charge (SOC and discharging/charging power of the energy storage unit are formulated as chance constraints when accommodating uncertainties of RESs, considering mild violations of these constraints are allowed during long-term operation, and a closed-loop online update strategy is performed to adaptively tighten or relax constraints according to the actual deviation probability of violation level from the desired one as well as the current change rate of deviation probability. Numerical studies show that the proposed adaptively constrained stochastic MPC for MG optimal operation is much less conservative compared with the scenario optimization based robust MPC, and also presents a better convergence performance to the desired constraint violation level than other online update strategies.

  17. Comparison and extension of a direct model reference adaptive control procedure

    Science.gov (United States)

    Neat, Gregory W.; Kaufman, Howard; Steinvorth, Rodrigo

    1992-01-01

    This paper analyzes and extends an easily implemented direct model reference adaptive control procedure. The paper focuses on the major limitation of this control approach which is the satisfaction of a strictly positive real sufficiency condition in order to guarantee asymptotic tracking. Attempts, to date, to address this problem have been unable to relax simultaneously the stringent condition and maintain asymptotic tracking capabilities. Three different modifications to existing versions of this algorithm are presented which substantially relax the stringent sufficiency condition while providing asymptotic tracking. These three modifications achieve this goal by imposing slight adjustments to existing sufficiency conditions. A simulation example demonstrates that the modifications eliminate the steady error inherent in the existing methods.

  18. Robust Longitudinal Aircraft- Control Based on an Adaptive Fuzzy-Logic Algorithm

    Directory of Open Access Journals (Sweden)

    Abdel- Latif Elshafei

    2002-06-01

    Full Text Available To study the aircraft response to a fast pull-up manoeuvre, a short period approximation of the longitudinal model is considered. The model is highly nonlinear and includes parametric uncertainties. To cope with a wide range of command signals, a robust adaptive fuzzy logic controller is proposed. The proposed controller adopts a dynamic inversion approach. Since feedback linearization is practically imperfect, robustifying and adaptive components are included in the control law to compensate for modeling errors and achieve acceptable tracking errors. Two fuzzy systems are implemented. The first system models the nominal values of the system’s nonlinearity. The second system is an adaptive one that compensates for modeling errors. The derivation of the control law based on a dynamic game approach is given in detail. Stability of the closed-loop control system is also verified. Simulation results based on an F16-model illustrate a successful tracking performance of the proposed controller.

  19. Control of multi-machine using adaptive fuzzy

    Directory of Open Access Journals (Sweden)

    Bouchiba Bousmaha

    2011-01-01

    Full Text Available An indirect Adaptive fuzzy excitation control (IAFLC of power systems based on multi-input-multi-output linearization technique is developed in this paper. The power system considered in this paper consists of two generators and infinite bus connected through a network of transformers and transmission lines. The fuzzy controller is constructed from fuzzy feedback linearization controller whose parameters are adjusted indirectly from the estimates of plant parameters. The adaptation law adjusts the controller parameters on-line so that the plant output tracks the reference model output. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system.

  20. Adaptive control of manipulators handling hazardous waste

    International Nuclear Information System (INIS)

    Colbaugh, R.; Glass, K.

    1994-01-01

    This article focuses on developing a robot control system capable of meeting hazardous waste handling application requirements, and presents as a solution an adaptive strategy for controlling the mechanical impedance of kinematically redundant manipulators. The proposed controller is capable of accurate end-effector impedance control and effective redundancy utilization, does not require knowledge of the complex robot dynamic model or parameter values for the robot or the environment, and is implemented without calculation of the robot inverse transformation. Computer simulation results are given for a four degree of freedom redundant robot under adaptive impedance control. These results indicate that the proposed controller is capable of successfully performing important tasks in robotic waste handling applications. (author) 3 figs., 39 refs

  1. Disturbance Accommodating Adaptive Control with Application to Wind Turbines

    Science.gov (United States)

    Frost, Susan

    2012-01-01

    Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.

  2. Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

    Science.gov (United States)

    Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  3. Robust and Adaptive Control With Aerospace Applications

    CERN Document Server

    Lavretsky, Eugene

    2013-01-01

    Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems.  The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: ·         case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; ·         detailed background material for each chapter to motivate theoretical developments; ·         realistic examples and simulation data illustrating key features ...

  4. Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Gergely Takács

    2014-01-01

    Full Text Available This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

  5. Theoretical model for ultracold molecule formation via adaptive feedback control

    International Nuclear Information System (INIS)

    Poschinger, Ulrich; Salzmann, Wenzel; Wester, Roland; Weidemueller, Matthias; Koch, Christiane P; Kosloff, Ronnie

    2006-01-01

    We theoretically investigate pump-dump photoassociation of ultracold molecules with amplitude- and phase-modulated femtosecond laser pulses. For this purpose, a perturbative model for light-matter interaction is developed and combined with a genetic algorithm for adaptive feedback control of the laser pulse shapes. The model is applied to the formation of 85 Rb 2 molecules in a magneto-optical trap. We find that optimized pulse shapes may maximize the formation of ground state molecules in a specific vibrational state at a pump-dump delay time for which unshaped pulses lead to a minimum of the formation rate. Compared to the maximum formation rate obtained for unshaped pulses at the optimum pump-dump delay, the optimized pulses lead to a significant improvement of about 40% for the target level population. Since our model yields the spectral amplitudes and phases of the optimized pulses, the results are directly applicable in pulse shaping experiments

  6. Controlling smart grid adaptivity

    OpenAIRE

    Toersche, Hermen; Nykamp, Stefan; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria

    2012-01-01

    Methods are discussed for planning oriented smart grid control to cope with scenarios with limited predictability, supporting an increasing penetration of stochastic renewable resources. The performance of these methods is evaluated with simulations using measured wind generation and consumption data. Forecast errors are shown to affect worst case behavior in particular, the severity of which depends on the chosen adaptivity strategy and error model.

  7. Citing & Referencing Using the Harvard Style: Examples

    OpenAIRE

    Cullen, John G.

    2016-01-01

    This teaching resource supplements 2 videos which are available online on YouTube. These videos are titled: • ‘Citing and referencing using the Harvard Style (Part 1)’ - Available at https://www.youtube.com/watch?v=9X1UjtfgTU8 • Citing and referencing using the Harvard Style (Part 2)’ - Available at https://www.youtube.com/watch?v=Hj_EXIFviZA

  8. Non-identifier based adaptive control in mechatronics theory and application

    CERN Document Server

    Hackl, Christoph M

    2017-01-01

    This book introduces non-identifier-based adaptive control (with and without internal model) and its application to the current, speed and position control of mechatronic systems such as electrical synchronous machines, wind turbine systems, industrial servo systems, and rigid-link, revolute-joint robots. In mechatronics, there is often only rough knowledge of the system. Due to parameter uncertainties, nonlinearities and unknown disturbances, model-based control strategies can reach their performance or stability limits without iterative controller design and performance evaluation, or system identification and parameter estimation. The non-identifier-based adaptive control presented is an alternative that neither identifies the system nor estimates its parameters but ensures stability. The adaptive controllers are easy to implement, compensate for disturbances and are inherently robust to parameter uncertainties and nonlinearities. For controller implementation only structural system knowledge (like relativ...

  9. Design of L1 -Adaptive Controller for Single Axis Positioning Table

    Directory of Open Access Journals (Sweden)

    Amjad Jalil Humaidi

    2017-11-01

    Full Text Available L1 adaptive controller has proven to provide fast adaptation with guaranteed transients in a large variety of systems. It is commonly used for controlling systems with uncertain time-varying unknown parameters. The effectiveness of L1 adaptive controller for position control of single axis has been examined and compared with Model Reference Adaptive Controller (MRAC. The Linear servo motor is one of the main constituting elements of the x-y table which is mostly used in automation application. It is characterized by time-varying friction and disturbance

  10. Design of adaptive switching control for hypersonic aircraft

    Directory of Open Access Journals (Sweden)

    Xin Jiao

    2015-10-01

    Full Text Available This article proposes a novel adaptive switching control of hypersonic aircraft based on type-2 Takagi–Sugeno–Kang fuzzy sliding mode control and focuses on the problem of stability and smoothness in the switching process. This method uses full-state feedback to linearize the nonlinear model of hypersonic aircraft. Combining the interval type-2 Takagi–Sugeno–Kang fuzzy approach with sliding mode control keeps the adaptive switching process stable and smooth. For rapid stabilization of the system, the adaptive laws use a direct constructive Lyapunov analysis together with an established type-2 Takagi–Sugeno–Kang fuzzy logic system. Simulation results indicate that the proposed control scheme can maintain the stability and smoothness of switching process for the hypersonic aircraft.

  11. Hybrid adaptive ascent flight control for a flexible launch vehicle

    Science.gov (United States)

    Lefevre, Brian D.

    For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the

  12. Adaptive Backstepping Self-balancing Control of a Two-wheel Electric Scooter

    Directory of Open Access Journals (Sweden)

    Nguyen Ngoc Son

    2014-10-01

    Full Text Available This paper introduces an adaptive backstepping control law for a two-wheel electric scooter (eScooter with a nonlinear uncertain model. Adaptive backstepping control is integrated with feedback control that satisfies Lyapunov stability. By using the recursive structure to find the controlled function and estimate uncertain parameters, an adaptive backstepping method allows us to build a feedback control law that efficiently controls a self-balancing controller of the eScooter. Additionally, a controller area network (CAN bus with high reliability is applied for communicating between the modules of the eScooter. Simulation and experimental results demonstrate the robustness and good performance of the proposed adaptive backstepping control.

  13. Modelling and adaptive control of small capacity chillers for HVAC applications

    International Nuclear Information System (INIS)

    Beghi, A.; Cecchinato, Luca

    2011-01-01

    An adaptive controller for single and uneven tandem scroll compressor, packaged air-cooled water chillers is described. The designed controller allows to substantially increase the energy performance of the system, as well as to achieve excellent regulation performances in process applications. The controller parameters are adapted on the basis of estimates of the plant thermal load, that are computed by using a Kalman filter. An ad hoc approach is used to define a relay control logic, which is based on a numerical optimization procedure. To support controller design, a detailed simulation environment is developed and validated on an experimental facility. Performance of the algorithm is described with both simulation and experimental data. At low part load ratio values the proposed algorithm grants a 0.6-0.7 K improvement in the regulation performance in terms of supply water temperature standard deviation and mean supply water temperature deviation. The unit energy efficiency improvement with respect to supply water temperature control varies from 7.3% to 3.0% while the experimental seasonal energy efficiency rating improvement is 9.1%. - Research highlights: → Design of an advanced control algorithms for small capacity chillers. → Matlab/Simulink simulation environment development and experimental validation. → Development of an adaptive control algorithm for scroll compressor chillers, which allows to increase both control accuracy and energy performance. → New load estimation scheme based on a Kalman filter.

  14. Spatial analysis and mapping of malaria risk in Malawi using point-referenced prevalence of infection data

    Directory of Open Access Journals (Sweden)

    Kazembe Lawrence N

    2006-09-01

    Full Text Available Abstract Background Current malaria control initiatives aim at reducing malaria burden by half by the year 2010. Effective control requires evidence-based utilisation of resources. Characterizing spatial patterns of risk, through maps, is an important tool to guide control programmes. To this end an analysis was carried out to predict and map malaria risk in Malawi using empirical data with the aim of identifying areas where greatest effort should be focussed. Methods Point-referenced prevalence of infection data for children aged 1–10 years were collected from published and grey literature and geo-referenced. The model-based geostatistical methods were applied to analyze and predict malaria risk in areas where data were not observed. Topographical and climatic covariates were added in the model for risk assessment and improved prediction. A Bayesian approach was used for model fitting and prediction. Results Bivariate models showed a significant association of malaria risk with elevation, annual maximum temperature, rainfall and potential evapotranspiration (PET. However in the prediction model, the spatial distribution of malaria risk was associated with elevation, and marginally with maximum temperature and PET. The resulting map broadly agreed with expert opinion about the variation of risk in the country, and further showed marked variation even at local level. High risk areas were in the low-lying lake shore regions, while low risk was along the highlands in the country. Conclusion The map provided an initial description of the geographic variation of malaria risk in Malawi, and might help in the choice and design of interventions, which is crucial for reducing the burden of malaria in Malawi.

  15. Reservoir-based Online Adaptive Forward Models with Neural Control for Complex Locomotion in a Hexapod Robot

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Dasgupta, Sakyasingha; Goldschmidt, Dennis

    2014-01-01

    Walking animals show fascinating locomotor abilities and complex behaviors. Biological study has revealed that such complex behaviors is a result of a combination of biomechanics and neural mechanisms. While biomechanics allows for flexibility and a variety of movements, neural mechanisms generate...... locomotion, make predictions, and provide adaptation. Inspired by this finding, we present here an artificial bio-inspired walking system which combines biomechanics (in terms of its body and leg structures) and neural mechanisms. The neural mechanisms consist of 1) central pattern generator-based control...... for generating basic rhythmic patterns and coordinated movements, 2) reservoir-based adaptive forward models with efference copies for sensory prediction as well as state estimation, and 3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental...

  16. An application of indirect model reference adaptive control to a low-power proton exchange membrane fuel cell

    Science.gov (United States)

    Yang, Yee-Pien; Liu, Zhao-Wei; Wang, Fu-Cheng

    2008-05-01

    Nonlinearity and the time-varying dynamics of fuel cell systems make it complex to design a controller for improving output performance. This paper introduces an application of a model reference adaptive control to a low-power proton exchange membrane (PEM) fuel cell system, which consists of three main components: a fuel cell stack, an air pump to supply air, and a solenoid valve to adjust hydrogen flow. From the system perspective, the dynamic model of the PEM fuel cell stack can be expressed as a multivariable configuration of two inputs, hydrogen and air-flow rates, and two outputs, cell voltage and current. The corresponding transfer functions can be identified off-line to describe the linearized dynamics with a finite order at a certain operating point, and are written in a discrete-time auto-regressive moving-average model for on-line estimation of parameters. This provides a strategy of regulating the voltage and current of the fuel cell by adaptively adjusting the flow rates of air and hydrogen. Experiments show that the proposed adaptive controller is robust to the variation of fuel cell system dynamics and power request. Additionally, it helps decrease fuel consumption and relieves the DC/DC converter in regulating the fluctuating cell voltage.

  17. Adaptive Piezoelectric Absorber for Active Vibration Control

    Directory of Open Access Journals (Sweden)

    Sven Herold

    2016-02-01

    Full Text Available Passive vibration control solutions are often limited to working reliably at one design point. Especially applied to lightweight structures, which tend to have unwanted vibration, active vibration control approaches can outperform passive solutions. To generate dynamic forces in a narrow frequency band, passive single-degree-of-freedom oscillators are frequently used as vibration absorbers and neutralizers. In order to respond to changes in system properties and/or the frequency of excitation forces, in this work, adaptive vibration compensation by a tunable piezoelectric vibration absorber is investigated. A special design containing piezoelectric stack actuators is used to cover a large tuning range for the natural frequency of the adaptive vibration absorber, while also the utilization as an active dynamic inertial mass actuator for active control concepts is possible, which can help to implement a broadband vibration control system. An analytical model is set up to derive general design rules for the system. An absorber prototype is set up and validated experimentally for both use cases of an adaptive vibration absorber and inertial mass actuator. Finally, the adaptive vibration control system is installed and tested with a basic truss structure in the laboratory, using both the possibility to adjust the properties of the absorber and active control.

  18. Map Coordinate Referencing and the use of GPS Datasets in Ghana ...

    African Journals Online (AJOL)

    Map Coordinate Referencing and the use of GPS Datasets in Ghana. ... Journal of Science and Technology (Ghana) ... systems used in Ghana (the Ghana war office system and also the Clarke1880 system) using the Bursa-Wolf model.

  19. A Reactive Power Based Reference Model for Adaptive Control Strategy in a SEIG

    Directory of Open Access Journals (Sweden)

    M. A. Taghikhani

    2018-02-01

    Full Text Available In this paper, a new control strategy is proposed for a three-phase squirrel-cage self-excited induction generator (SEIG connected to a variable speed wind turbine in autonomous mode. In order to improve the dynamic performance of the mentioned vector control system, a model reference adaptive controller is used for online rotor time constant estimation. Thus, the main drawbacks of this method, which include the effects of the changes in machine parameters on rotor flux estimation, slip speed, the creation of instability problems and the system leaving vector control mode, are resolved. In this control strategy, a PI controller is used to control the dc voltage and three similar hysteresis current controllers (HCC are used to control the switching of IGBTs. The results of the dynamic simulation indicate the desirable performance of the proposed system.

  20. A two-stage planning and control model toward Economically Adapted Power Distribution Systems using analytical hierarchy processes and fuzzy optimization

    Energy Technology Data Exchange (ETDEWEB)

    Schweickardt, Gustavo [Instituto de Economia Energetica, Fundacion Bariloche, Centro Atomico Bariloche - Pabellon 7, Av. Bustillo km 9500, 8400 Bariloche (Argentina); Miranda, Vladimiro [INESC Porto, Instituto de Engenharia de Sistemas e Computadores do Porto and FEUP, Faculdade de Engenharia da Universidade do Porto, R. Dr. Roberto Frias, 378, 4200-465 Porto (Portugal)

    2009-07-15

    This work presents a model to evaluate the Distribution System Dynamic De-adaptation respecting its planning for a given period of Tariff Control. The starting point for modeling is brought about by the results from a multi-criteria method based on Fuzzy Dynamic Programming and on Analytic Hierarchy Processes applied in a mid/short-term horizon (stage 1). Then, the decision-making activities using the Hierarchy Analytical Processes will allow defining, for a Control of System De-adaptation (stage 2), a Vector to evaluate the System Dynamic Adaptation. It is directly associated to an eventual series of inbalances that take place during its evolution. (author)

  1. Projection Operator: A Step Towards Certification of Adaptive Controllers

    Science.gov (United States)

    Larchev, Gregory V.; Campbell, Stefan F.; Kaneshige, John T.

    2010-01-01

    One of the major barriers to wider use of adaptive controllers in commercial aviation is the lack of appropriate certification procedures. In order to be certified by the Federal Aviation Administration (FAA), an aircraft controller is expected to meet a set of guidelines on functionality and reliability while not negatively impacting other systems or safety of aircraft operations. Due to their inherent time-variant and non-linear behavior, adaptive controllers cannot be certified via the metrics used for linear conventional controllers, such as gain and phase margin. Projection Operator is a robustness augmentation technique that bounds the output of a non-linear adaptive controller while conforming to the Lyapunov stability rules. It can also be used to limit the control authority of the adaptive component so that the said control authority can be arbitrarily close to that of a linear controller. In this paper we will present the results of applying the Projection Operator to a Model-Reference Adaptive Controller (MRAC), varying the amount of control authority, and comparing controller s performance and stability characteristics with those of a linear controller. We will also show how adjusting Projection Operator parameters can make it easier for the controller to satisfy the certification guidelines by enabling a tradeoff between controller s performance and robustness.

  2. An adaptive predictive controller and its applications in power stations

    Energy Technology Data Exchange (ETDEWEB)

    Yang Zhiyuan; Lu Huiming; Zhang Xinggao [North China Electric Power University, Beijing (China); Song Chunping [Tsinghua University, Beijing (China). Dept. of Thermal Energy Engineering

    1999-07-01

    Based on the objective function in the form of integration of generalized model error, a globally convergent model reference adaptive predictive control algorithm (MRAPC) containing inertia-time compensators is presented in this paper. MRAPC has been successfully applied to control important thermal process of more than 20 units in many Chinese power stations. In this paper three representative examples are described. Continual operation results for years demonstrate that MRAPC is a successful attempt for the practical applications of adaptive control techniques. (author)

  3. An Adaptive Speed Control Approach for DC Shunt Motors

    Directory of Open Access Journals (Sweden)

    Ruben Tapia-Olvera

    2016-11-01

    Full Text Available A B-spline neural networks-based adaptive control technique for angular speed reference trajectory tracking tasks with highly efficient performance for direct current shunt motors is proposed. A methodology for adaptive control and its proper training procedure are introduced. This algorithm sets the control signal without using a detailed mathematical model nor exact values of the parameters of the nonlinear dynamic system. The proposed robust adaptive tracking control scheme only requires measurements of the velocity output signal. Thus, real-time measurements or estimations of acceleration, current and disturbance signals are avoided. Experimental results confirm the efficient and robust performance of the proposed control approach for highly demanding motor operation conditions exposed to variable-speed reference trajectories and completely unknown load torque. Hence, laboratory experimental tests on a direct current shunt motor prove the viability of the proposed adaptive output feedback trajectory tracking control approach.

  4. Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

    Science.gov (United States)

    Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

    2013-09-01

    This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

  5. Social referencing and cat-human communication.

    Science.gov (United States)

    Merola, I; Lazzaroni, M; Marshall-Pescini, S; Prato-Previde, E

    2015-05-01

    Cats' (Felis catus) communicative behaviour towards humans was explored using a social referencing paradigm in the presence of a potentially frightening object. One group of cats observed their owner delivering a positive emotional message, whereas another group received a negative emotional message. The aim was to evaluate whether cats use the emotional information provided by their owners about a novel/unfamiliar object to guide their own behaviour towards it. We assessed the presence of social referencing, in terms of referential looking towards the owner (defined as looking to the owner immediately before or after looking at the object), the behavioural regulation based on the owner's emotional (positive vs negative) message (vocal and facial), and the observational conditioning following the owner's actions towards the object. Most cats (79 %) exhibited referential looking between the owner and the object, and also to some extent changed their behaviour in line with the emotional message given by the owner. Results are discussed in relation to social referencing in other species (dogs in particular) and cats' social organization and domestication history.

  6. Design and implementation of adaptive inverse control algorithm for a micro-hand control system

    Directory of Open Access Journals (Sweden)

    Wan-Cheng Wang

    2014-01-01

    Full Text Available The Letter proposes an online tuned adaptive inverse position control algorithm for a micro-hand. First, the configuration of the micro-hand is discussed. Next, a kinematic analysis of the micro-hand is investigated and then the relationship between the rotor position of micro-permanent magnet synchronous motor and the tip of the micro-finger is derived. After that, an online tuned adaptive inverse control algorithm, which includes an adaptive inverse model and an adaptive inverse control, is designed. The online tuned adaptive inverse control algorithm has better performance than the proportional–integral control algorithm does. In addition, to avoid damaging the object during the grasping process, an online force control algorithm is proposed here as well. An embedded micro-computer, cRIO-9024, is used to realise the whole position control algorithm and the force control algorithm by using software. As a result, the hardware circuit is very simple. Experimental results show that the proposed system can provide fast transient responses, good load disturbance responses, good tracking responses and satisfactory grasping responses.

  7. Development of adaptive control applied to chaotic systems

    Science.gov (United States)

    Rhode, Martin Andreas

    1997-12-01

    Continuous-time derivative control and adaptive map-based recursive feedback control techniques are used to control chaos in a variety of systems and in situations that are of practical interest. The theoretical part of the research includes the review of fundamental concept of control theory in the context of its applications to deterministic chaotic systems, the development of a new adaptive algorithm to identify the linear system properties necessary for control, and the extension of the recursive proportional feedback control technique, RPF, to high dimensional systems. Chaos control was applied to models of a thermal pulsed combustor, electro-chemical dissolution and the hyperchaotic Rossler system. Important implications for combustion engineering were suggested by successful control of the model of the thermal pulsed combustor. The system was automatically tracked while maintaining control into regions of parameter and state space where no stable attractors exist. In a simulation of the electrochemical dissolution system, application of derivative control to stabilize a steady state, and adaptive RPF to stabilize a period one orbit, was demonstrated. The high dimensional adaptive control algorithm was applied in a simulation using the Rossler hyperchaotic system, where a period-two orbit with two unstable directions was stabilized and tracked over a wide range of a system parameter. In the experimental part, the electrochemical system was studied in parameter space, by scanning the applied potential and the frequency of the rotating copper disk. The automated control algorithm is demonstrated to be effective when applied to stabilize a period-one orbit in the experiment. We show the necessity of small random perturbations applied to the system in order to both learn the dynamics and control the system at the same time. The simultaneous learning and control capability is shown to be an important part of the active feedback control.

  8. Postgraduate nursing student knowledge, attitudes, skills, and confidence in appropriately referencing academic work.

    Science.gov (United States)

    Greenwood, Melanie; Walkem, Kerrie; Smith, Lindsay Mervyn; Shearer, Toniele; Stirling, Christine

    2014-08-01

    Preventing plagiarism is an ongoing issue for higher education institutions. Although plagiarism has been traditionally seen as cheating, it is increasingly thought to be the result of poor referencing, with students reporting difficulties citing and referencing bibliographic sources. This study examined the academic knowledge, attitude, skills, and confidence of students in a school of nursing to understand poor referencing. A cross-sectional quantitative and qualitative survey was distributed to postgraduate (N = 1,000) certificate, diploma, and master's students. Quantitative data gathered demographics, cultural and linguistic background, and use of technology. Thematic analysis discovered patterns and themes. Results showed participants understood requirements for referencing; half indicated poor referencing was due to difficulty referencing Internet sources or losing track of sources, and many lacked confidence in key referencing tasks. Despite this, 50% did not make use of referencing resources. Overall, these data suggest incorrect referencing is rarely intentional and predominantly caused by skills deficit. Copyright 2014, SLACK Incorporated.

  9. An adaptive control application in a large thermal combined power plant

    International Nuclear Information System (INIS)

    Kocaarslan, Ilhan; Cam, Ertugrul

    2007-01-01

    In this paper, an adaptive controller was applied to a 765 MW large thermal power plant to decrease operating costs, increase quality of generated electricity and satisfy environmental concerns. Since power plants may present several operating problems such as disturbances and severe effects at operating points, design of their controllers needs to be carried out adequately. For these reasons, first, a reduced mathematical model was developed under Computer Aided Analysis and Design Package for Control (CADACS), so that the results of the experimental model have briefly been discussed. Second, conventional PID and adaptive controllers were designed and implemented under the real-time environment of the CADACS software. Additionally, the design of the adaptive model-reference and conventional PID controllers used in the power plant for real-time control were theoretically presented. All processes were realized in real-time. Due to safety restrictions, a direct connection to the sensors and actuators of the plant was not allowed. Instead a coupling to the control system was realized. This offers, in addition, the usage of the supervisory functions of an industrial process computer system. Application of the controllers indicated that the proposed adaptive controller has better performances for rise and settling times of electrical power, and enthalpy outputs than the conventional PID controller does

  10. Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model

    Science.gov (United States)

    Yue, Fengfa; Li, Xingfei; Chen, Cheng; Tan, Wenbin

    2017-12-01

    In order to improve the control accuracy and stability of opto-electronic tracking system fixed on reef or airport under friction and external disturbance conditions, adaptive integral backstepping sliding mode control approach with friction compensation is developed to achieve accurate and stable tracking for fast moving target. The nonlinear observer and slide mode controller based on modified LuGre model with friction compensation can effectively reduce the influence of nonlinear friction and disturbance of this servo system. The stability of the closed-loop system is guaranteed by Lyapunov theory. The steady-state error of the system is eliminated by integral action. The adaptive integral backstepping sliding mode controller and its performance are validated by a nonlinear modified LuGre dynamic model of the opto-electronic tracking system in simulation and practical experiments. The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.

  11. Adaptive Disturbance Rejection Control for Automatic Carrier Landing System

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2016-01-01

    Full Text Available An adaptive disturbance rejection algorithm is proposed for carrier landing system in the final-approach. The carrier-based aircraft dynamics and the linearized longitudinal model under turbulence conditions in the final-approach are analyzed. A stable adaptive control scheme is developed based on LDU decomposition of the high-frequency gain matrix, which ensures closed-loop stability and asymptotic output tracking. Finally, simulation studies of a linearized longitudinal-directional dynamics model are conducted to demonstrate the performance of the adaptive scheme.

  12. Distributed Recurrent Neural Forward Models with Synaptic Adaptation and CPG-based control for Complex Behaviors of Walking Robots

    Directory of Open Access Journals (Sweden)

    Sakyasingha eDasgupta

    2015-09-01

    Full Text Available Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures with the underlying neural mechanisms. The neural mechanisms consist of 1 central pattern generator based control for generating basic rhythmic patterns and coordinated movements, 2 distributed (at each leg recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and 3 searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps as well as climbing over high obstacles. Furthermore we demonstrate that the newly developed recurrent network based approach to sensorimotor prediction outperforms the previous state of the art adaptive neuron

  13. A Model Based Control methodology combining Blade Pitch and Adaptive Trailing Edge Flaps in a common framework

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Bergami, Leonardo; Andersen, Peter Bjørn

    2013-01-01

    This work investigates how adaptive trailing edge flaps and classical blade pitch can work in concert using a model-based state space control formulation. The trade-off between load reduction and actuator activity is decided by setting different weights in the objective function used by the model...

  14. A Model Based Control methodology combining Blade Pitch and Adaptive Trailing Edge Flaps in a common framework

    DEFF Research Database (Denmark)

    This work investigates how adaptive trailing edge flaps and classical blade pitch can work in concert using a model-based state space control formulation. The trade-off between load reduction and actuator activity is decided by setting different weights in the objective function used by the model...

  15. Adaptive State Feedback—Theory and Application for Wind Turbine Control

    Directory of Open Access Journals (Sweden)

    Kaman Thapa Magar

    2017-12-01

    Full Text Available A class of adaptive disturbance tracking controllers (ADTCs is augmented with disturbance and state estimation and adaptive state feedback, in which a controller and estimator, which are designed on the basis of a lower-order model, are used to control a higher-order nonlinear plant. The ADTC requires that the plant be almost strict positive real (ASPR to ensure stability. In this paper, we show that the ASPR property of a plant is retained with the addition of disturbance and state estimation and state feedback, thereby ensuring the stability of the augmented system. The proposed adaptive controller with augmentation is presented in the context of maximum power extraction from a wind turbine in a low-wind-speed operation region. A simulation and comparative study on the National Renewable Energy Laboratory’s (NREL’s 5 MW nonlinear wind turbine model with an existing baseline Proportional-Integral-Derivative(PID controller shows that the proposed controller is more effective than the existing baseline PID controller.

  16. L(sub 1) Adaptive Control Design for NASA AirSTAR Flight Test Vehicle

    Science.gov (United States)

    Gregory, Irene M.; Cao, Chengyu; Hovakimyan, Naira; Zou, Xiaotian

    2009-01-01

    In this paper we present a new L(sub 1) adaptive control architecture that directly compensates for matched as well as unmatched system uncertainty. To evaluate the L(sub 1) adaptive controller, we take advantage of the flexible research environment with rapid prototyping and testing of control laws in the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. We apply the L(sub 1) adaptive control laws to the subscale turbine powered Generic Transport Model. The presented results are from a full nonlinear simulation of the Generic Transport Model and some preliminary pilot evaluations of the L(sub 1) adaptive control law.

  17. Parameters Tuning of Model Free Adaptive Control Based on Minimum Entropy

    Institute of Scientific and Technical Information of China (English)

    Chao Ji; Jing Wang; Liulin Cao; Qibing Jin

    2014-01-01

    Dynamic linearization based model free adaptive control(MFAC) algorithm has been widely used in practical systems, in which some parameters should be tuned before it is successfully applied to process industries. Considering the random noise existing in real processes, a parameter tuning method based on minimum entropy optimization is proposed,and the feature of entropy is used to accurately describe the system uncertainty. For cases of Gaussian stochastic noise and non-Gaussian stochastic noise, an entropy recursive optimization algorithm is derived based on approximate model or identified model. The extensive simulation results show the effectiveness of the minimum entropy optimization for the partial form dynamic linearization based MFAC. The parameters tuned by the minimum entropy optimization index shows stronger stability and more robustness than these tuned by other traditional index,such as integral of the squared error(ISE) or integral of timeweighted absolute error(ITAE), when the system stochastic noise exists.

  18. Algebraic and adaptive learning in neural control systems

    Science.gov (United States)

    Ferrari, Silvia

    A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

  19. Effect of a care plan based on Roy adaptation model biological dimension on stroke patients' physiologic adaptation level.

    Science.gov (United States)

    Alimohammadi, Nasrollah; Maleki, Bibi; Shahriari, Mohsen; Chitsaz, Ahmad

    2015-01-01

    Stroke is a stressful event with several functional, physical, psychological, social, and economic problems that affect individuals' different living balances. With coping strategies, patients try to control these problems and return to their natural life. The aim of this study is to investigate the effect of a care plan based on Roy adaptation model biological dimension on stroke patients' physiologic adaptation level. This study is a clinical trial in which 50 patients, affected by brain stroke and being admitted in the neurology ward of Kashani and Alzahra hospitals, were randomly assigned to control and study groups in Isfahan in 2013. Roy adaptation model care plan was administered in biological dimension in the form of four sessions and phone call follow-ups for 1 month. The forms related to Roy adaptation model were completed before and after intervention in the two groups. Chi-square test and t-test were used to analyze the data through SPSS 18. There was a significant difference in mean score of adaptation in physiological dimension in the study group after intervention (P adaptation in the patients affected by brain stroke in the study and control groups showed a significant increase in physiological dimension in the study group by 47.30 after intervention (P adaptation model biological dimension care plan can result in an increase in adaptation in patients with stroke in physiological dimension. Nurses can use this model for increasing patients' adaptation.

  20. Model-based adaptive sliding mode control of the subcritical boiler-turbine system with uncertainties.

    Science.gov (United States)

    Tian, Zhen; Yuan, Jingqi; Xu, Liang; Zhang, Xiang; Wang, Jingcheng

    2018-05-25

    As higher requirements are proposed for the load regulation and efficiency enhancement, the control performance of boiler-turbine systems has become much more important. In this paper, a novel robust control approach is proposed to improve the coordinated control performance for subcritical boiler-turbine units. To capture the key features of the boiler-turbine system, a nonlinear control-oriented model is established and validated with the history operation data of a 300 MW unit. To achieve system linearization and decoupling, an adaptive feedback linearization strategy is proposed, which could asymptotically eliminate the linearization error caused by the model uncertainties. Based on the linearized boiler-turbine system, a second-order sliding mode controller is designed with the super-twisting algorithm. Moreover, the closed-loop system is proved robustly stable with respect to uncertainties and disturbances. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves excellent tracking performance, strong robustness and chattering reduction. Copyright © 2018. Published by Elsevier Ltd.

  1. Fuzzy adaptive speed control of a permanent magnet synchronous motor

    Science.gov (United States)

    Choi, Han Ho; Jung, Jin-Woo; Kim, Rae-Young

    2012-05-01

    A fuzzy adaptive speed controller is proposed for a permanent magnet synchronous motor (PMSM). The proposed fuzzy adaptive speed regulator is insensitive to model parameter and load torque variations because it does not need any accurate knowledge about the motor parameter and load torque values. The stability of the proposed control system is also proven. The proposed adaptive speed regulator system is implemented by using a TMS320F28335 floating point DSP. Simulation and experimental results are presented to verify the effectiveness of the proposed fuzzy adaptive speed controller under uncertainties such as motor parameter and load torque variations using a prototype PMSM drive system.

  2. Adaptive Optimizing Nonlinear Control Design for an Over-actuated Aircraft Model

    NARCIS (Netherlands)

    Van Oort, E.R.; Sonneveldt, L.; Chu, Q.P.; Mulder, J.A.

    2011-01-01

    In this paper nonlinear adaptive flight control laws based on the backstepping approach are proposed which are applicable to over-actuated nonlinear systems. Instead of solving the control allocation exactly, update laws for the desired control effector signals are defined such that they converge to

  3. Adaptive Neural Network Sliding Mode Control for Quad Tilt Rotor Aircraft

    Directory of Open Access Journals (Sweden)

    Yanchao Yin

    2017-01-01

    Full Text Available A novel neural network sliding mode control based on multicommunity bidirectional drive collaborative search algorithm (M-CBDCS is proposed to design a flight controller for performing the attitude tracking control of a quad tilt rotors aircraft (QTRA. Firstly, the attitude dynamic model of the QTRA concerning propeller tension, channel arm, and moment of inertia is formulated, and the equivalent sliding mode control law is stated. Secondly, an adaptive control algorithm is presented to eliminate the approximation error, where a radial basis function (RBF neural network is used to online regulate the equivalent sliding mode control law, and the novel M-CBDCS algorithm is developed to uniformly update the unknown neural network weights and essential model parameters adaptively. The nonlinear approximation error is obtained and serves as a novel leakage term in the adaptations to guarantee the sliding surface convergence and eliminate the chattering phenomenon, which benefit the overall attitude control performance for QTRA. Finally, the appropriate comparisons among the novel adaptive neural network sliding mode control, the classical neural network sliding mode control, and the dynamic inverse PID control are examined, and comparative simulations are included to verify the efficacy of the proposed control method.

  4. Flight Test of L1 Adaptive Control Law: Offset Landings and Large Flight Envelope Modeling Work

    Science.gov (United States)

    Gregory, Irene M.; Xargay, Enric; Cao, Chengyu; Hovakimyan, Naira

    2011-01-01

    This paper presents new results of a flight test of the L1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented include control law evaluation for piloted offset landing tasks as well as results in support of nonlinear aerodynamic modeling and real-time dynamic modeling of the departure-prone edges of the flight envelope.

  5. Novel Fuzzy-Modeling-Based Adaptive Synchronization of Nonlinear Dynamic Systems

    Directory of Open Access Journals (Sweden)

    Shih-Yu Li

    2017-01-01

    Full Text Available In this paper, a novel fuzzy-model-based adaptive synchronization scheme and its fuzzy update laws of parameters are proposed to address the adaptive synchronization problem. The proposed fuzzy controller does not share the same premise of fuzzy system, and the numbers of fuzzy controllers is reduced effectively through the novel modeling strategy. In addition, based on the adaptive synchronization scheme, the error dynamic system can be guaranteed to be asymptotically stable and the true values of unknown parameters can be obtained. Two identical complicated dynamic systems, Mathieu-Van der pol system (M-V system with uncertainties, are illustrated for numerical simulation example to show the effectiveness and feasibility of the proposed novel adaptive control strategy.

  6. Adaptive control of port-Hamiltonian systems

    NARCIS (Netherlands)

    Dirksz, D.A.; Scherpen, J.M.A.; Edelmayer, András

    2010-01-01

    In this paper an adaptive control scheme is presented for general port-Hamiltonian systems. Adaptive control is used to compensate for control errors that are caused by unknown or uncertain parameter values of a system. The adaptive control is also combined with canonical transformation theory for

  7. Basic Research on Adaptive Model Algorithmic Control

    Science.gov (United States)

    1985-12-01

    Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes

  8. On Using Exponential Parameter Estimators with an Adaptive Controller

    Science.gov (United States)

    Patre, Parag; Joshi, Suresh M.

    2011-01-01

    Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.

  9. Adaptation in integrated assessment modeling: where do we stand?

    OpenAIRE

    Patt, A.; van Vuuren, D.P.; Berkhout, F.G.H.; Aaheim, A.; Hof, A.F.; Isaac, M.; Mechler, R.

    2010-01-01

    Adaptation is an important element on the climate change policy agenda. Integrated assessment models, which are key tools to assess climate change policies, have begun to address adaptation, either by including it implicitly in damage cost estimates, or by making it an explicit control variable. We analyze how modelers have chosen to describe adaptation within an integrated framework, and suggest many ways they could improve the treatment of adaptation by considering more of its bottom-up cha...

  10. A heuristic mathematical model for the dynamics of sensory conflict and motion sickness

    Science.gov (United States)

    Oman, C. M.

    1982-01-01

    By consideration of the information processing task faced by the central nervous system in estimating body spatial orientation and in controlling active body movement using an internal model referenced control strategy, a mathematical model for sensory conflict generation is developed. The model postulates a major dynamic functional role for sensory conflict signals in movement control, as well as in sensory-motor adaptation. It accounts for the role of active movement in creating motion sickness symptoms in some experimental circumstance, and in alleviating them in others. The relationship between motion sickness produced by sensory rearrangement and that resulting from external motion disturbances is explicitly defined. A nonlinear conflict averaging model is proposed which describes dynamic aspects of experimentally observed subjective discomfort sensation, and suggests resulting behaviours. The model admits several possibilities for adaptive mechanisms which do not involve internal model updating. Further systematic efforts to experimentally refine and validate the model are indicated.

  11. Model-based design of adaptive embedded systems

    CERN Document Server

    Hamberg, Roelof; Reckers, Frans; Verriet, Jacques

    2013-01-01

    Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product trade-offs between system qualities at system level. The main challenge in the development of adaptive systems is keeping control of the intrinsic complexity of such systems while working with multi-disciplinary teams to create different parts of the system. Model-Based Development of Adaptive Embedded Systems focuses on the development of adaptive embedded systems both from an architectural and methodological point of view. It describes architectural solution patterns for adaptive systems and state-of-the-art model-based methods and techniques to support adaptive system development. In particular, the book describes the outcome of the Octopus project, a cooperation of a multi-disciplinary team of academic and indus...

  12. Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach.

    Science.gov (United States)

    Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian

    2011-04-01

    This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.

  13. A discrete-time adaptive control scheme for robot manipulators

    Science.gov (United States)

    Tarokh, M.

    1990-01-01

    A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

  14. Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

    Science.gov (United States)

    Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

    2011-01-01

    When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526

  15. A new state space model for the NASA/JPL 70-meter antenna servo controls

    Science.gov (United States)

    Hill, R. E.

    1987-01-01

    A control axis referenced model of the NASA/JPL 70-m antenna structure is combined with the dynamic equations of servo components to produce a comprehansive state variable (matrix) model of the coupled system. An interactive Fortran program for generating the linear system model and computing its salient parameters is described. Results are produced in a state variable, block diagram, and in factored transfer function forms to facilitate design and analysis by classical as well as modern control methods.

  16. Adaptive sequential controller

    Energy Technology Data Exchange (ETDEWEB)

    El-Sharkawi, Mohamed A. (Renton, WA); Xing, Jian (Seattle, WA); Butler, Nicholas G. (Newberg, OR); Rodriguez, Alonso (Pasadena, CA)

    1994-01-01

    An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

  17. Adaptive sequential controller

    Science.gov (United States)

    El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso

    1994-01-01

    An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

  18. Adapting Dynamic Mathematical Models to a Pilot Anaerobic Digestion Reactor

    Directory of Open Access Journals (Sweden)

    F. Haugen, R. Bakke, and B. Lie

    2013-04-01

    Full Text Available A dynamic model has been adapted to a pilot anaerobic reactor fed diarymanure. Both steady-state data from online sensors and laboratory analysis anddynamic operational data from online sensors are used in the model adaptation.The model is based on material balances, and comprises four state variables,namely biodegradable volatile solids, volatile fatty acids, acid generatingmicrobes (acidogens, and methane generating microbes (methanogens. The modelcan predict the methane gas flow produced in the reactor. The model may beused for optimal reactor design and operation, state-estimation and control.Also, a dynamic model for the reactor temperature based on energy balance ofthe liquid in the reactor is adapted. This model may be used for optimizationand control when energy and economy are taken into account.

  19. Retrospective Cost Adaptive Control with Concurrent Closed-Loop Identification

    Science.gov (United States)

    Sobolic, Frantisek M.

    Retrospective cost adaptive control (RCAC) is a discrete-time direct adaptive control algorithm for stabilization, command following, and disturbance rejection. RCAC is known to work on systems given minimal modeling information which is the leading numerator coefficient and any nonminimum-phase (NMP) zeros of the plant transfer function. This information is normally needed a priori and is key in the development of the filter, also known as the target model, within the retrospective performance variable. A novel approach to alleviate the need for prior modeling of both the leading coefficient of the plant transfer function as well as any NMP zeros is developed. The extension to the RCAC algorithm is the use of concurrent optimization of both the target model and the controller coefficients. Concurrent optimization of the target model and controller coefficients is a quadratic optimization problem in the target model and controller coefficients separately. However, this optimization problem is not convex as a joint function of both variables, and therefore nonconvex optimization methods are needed. Finally, insights within RCAC that include intercalated injection between the controller numerator and the denominator, unveil the workings of RCAC fitting a specific closed-loop transfer function to the target model. We exploit this interpretation by investigating several closed-loop identification architectures in order to extract this information for use in the target model.

  20. Calculation of vehicle delay at signal-controlled intersections with adaptive traffic control algorithm

    Directory of Open Access Journals (Sweden)

    Andronov Roman

    2018-01-01

    Full Text Available By widely introducing information technology tools in the field of traffic control, it is possible to increase the capacity of hubs and reduce vehicle delays. Adaptive traffic light control is one of such tools. Its effectiveness can be assessed through traffic flow simulation. The aim of this study is to create a simulation model of a signal-controlled intersection that can be used to assess the effectiveness of adaptive control in various traffic situations, including the presence or absence of pedestrian traffic through an intersection. The model is based on a numerical experiment conducted using the Monte Carlo method. As a result of the study, vehicle delays, queue length and duration of traffic light cycles are calculated subject to different intensities of incoming traffic flows, and the presence or absence of pedestrian traffic.

  1. Adaptive pitch control for load mitigation of wind turbines

    Science.gov (United States)

    Yuan, Yuan; Tang, J.

    2015-04-01

    In this research, model reference adaptive control is examined for the pitch control of wind turbines that may suffer from reduced life owing to extreme loads and fatigue when operated under a high wind speed. Specifically, we aim at making a trade-off between the maximum energy captured and the load induced. The adaptive controller is designed to track the optimal generator speed and at the same time to mitigate component loads under turbulent wind field and other uncertainties. The proposed algorithm is tested on the NREL offshore 5-MW baseline wind turbine, and its performance is compared with that those of the gain scheduled proportional integral (GSPI) control and the disturbance accommodating control (DAC). The results show that the blade root flapwise load can be reduced at a slight expense of optimal power output. The generator speed regulation under adaptive controller is better than DAC.

  2. Synchronization of discrete-time spatiotemporal chaos via adaptive fuzzy control

    International Nuclear Information System (INIS)

    Xue Yueju; Yang Shiyuan

    2003-01-01

    A discrete-time adaptive fuzzy control scheme is presented to synchronize model-unknown coupled Henon-map lattices (CHMLs). The proposed method is robust to approximate errors, parameter mismatches and disturbances, because it integrates the merits of the adaptive fuzzy systems and the variable structure control with a sector. The simulation results of synchronization of CHMLs show that it not only can synchronize model-unknown CHMLs but also is robust against parameter mismatches and noise of the systems. These merits are advantageous for engineering realization

  3. Synchronization of discrete-time spatiotemporal chaos via adaptive fuzzy control

    Energy Technology Data Exchange (ETDEWEB)

    Xue Yueju E-mail: xueyj@mail.tsinghua.edu.cn; Yang Shiyuan E-mail: ysy-dau@tsinghua.edu.cn

    2003-08-01

    A discrete-time adaptive fuzzy control scheme is presented to synchronize model-unknown coupled Henon-map lattices (CHMLs). The proposed method is robust to approximate errors, parameter mismatches and disturbances, because it integrates the merits of the adaptive fuzzy systems and the variable structure control with a sector. The simulation results of synchronization of CHMLs show that it not only can synchronize model-unknown CHMLs but also is robust against parameter mismatches and noise of the systems. These merits are advantageous for engineering realization.

  4. Adaptive multiparameter control: application to a Rapid Thermal Processing process; Commande Adaptative Multivariable: Application a un Procede de Traitement Thermique Rapide

    Energy Technology Data Exchange (ETDEWEB)

    Morales Mago, S J

    1995-12-20

    In this work the problem of temperature uniformity control in rapid thermal processing is addressed by means of multivariable adaptive control. Rapid Thermal Processing (RTP) is a set of techniques proposed for semiconductor fabrication processes such as annealing, oxidation, chemical vapour deposition and others. The product quality depends on two mains issues: precise trajectory following and spatial temperature uniformity. RTP is a fabrication technique that requires a sophisticated real-time multivariable control system to achieve acceptable results. Modelling of the thermal behaviour of the process leads to very complex mathematical models. These are the reasons why adaptive control techniques are chosen. A multivariable linear discrete time model of the highly non-linear process is identified on-line, using an identification scheme which includes supervisory actions. This identified model, combined with a multivariable predictive control law allows to prevent the controller from systems variations. The control laws are obtained by minimization of a quadratic cost function or by pole placement. In some of these control laws, a partial state reference model was included. This reference model allows to incorporate an appropriate tracking capability into the control law. Experimental results of the application of the involved multivariable adaptive control laws on a RTP system are presented. (author) refs

  5. User Defined Geo-referenced Information

    DEFF Research Database (Denmark)

    Konstantas, Dimitri; Villalba, Alfredo; di Marzo Serugendo, Giovanna

    2009-01-01

    . In this paper we present two novel mobile and wireless collaborative services and concepts, the Hovering Information, a mobile, geo-referenced content information management system, and the QoS Information service, providing user observed end-to-end infrastructure geo-related QoS information....

  6. On the role of model-based monitoring for adaptive planning under uncertainty

    Science.gov (United States)

    Raso, Luciano; Kwakkel, Jan; Timmermans, Jos; Haasnoot, Mariolijn

    2016-04-01

    , triggered by the challenge of uncertainty in operational control, may offer solutions from which monitoring for adaptive planning can benefit. Specifically: (i) in control, observations are incorporated into the model through data assimilation, updating the present state, boundary conditions, and parameters based on new observations, diminishing the shadow of the past; (ii) adaptive control is a way to modify the characteristics of the internal model, incorporating new knowledge on the system, countervailing the inhibition of learning; and (iii) in closed-loop control, a continuous system update equips the controller with "inherent robustness", i.e. to capacity to adapts to new conditions even when these were not initially considered. We aim to explore how inherent robustness addresses the challenge of surprise. Innovations in model-based control might help to improve and adapt the models used to support adaptive delta management to new information (reducing uncertainty). Moreover, this would offer a starting point for using these models not only in the design of adaptive plans, but also as part of the monitoring. The proposed research requires multidisciplinary cooperation between control theory, the policy sciences, and integrated assessment modeling.

  7. Implementation of robust adaptive control for robotic manipulator using TMS320C30

    International Nuclear Information System (INIS)

    Han, S. H.

    1996-01-01

    A new adaptive digital control scheme for the robotic manipulator is proposed in this paper. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the adaptive feedforward and feedback controller and PI type time-varying control elements. The control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot. (author)

  8. Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

    Science.gov (United States)

    Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

    2018-04-01

    In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

  9. Synchronization of generalized Henon map by using adaptive fuzzy controller

    Energy Technology Data Exchange (ETDEWEB)

    Xue Yueju E-mail: xueyj@mail.tsinghua.edu.cn; Yang Shiyuan E-mail: ysy-dau@tsinghua.edu.cn

    2003-08-01

    In this paper, an adaptive fuzzy control method is presented to synchronize model-unknown discrete-time generalized Henon map. The proposed method is robust to approximate errors and disturbances, because it integrates the merits of adaptive fuzzy and the variable structure control. Moreover, it can realize the synchronizations of non-identical chaotic systems. The simulation results of synchronization of generalized Henon map show that it not only can synchronize model-unknown generalized Henon map but also is robust against the noise of the systems. These merits are advantageous for engineering realization.

  10. Synchronization of generalized Henon map by using adaptive fuzzy controller

    International Nuclear Information System (INIS)

    Xue Yueju; Yang Shiyuan

    2003-01-01

    In this paper, an adaptive fuzzy control method is presented to synchronize model-unknown discrete-time generalized Henon map. The proposed method is robust to approximate errors and disturbances, because it integrates the merits of adaptive fuzzy and the variable structure control. Moreover, it can realize the synchronizations of non-identical chaotic systems. The simulation results of synchronization of generalized Henon map show that it not only can synchronize model-unknown generalized Henon map but also is robust against the noise of the systems. These merits are advantageous for engineering realization

  11. Modeling of processes of an adaptive business management

    Directory of Open Access Journals (Sweden)

    Karev Dmitry Vladimirovich

    2011-04-01

    Full Text Available On the basis of the analysis of systems of adaptive management board business proposed the original version of the real system of adaptive management, the basis of which used dynamic recursive model cash flow forecast and real data. Proposed definitions and the simulation of scales and intervals of model time in the control system, as well as the thresholds observations and conditions of changing (correction of the administrative decisions. The process of adaptive management is illustrated on the basis proposed by the author of the script of development of business.

  12. Adaptive Controller for 6-DOF Parallel Robot Using T-S Fuzzy Inference

    Directory of Open Access Journals (Sweden)

    Xue Jian

    2013-02-01

    Full Text Available 6-DOF parallel robot always appears in the form of Stewart platform. It has been widely used in industry for the benefits such as strong structural stiffness, high movement accuracy and so on. Space docking technology makes higher requirements of motion accuracy and dynamic performance to the control method on 6-DOF parallel robot. In this paper, a hydraulic 6-DOF parallel robot was used to simulate the docking process. Based on this point, this paper gave a thorough study on the design of an adaptive controller to eliminate the asymmetric of controlled plant and uncertain load force interference. Takagi-Sugeno (T-S fuzzy inference model was used to build the fuzzy adaptive controller. With T-S model, the controller directly imposes adaptive control signal on the plant to make sure that the output of plant could track the reference model output. The controller has simple structure and is easy to implement. Experiment results show that the controller can eliminate asymmetric and achieve good dynamic performance, and has good robustness to load interference.

  13. Light and dark adaptation of visually perceived eye level controlled by visual pitch.

    Science.gov (United States)

    Matin, L; Li, W

    1995-01-01

    The pitch of a visual field systematically influences the elevation at which a monocularly viewing subject sets a target so as to appear at visually perceived eye level (VPEL). The deviation of the setting from true eye level average approximately 0.6 times the angle of pitch while viewing a fully illuminated complexly structured visual field and is only slightly less with one or two pitched-from-vertical lines in a dark field (Matin & Li, 1994a). The deviation of VPEL from baseline following 20 min of dark adaptation reaches its full value less than 1 min after the onset of illumination of the pitched visual field and decays exponentially in darkness following 5 min of exposure to visual pitch, either 30 degrees topbackward or 20 degrees topforward. The magnitude of the VPEL deviation measured with the dark-adapted right eye following left-eye exposure to pitch was 85% of the deviation that followed pitch exposure of the right eye itself. Time constants for VPEL decay to the dark baseline were the same for same-eye and cross-adaptation conditions and averaged about 4 min. The time constants for decay during dark adaptation were somewhat smaller, and the change during dark adaptation extended over a 16% smaller range following the viewing of the dim two-line pitched-from-vertical stimulus than following the viewing of the complex field. The temporal course of light and dark adaptation of VPEL is virtually identical to the course of light and dark adaptation of the scotopic luminance threshold following exposure to the same luminance. We suggest that, following rod stimulation along particular retinal orientations by portions of the pitched visual field, the storage of the adaptation process resides in the retinogeniculate system and is manifested in the focal system as a change in luminance threshold and in the ambient system as a change in VPEL. The linear model previously developed to account for VPEL, which was based on the interaction of influences from the

  14. Helping me, helping you: self-referencing and gender roles in donor advertising.

    Science.gov (United States)

    Hupfer, M E

    2006-06-01

    Donor advertising typically emphasizes altruism, but an appeal to individual self-interest may be more effective in heightening blood donation intentions among youthful nondonors. A total of 292 undergraduate business students at a Canadian university provided complete data in response to a between-subjects full-factorial advertising experiment with sex, self-referencing, and message strategy factors. Self-referencing, or mental processing that links information to the self-concept, was elicited at either a low or moderate level, whereas the message strategy was either agentic (donate blood because you may need it yourself) or communal (donate blood because someone close to you may need it). Dependent variables included identification with the ad, donation intentions, and a discrimination measure of recognition memory. A three-way interaction among sex, self-referencing level (low or moderate), and message (agentic or communal) was found. Two-way self-referencing by message graphs of donation intentions and ad identification showed a parallel structure for males in that their responses were generally more favorable when self-referencing was at a moderate level, regardless of the message type. Among women, however, crossover interactions between the level of self-referencing and the message type (agentic vs. communal) were observed, such that the message's effect differed with the level of self-referencing. For both men and women, the agentic message was more effective than communal ad copy when a moderate level of self-referencing was achieved. Collection agencies should consider appealing to young nondonors by suggesting that they give blood to make it available for themselves if required.

  15. Academic Practice, APA Referencing Style:guidelines for staff and students

    OpenAIRE

    Nielsen, Sandro; Heine, Carmen

    2017-01-01

    Vejledning i at undgå plagiering ved at følge de normer, der gælder for good academic practice. Dette indebærer at man angiver kilder korrekt, og når det er nødvendigt, og at man har en korrekt udformet fortegnelse over referencer. Vejledningen indeholder konkrete eksempler på korrekt kildeangivelse og referencer i henhold til APA referencing system.Vejledning i at undgå plagiering ved at følge de normer, der gælder for good academic practice. Dette indebærer at man angiver kilder korrekt, og...

  16. Adaptive Admittance Control for an Ankle Exoskeleton Using an EMG-Driven Musculoskeletal Model

    Directory of Open Access Journals (Sweden)

    Shaowei Yao

    2018-04-01

    Full Text Available Various rehabilitation robots have been employed to recover the motor function of stroke patients. To improve the effect of rehabilitation, robots should promote patient participation and provide compliant assistance. This paper proposes an adaptive admittance control scheme (AACS consisting of an admittance filter, inner position controller, and electromyography (EMG-driven musculoskeletal model (EDMM. The admittance filter generates the subject's intended motion according to the joint torque estimated by the EDMM. The inner position controller tracks the intended motion, and its parameters are adjusted according to the estimated joint stiffness. Eight healthy subjects were instructed to wear the ankle exoskeleton robot, and they completed a series of sinusoidal tracking tasks involving ankle dorsiflexion and plantarflexion. The robot was controlled by the AACS and a non-adaptive admittance control scheme (NAACS at four fixed parameter levels. The tracking performance was evaluated using the jerk value, position error, interaction torque, and EMG levels of the tibialis anterior (TA and gastrocnemius (GAS. For the NAACS, the jerk value and position error increased with the parameter levels, and the interaction torque and EMG levels of the TA tended to decrease. In contrast, the AACS could maintain a moderate jerk value, position error, interaction torque, and TA EMG level. These results demonstrate that the AACS achieves a good tradeoff between accurate tracking and compliant assistance because it can produce a real-time response to stiffness changes in the ankle joint. The AACS can alleviate the conflict between accurate tracking and compliant assistance and has potential for application in robot-assisted rehabilitation.

  17. Using adaptive model predictive control to customize maintenance therapy chemotherapeutic dosing for childhood acute lymphoblastic leukemia.

    Science.gov (United States)

    Noble, Sarah L; Sherer, Eric; Hannemann, Robert E; Ramkrishna, Doraiswami; Vik, Terry; Rundell, Ann E

    2010-06-07

    Acute lymphoblastic leukemia (ALL) is a common childhood cancer in which nearly one-quarter of patients experience a disease relapse. However, it has been shown that individualizing therapy for childhood ALL patients by adjusting doses based on the blood concentration of active drug metabolite could significantly improve treatment outcome. An adaptive model predictive control (MPC) strategy is presented in which maintenance therapy for childhood ALL is personalized using routine patient measurements of red blood cell mean corpuscular volume as a surrogate for the active drug metabolite concentration. A clinically relevant mathematical model is developed and used to describe the patient response to the chemotherapeutic drug 6-mercaptopurine, with some model parameters being patient-specific. During the course of treatment, the patient-specific parameters are adaptively identified using recurrent complete blood count measurements, which sufficiently constrain the patient parameter uncertainty to support customized adjustments of the drug dose. While this work represents only a first step toward a quantitative tool for clinical use, the simulated treatment results indicate that the proposed mathematical model and adaptive MPC approach could serve as valuable resources to the oncologist toward creating a personalized treatment strategy that is both safe and effective. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  18. Substantiation of Structure of Adaptive Control Systems for Motor Units

    Science.gov (United States)

    Ovsyannikov, S. I.

    2018-05-01

    The article describes the development of new electronic control systems, in particular motor units, for small-sized agricultural equipment. Based on the analysis of traffic control systems, the main course of development of the conceptual designs of motor units has been defined. The systems aimed to control the course motion of the motor unit in automatic mode using the adaptive systems have been developed. The article presents structural models of the conceptual motor units based on electrically controlled systems by the operation of drive motors and adaptive systems that make the motor units completely automated.

  19. Adaptive sliding mode control of tri-layer conjugated polymer actuators

    International Nuclear Information System (INIS)

    Wang, Xiangjiang; Alici, Gursel; Nguyen, Chuc Huu

    2013-01-01

    This paper proposes an adaptive sliding mode control methodology to enhance the positioning ability of conducting polymer actuators typified by tri-layer conjugated polymer actuators. This is motivated by the search for an effective control strategy to command such actuators to a desired configuration in the presence of parametric uncertainties and unmodeled disturbances. After analyzing the stability of the adaptive sliding mode control system, experiments were conducted to demonstrate its satisfactory tracking ability, based on a series of experimental results. Implementation of the control law requires a valid model of the conducting polymer actuator and boundaries of the uncertainties and disturbances. Based on the theoretical and experimental results presented, the adaptive sliding mode control methodology is very attractive in the field of smart actuators which contain significant uncertainties and disturbances. (paper)

  20. Model reference adaptive control of flexible robots in the presence of sudden load changes

    Science.gov (United States)

    Steinvorth, Rodrigo; Kaufman, Howard; Neat, Gregory

    1991-01-01

    Direct command generator tracker based model reference adaptive control (MRAC) algorithms are applied to the dynamics for a flexible-joint arm in the presence of sudden load changes. Because of the need to satisfy a positive real condition, such MRAC procedures are designed so that a feedforward augmented output follows the reference model output, thus, resulting in an ultimately bounded rather than zero output error. Thus, modifications are suggested and tested that: (1) incorporate feedforward into the reference model's output as well as the plant's output, and (2) incorporate a derivative term into only the process feedforward loop. The results of these simulations give a response with zero steady state model following error, and thus encourage further use of MRAC for more complex flexibile robotic systems.

  1. Parameter Identification and Adaptive Control Applied to the Inverted Pendulum

    Directory of Open Access Journals (Sweden)

    Carlos A. Saldarriaga-Cortés

    2012-06-01

    Full Text Available This paper presents a methodology to implement an adaptive control of the inverted pendulum system; which uses the recursive square minimum method for the identification of a dynamic digital model of the plant and then, with its estimated parameters, tune in real time a pole placement control. The plant to be used is an unstable and nonlinear system. This fact, combined with the adaptive controller characteristics, allows the obtained results to be extended to a great variety of systems. The results show that the above methodology was implemented satisfactorily in terms of estimation, stability and control of such a system. It was established that adaptive techniques have a proper performance even in systems with complex features such as nonlinearity and instability.

  2. A better norm-referenced grading using the standard deviation criterion.

    Science.gov (United States)

    Chan, Wing-shing

    2014-01-01

    The commonly used norm-referenced grading assigns grades to rank-ordered students in fixed percentiles. It has the disadvantage of ignoring the actual distance of scores among students. A simple norm-referenced grading via standard deviation is suggested for routine educational grading. The number of standard deviation of a student's score from the class mean was used as the common yardstick to measure achievement level. Cumulative probability of a normal distribution was referenced to help decide the amount of students included within a grade. RESULTS of the foremost 12 students from a medical examination were used for illustrating this grading method. Grading by standard deviation seemed to produce better cutoffs in allocating an appropriate grade to students more according to their differential achievements and had less chance in creating arbitrary cutoffs in between two similarly scored students than grading by fixed percentile. Grading by standard deviation has more advantages and is more flexible than grading by fixed percentile for norm-referenced grading.

  3. Geo-referenced modelling of metal concentrations in river basins at the catchment scale

    Science.gov (United States)

    Hüffmeyer, N.; Berlekamp, J.; Klasmeier, J.

    2009-04-01

    1. Introduction The European Water Framework Directive demands the good ecological and chemical state of surface waters [1]. This implies the reduction of unwanted metal concentrations in surface waters. To define reasonable environmental target values and to develop promising mitigation strategies a detailed exposure assessment is required. This includes the identification of emission sources and the evaluation of their effect on local and regional surface water concentrations. Point source emissions via municipal or industrial wastewater that collect metal loads from a wide variety of applications and products are important anthropogenic pathways into receiving waters. Natural background and historical influences from ore-mining activities may be another important factor. Non-point emissions occur via surface runoff and erosion from drained land area. Besides deposition metals can be deposited by fertilizer application or the use of metal products such as wires or metal fences. Surface water concentrations vary according to the emission strength of sources located nearby and upstream of the considered location. A direct link between specific emission sources and pathways on the one hand and observed concentrations can hardly be established by monitoring alone. Geo-referenced models such as GREAT-ER (Geo-referenced Regional Exposure Assessment Tool for European Rivers) deliver spatially resolved concentrations in a whole river basin and allow for evaluating the causal relationship between specific emissions and resulting concentrations. This study summarizes the results of investigations for the metals zinc and copper in three German catchments. 2. The model GREAT-ER The geo-referenced model GREAT-ER has originally been developed to simulate and assess chemical burden of European river systems from multiple emission sources [2]. Emission loads from private households and rainwater runoff are individually estimated based on average consumption figures, runoff rates

  4. Adaptive control of chaotic continuous-time systems with delay

    Science.gov (United States)

    Tian, Yu-Chu; Gao, Furong

    1998-06-01

    A simple delay system governed by a first-order differential-delay equation may behave chaotically, but the conditions for the system to have such behaviors have not been well recognized. In this paper, a set of rules is postulated first for the conditions for the delay system to display chaos. A model-reference adaptive control scheme is then proposed to control the chaotic system state to converge to an arbitrarily given reference trajectory with certain and uncertain system parameters. Numerical examples are given to analyze the chaotic behaviors of the delay system and to demonstrate the effectiveness of the proposed adaptive control scheme.

  5. Modelo circumplejo del afecto aplicado al control de sistemas dinámicos

    Directory of Open Access Journals (Sweden)

    José Danilo Rairán-Antolines

    2009-01-01

    Full Text Available In this paper we propose the design of a new control strategy for dynamic systems based on human emotions. Since psychologists and neuroscientists have demonstrated that emotions are indispensable in the Decision-Making-Process, and decision-making is the work of every controller, it is our desire to emulate emotions in the systems design. Here we deal with four areas of application for this invention in which autonomy and adaptability are essential. As well, eight emotion computational models are referenced. Given that these involve cognition, it is concluded as necessary to make adjustments to include one of these in a control strategy. For this reason, this article formulates the use of the Circumplex Model of Affect, a model which labels a human emotion as a variable.

  6. Adaptive neural network controller for the molten steel level control of strip casting processes

    International Nuclear Information System (INIS)

    Chen, Hung Yi; Huang, Shiuh Jer

    2010-01-01

    The twin-roll strip casting process is a steel-strip production method which combines continuous casting and hot rolling processes. The production line from molten liquid steel to the final steel-strip is shortened and the production cost is reduced significantly as compared to conventional continuous casting. The quality of strip casting process depends on many process parameters, such as molten steel level in the pool, solidification position, and roll gap. Their relationships are complex and the strip casting process has the properties of nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate process model for designing a model-based controller to monitor the strip quality. In this paper, a model-free adaptive neural network controller is developed to overcome this problem. The proposed control strategy is based on a neural network structure combined with a sliding-mode control scheme. An adaptive rule is employed to on-line adjust the weights of radial basis functions by using the reaching condition of a specified sliding surface. This surface has the on-line learning ability to respond to the system's nonlinear and time-varying behaviors. Since this model-free controller has a simple control structure and small number of control parameters, it is easy to implement. Simulation results, based on a semi experimental system dynamic model and parameters, are executed to show the control performance of the proposed intelligent controller. In addition, the control performance is compared with that of a traditional Pid controller

  7. Adaptive Augmenting Control and Launch Vehicle Adaptive Control Flight Experiments

    Data.gov (United States)

    National Aeronautics and Space Administration — Researchers at NASA Armstrong are working to further the development of an adaptive augmenting control algorithm (AAC). The AAC was developed to improve the...

  8. Benchmark referencing of neutron dosimetry measurements

    International Nuclear Information System (INIS)

    Eisenhauer, C.M.; Grundl, J.A.; Gilliam, D.M.; McGarry, E.D.; Spiegel, V.

    1980-01-01

    The concept of benchmark referencing involves interpretation of dosimetry measurements in applied neutron fields in terms of similar measurements in benchmark fields whose neutron spectra and intensity are well known. The main advantage of benchmark referencing is that it minimizes or eliminates many types of experimental uncertainties such as those associated with absolute detection efficiencies and cross sections. In this paper we consider the cavity external to the pressure vessel of a power reactor as an example of an applied field. The pressure vessel cavity is an accessible location for exploratory dosimetry measurements aimed at understanding embrittlement of pressure vessel steel. Comparisons with calculated predictions of neutron fluence and spectra in the cavity provide a valuable check of the computational methods used to estimate pressure vessel safety margins for pressure vessel lifetimes

  9. A driver-adaptive stability control strategy for sport utility vehicles

    Science.gov (United States)

    Zhu, Shenjin; He, Yuping

    2017-08-01

    Conventional vehicle stability control (VSC) systems are designed for average drivers. For a driver with a good driving skill, the VSC systems may be redundant; for a driver with a poor driving skill, the VSC intervention may be inadequate. To increase safety of sport utility vehicles (SUVs), this paper proposes a novel driver-adaptive VSC (DAVSC) strategy based on scaling the target yaw rate commanded by the driver. The DAVSC system is adaptive to drivers' driving skills. More control effort would be exerted for drivers with poor driving skills, and vice versa. A sliding mode control (SMC)-based differential braking (DB) controller is designed using a three degrees of freedom (DOF) yaw-plane model. An eight DOF nonlinear yaw-roll model is used to simulate the SUV dynamics. Two driver models, namely longitudinal and lateral, are used to 'drive' the virtual SUV. By integrating the virtual SUV, the DB controller, and the driver models, the performance of the DAVSC system is investigated. The simulations demonstrate the effectiveness of the DAVSC strategy.

  10. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

    Science.gov (United States)

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-03-14

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

  11. Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

    Science.gov (United States)

    Volyanskyy, Kostyantyn Y.

    Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

  12. On Synergistic Integration of Adaptive Dithering Based Internal Model Control for Hysteresis Compensation in Piezoactuated Nanopositioner

    Directory of Open Access Journals (Sweden)

    Saikat Kumar Shome

    2015-01-01

    Full Text Available Piezoelectric-stack actuated platforms are very popular in the parlance of nanopositioning with myriad applications like micro/nanofactory, atomic force microscopy, scanning probe microscopy, wafer design, biological cell manipulation, and so forth. Motivated by the necessity to improve trajectory tracking in such applications, this paper addresses the problem of rate dependent hysteretic nonlinearity in piezoelectric actuators (PEA. The classical second order Dahl model for hysteresis encapsulation is introduced first, followed by the identification of parameters through particle swarm optimization. A novel inversion based feedforward mechanism in combination with a feedback compensator is proposed to achieve high-precision tracking wherein the paradoxical concept of noise as a performance enhancer is introduced in the realm of PZAs. Having observed that dither induced stochastic resonance in the presence of periodic forcing reduces tracking error, dither capability is further explored in conjunction with a novel output harmonics based adaptive control scheme. The proposed adaptive controller is then augmented with an internal model control based approach to impart robustness against parametric variations and external disturbances. The proposed control law has been employed to track multifrequency signals with consistent compensation of rate dependent hysteresis of the PEA. The results indicate a greatly improved positioning accuracy along with considerable robustness achieved with the proposed integrated approach even for dual axis tracking applications.

  13. Robust intelligent sliding model control using recurrent cerebellar model articulation controller for uncertain nonlinear chaotic systems

    International Nuclear Information System (INIS)

    Peng Yafu

    2009-01-01

    In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This RISMC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control (SMC) due to unknown system dynamics, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The all adaptation laws of the RISMC system are derived based on the Lyapunov stability analysis and projection algorithm, so that the stability of the system can be guaranteed. Finally, the proposed RISMC system is applied to control a Van der Pol oscillator, a Genesio chaotic system and a Chua's chaotic circuit. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. In addition, the advantages of the proposed RISMC are indicated in comparison with a SMC system

  14. Implementation of a model reference adaptive control system using neural network to control a fast breeder reactor evaporator

    International Nuclear Information System (INIS)

    Ugolini, D.; Yoshikawa, S.; Endou, A.

    1994-01-01

    Artificial intelligence is foreseen as the base for new control systems aimed to replace traditional controllers and to assist and eventually advise plant operators. This paper discusses the development of an indirect model reference adaptive control (MRAC) system, using the artificial neural network (ANN) technique, and its implementation to control the outlet steam temperature of a sodium to water evaporator. The ANN technique is applied in the identification and in the control process of the indirect MRAC system. The emphasis is placed on demonstrating the efficacy of the indirect MRAC system in controlling the outlet steam temperature of the evaporator, and on showing the important function covered by the ANN technique. An important characteristic of this control system is that it relays only on some selected input variables and output variables of the evaporator model. These are the variables that can be actually measured or calculated in a real environment. The results obtained applying the indirect MRAC system to control the evaporator model are quite remarkable. The outlet temperature of the steam is almost perfectly kept close to its desired set point, when the evaporator is forced to depart from steady state conditions, either due to the variation of some input variables or due to the alteration of some of its internal parameters. The results also show the importance of the role played by the ANN technique in the overall control action. The connecting weights of the ANN nodes self adjust to follow the modifications which may occur in the characteristic of the evaporator model during a transient. The efficiency and the accuracy of the control action highly depends on the on-line identification process of the ANN, which is responsible for upgrading the connecting weights of the ANN nodes. (J.P.N.)

  15. Dynamic Self-Adaptive Reliability Control for Electric-Hydraulic Systems

    Directory of Open Access Journals (Sweden)

    Yi Wan

    2015-02-01

    Full Text Available The high-speed electric-hydraulic proportional control is a new development of the hydraulic control technique with high reliability, low cost, efficient energy, and easy maintenance; it is widely used in industrial manufacturing and production. However, there are still some unresolved challenges, the most notable being the requirements of high stability and real-time by the classical control algorithm due to its high nonlinear characteristics. We propose a dynamic self-adaptive mixed control method based on the least squares support vector machine (LSSVM and the genetic algorithm for high-speed electric-hydraulic proportional control systems in this paper; LSSVM is used to identify and adjust online a nonlinear electric-hydraulic proportional system, and the genetic algorithm is used to optimize the control law of the controlled system and dynamic self-adaptive internal model control and predictive control are implemented by using the mixed intelligent method. The internal model and the inverse control model are online adjusted together. At the same time, a time-dependent Hankel matrix is constructed based on sample data; thus finite dimensional solution can be optimized on finite dimensional space. The results of simulation experiments show that the dynamic characteristics are greatly improved by the mixed intelligent control strategy, and good tracking and high stability are met in condition of high frequency response.

  16. Design of a new adaptive fuzzy controller and its implementation for the damping force control of a magnetorheological damper

    International Nuclear Information System (INIS)

    Phu, Do Xuan; Shah, Kruti; Choi, Seung-Bok

    2014-01-01

    This paper presents a new adaptive fuzzy controller and its implementation for the damping force control of a magnetorheological (MR) fluid damper in order to validate the effectiveness of the control performance. An interval type 2 fuzzy model is built, and then combined with modified adaptive control to achieve the desired damping force. In the formulation of the new adaptive controller, an enhanced iterative algorithm is integrated with the fuzzy model to decrease the time of calculation (D Wu 2013 IEEE Trans. Fuzzy Syst. 21 80–99) and the control algorithm is synthesized based on the H ∞ tracking technique. In addition, for the verification of good control performance of the proposed controller, a cylindrical MR damper which can be applied to the vibration control of a washing machine is designed and manufactured. For the operating fluid, a recently developed plate-like particle-based MR fluid is used instead of a conventional MR fluid featuring spherical particles. To highlight the control performance of the proposed controller, two existing adaptive fuzzy control algorithms proposed by other researchers are adopted and altered for a comparative study. It is demonstrated from both simulation and experiment that the proposed new adaptive controller shows better performance of damping force control in terms of response time and tracking accuracy than the existing approaches. (papers)

  17. Modeling adaptive and non-adaptive responses to environmental change

    DEFF Research Database (Denmark)

    Coulson, Tim; Kendall, Bruce E; Barthold, Julia A.

    2017-01-01

    , with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we...... construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive....... Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full...

  18. Decentralized adaptive control of manipulators - Theory, simulation, and experimentation

    Science.gov (United States)

    Seraji, Homayoun

    1989-01-01

    The author presents a simple decentralized adaptive-control scheme for multijoint robot manipulators based on the independent joint control concept. The control objective is to achieve accurate tracking of desired joint trajectories. The proposed control scheme does not use the complex manipulator dynamic model, and each joint is controlled simply by a PID (proportional-integral-derivative) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. Simulation results are given for a two-link direct-drive manipulator under adaptive independent joint control. The results illustrate trajectory tracking under coupled dynamics and varying payload. The proposed scheme is implemented on a MicroVAX II computer for motion control of the three major joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite coupled nonlinear joint dynamics.

  19. Adaptive Landing Gear: Optimum Control Strategy and Potential for Improvement

    Directory of Open Access Journals (Sweden)

    Grzegorz Mikułowski

    2009-01-01

    Full Text Available An adaptive landing gear is a landing gear (LG capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~validated model of a real, passive landing gear as a reference. Potential for improvement is estimated statistically in terms of the mean and median (significant peak strut forces as well as in terms of the extended safe sinking velocity range. Three control strategies are verified experimentally using a laboratory test stand.

  20. Adaptive optimal stochastic state feedback control of resistive wall modes in tokamaks

    International Nuclear Information System (INIS)

    Sun, Z.; Sen, A.K.; Longman, R.W.

    2006-01-01

    An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least-square method with exponential forgetting factor and covariance resetting is used to identify (experimentally determine) the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time-dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used

  1. Defining adaptation in a generic multi layer model: CAM: The GRAPPLE Conceptual Adaptation Model

    NARCIS (Netherlands)

    Hendrix, M.; De Bra, P.M.E.; Pechenizkiy, M.; Smits, D.; Cristea, A.I.; Dillenbourg, P.; Specht, M.

    2008-01-01

    Authoring of Adaptive Hypermedia is a difficult and time consuming task. Reference models like LAOS and AHAM separate adaptation and content in different layers. Systems like AHA!, offer graphical tools based on these models to allow authors to define adaptation without knowing any adaptation

  2. Rotor Field Oriented Control with adaptive Iron Loss Compensation

    DEFF Research Database (Denmark)

    Rasmussen, Henrik; Vadstrup, P.; Børsting, H.

    1999-01-01

    It is well known from the literature that iron loses in an induction motor implies field angle estimation errors and hence detuning problems. In this paper a new method for estimating the iron loss resistor in an induction motor is presented. The method is based on a traditional dynamic model...... controlled in a Field Oriented Control scheme. This deviation is used to force a MIT-rule based adaptive estimator. An adaptive compensator containing the developed estimator is introduced and verified by simulations and tested by real time experiments....

  3. Direct adaptive control of a PUMA 560 industrial robot

    Science.gov (United States)

    Seraji, Homayoun; Lee, Thomas; Delpech, Michel

    1989-01-01

    The implementation and experimental validation of a new direct adaptive control scheme on a PUMA 560 industrial robot is described. The testbed facility consists of a Unimation PUMA 560 six-jointed robot and controller, and a DEC MicroVAX II computer which hosts the Robot Control C Library software. The control algorithm is implemented on the MicroVAX which acts as a digital controller for the PUMA robot, and the Unimation controller is effectively bypassed and used merely as an I/O device to interface the MicroVAX to the joint motors. The control algorithm for each robot joint consists of an auxiliary signal generated by a constant-gain Proportional plus Integral plus Derivative (PID) controller, and an adaptive position-velocity (PD) feedback controller with adjustable gains. The adaptive independent joint controllers compensate for the inter-joint couplings and achieve accurate trajectory tracking without the need for the complex dynamic model and parameter values of the robot. Extensive experimental results on PUMA joint control are presented to confirm the feasibility of the proposed scheme, in spite of strong interactions between joint motions. Experimental results validate the capabilities of the proposed control scheme. The control scheme is extremely simple and computationally very fast for concurrent processing with high sampling rates.

  4. Design and FPGA-implementation of an improved adaptive fuzzy logic controller for DC motor speed control

    Directory of Open Access Journals (Sweden)

    E.A. Ramadan

    2014-09-01

    Full Text Available This paper presents an improved adaptive fuzzy logic speed controller for a DC motor, based on field programmable gate array (FPGA hardware implementation. The developed controller includes an adaptive fuzzy logic control (AFLC algorithm, which is designed and verified with a nonlinear model of DC motor. Then, it has been synthesised, functionally verified and implemented using Xilinx Integrated Software Environment (ISE and Spartan-3E FPGA. The performance of this controller has been successfully validated with good tracking results under different operating conditions.

  5. Adaptive fuzzy trajectory control for biaxial motion stage system

    Directory of Open Access Journals (Sweden)

    Wei-Lung Mao

    2016-04-01

    Full Text Available Motion control is an essential part of industrial machinery and manufacturing systems. In this article, the adaptive fuzzy controller is proposed for precision trajectory tracking control in biaxial X-Y motion stage system. The theoretical analyses of direct fuzzy control which is insensitive to parameter uncertainties and external load disturbances are derived to demonstrate the feasibility to track the reference trajectories. The Lyapunov stability theorem has been used to testify the asymptotic stability of the whole system, and all the signals are bounded in the closed-loop system. The intelligent position controller combines the merits of the adaptive fuzzy control with robust characteristics and learning ability for periodic command tracking of a servo drive mechanism. The simulation and experimental results on square, triangle, star, and circle reference contours are presented to show that the proposed controller indeed accomplishes the better tracking performances with regard to model uncertainties. It is observed that the convergence of parameters and tracking errors can be faster and smaller compared with the conventional adaptive fuzzy control in terms of average tracking error and tracking error standard deviation.

  6. Adaptive Control of Nonlinear Discrete-Time Systems by Using OS-ELM Neural Networks

    Directory of Open Access Journals (Sweden)

    Xiao-Li Li

    2014-01-01

    Full Text Available As a kind of novel feedforward neural network with single hidden layer, ELM (extreme learning machine neural networks are studied for the identification and control of nonlinear dynamic systems. The property of simple structure and fast convergence of ELM can be shown clearly. In this paper, we are interested in adaptive control of nonlinear dynamic plants by using OS-ELM (online sequential extreme learning machine neural networks. Based on data scope division, the problem that training process of ELM neural network is sensitive to the initial training data is also solved. According to the output range of the controlled plant, the data corresponding to this range will be used to initialize ELM. Furthermore, due to the drawback of conventional adaptive control, when the OS-ELM neural network is used for adaptive control of the system with jumping parameters, the topological structure of the neural network can be adjusted dynamically by using multiple model switching strategy, and an MMAC (multiple model adaptive control will be used to improve the control performance. Simulation results are included to complement the theoretical results.

  7. Fuzzy adaptive robust control for space robot considering the effect of the gravity

    Directory of Open Access Journals (Sweden)

    Qin Li

    2014-12-01

    Full Text Available Space robot is assembled and tested in gravity environment, and completes on-orbit service (OOS in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control (FARC strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative (PD controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.

  8. R@P: developing and promoting the Referencing@Portsmouth service

    OpenAIRE

    Matthews, J.; Gwyer, Roisin; Jones, Linda; Worden, Anne

    2009-01-01

    The library at the University of Portsmouth (UoP) has for some years been providing advice on referencing across the institution, either at enquiry desks or through subject/faculty librarians.In addition, annually updated short guidesto Vancouver and Harvard (American Psychological Association variant) were produced by thelibrary, and distributed to new students in their thousands. This sufficed for a time but in thelast three or four years the number of referencing enquiries being fielded by...

  9. Vibrations control of light rail transportation vehicle via PID type fuzzy controller using parameters adaptive method

    OpenAIRE

    METİN, Muzaffer; GÜÇLÜ, Rahmi

    2014-01-01

    In this study, a conventional PID type fuzzy controller and parameter adaptive fuzzy controller are designed to control vibrations actively of a light rail transport vehicle which modeled as 6 degree-of-freedom system and compared performances of these two controllers. Rail vehicle model consists of a passenger seat and its suspension system, vehicle body, bogie, primary and secondary suspensions and wheels. The similarity between mathematical model and real system is shown by compar...

  10. Coordinating IMC-PID and adaptive SMC controllers for a PEMFC.

    Science.gov (United States)

    Wang, Guo-Liang; Wang, Yong; Shi, Jun-Hai; Shao, Hui-He

    2010-01-01

    For a Proton Exchange Membrane Fuel Cell (PEMFC) power plant with a methanol reformer, the process parameters and power output are considered simultaneously to avoid violation of the constraints and to keep the fuel cell power plant safe and effective. In this paper, a novel coordinating scheme is proposed by combining an Internal Model Control (IMC) based PID Control and adaptive Sliding Mode Control (SMC). The IMC-PID controller is designed for the reformer of the fuel flow rate according to the expected first-order dynamic properties. The adaptive SMC controller of the fuel cell current has been designed using the constant plus proportional rate reaching law. The parameters of the SMC controller are adaptively tuned according to the response of the fuel flow rate control system. When the power output controller feeds back the current references to these two controllers, the coordinating controllers system works in a system-wide way. The simulation results of the PEMFC power plant demonstrate the effectiveness of the proposed method. 2009 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Developed adaptive neuro-fuzzy algorithm to control air conditioning ...

    African Journals Online (AJOL)

    The paper developed artificial intelligence technique adaptive neuro-fuzzy controller for air conditioning systems at different pressures. The first order Sugeno fuzzy inference system was implemented and utilized for modeling and controller design. In addition, the estimation of the heat transfer rate and water mass flow rate ...

  12. Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

    Science.gov (United States)

    Xiao, Lingfei; Du, Yanbin; Hu, Jixiang; Jiang, Bin

    2018-03-01

    In this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.

  13. Unstructured mesh adaptivity for urban flooding modelling

    Science.gov (United States)

    Hu, R.; Fang, F.; Salinas, P.; Pain, C. C.

    2018-05-01

    Over the past few decades, urban floods have been gaining more attention due to their increase in frequency. To provide reliable flooding predictions in urban areas, various numerical models have been developed to perform high-resolution flood simulations. However, the use of high-resolution meshes across the whole computational domain causes a high computational burden. In this paper, a 2D control-volume and finite-element flood model using adaptive unstructured mesh technology has been developed. This adaptive unstructured mesh technique enables meshes to be adapted optimally in time and space in response to the evolving flow features, thus providing sufficient mesh resolution where and when it is required. It has the advantage of capturing the details of local flows and wetting and drying front while reducing the computational cost. Complex topographic features are represented accurately during the flooding process. For example, the high-resolution meshes around the buildings and steep regions are placed when the flooding water reaches these regions. In this work a flooding event that happened in 2002 in Glasgow, Scotland, United Kingdom has been simulated to demonstrate the capability of the adaptive unstructured mesh flooding model. The simulations have been performed using both fixed and adaptive unstructured meshes, and then results have been compared with those published 2D and 3D results. The presented method shows that the 2D adaptive mesh model provides accurate results while having a low computational cost.

  14. Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

  15. A new robust adaptive controller for vibration control of active engine mount subjected to large uncertainties

    International Nuclear Information System (INIS)

    Fakhari, Vahid; Choi, Seung-Bok; Cho, Chang-Hyun

    2015-01-01

    This work presents a new robust model reference adaptive control (MRAC) for vibration control caused from vehicle engine using an electromagnetic type of active engine mount. Vibration isolation performances of the active mount associated with the robust controller are evaluated in the presence of large uncertainties. As a first step, an active mount with linear solenoid actuator is prepared and its dynamic model is identified via experimental test. Subsequently, a new robust MRAC based on the gradient method with σ-modification is designed by selecting a proper reference model. In designing the robust adaptive control, structured (parametric) uncertainties in the stiffness of the passive part of the mount and in damping ratio of the active part of the mount are considered to investigate the robustness of the proposed controller. Experimental and simulation results are presented to evaluate performance focusing on the robustness behavior of the controller in the face of large uncertainties. The obtained results show that the proposed controller can sufficiently provide the robust vibration control performance even in the presence of large uncertainties showing an effective vibration isolation. (paper)

  16. Neuromusculoskeletal models based on the muscle synergy hypothesis for the investigation of adaptive motor control in locomotion via sensory-motor coordination.

    Science.gov (United States)

    Aoi, Shinya; Funato, Tetsuro

    2016-03-01

    Humans and animals walk adaptively in diverse situations by skillfully manipulating their complicated and redundant musculoskeletal systems. From an analysis of measured electromyographic (EMG) data, it appears that despite complicated spatiotemporal properties, muscle activation patterns can be explained by a low dimensional spatiotemporal structure. More specifically, they can be accounted for by the combination of a small number of basic activation patterns. The basic patterns and distribution weights indicate temporal and spatial structures, respectively, and the weights show the muscle sets that are activated synchronously. In addition, various locomotor behaviors have similar low dimensional structures and major differences appear in the basic patterns. These analysis results suggest that neural systems use muscle group combinations to solve motor control redundancy problems (muscle synergy hypothesis) and manipulate those basic patterns to create various locomotor functions. However, it remains unclear how the neural system controls such muscle groups and basic patterns through neuromechanical interactions in order to achieve adaptive locomotor behavior. This paper reviews simulation studies that explored adaptive motor control in locomotion via sensory-motor coordination using neuromusculoskeletal models based on the muscle synergy hypothesis. Herein, the neural mechanism in motor control related to the muscle synergy for adaptive locomotion and a potential muscle synergy analysis method including neuromusculoskeletal modeling for motor impairments and rehabilitation are discussed. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  17. Adaptation in integrated assessment modeling: where do we stand?

    NARCIS (Netherlands)

    Patt, A.; van Vuuren, D.P.; Berkhout, F.G.H.; Aaheim, A.; Hof, A.F.; Isaac, M.; Mechler, R.

    2010-01-01

    Adaptation is an important element on the climate change policy agenda. Integrated assessment models, which are key tools to assess climate change policies, have begun to address adaptation, either by including it implicitly in damage cost estimates, or by making it an explicit control variable. We

  18. Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

    Science.gov (United States)

    Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

    2017-10-01

    Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

  19. Adaptive Control System of Hydraulic Pressure Based on The Mathematical Modeling

    Science.gov (United States)

    Pilipenko, A. V.; Pilipenko, A. P.; Kanatnikov, N. V.

    2016-04-01

    In this paper, the authors highlight the problem of replacing an old heavy industrial equipment, and offer the replacement of obsolete control systems on the modern adaptive control system, which takes into account changes in the hydraulic system of the press and compensates them with a corrective action. The proposed system can reduce a water hammer and thereby increase the durability of the hydraulic system and tools.

  20. Adaptive powertrain control for plugin hybrid electric vehicles

    Science.gov (United States)

    Kedar-Dongarkar, Gurunath; Weslati, Feisel

    2013-10-15

    A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

  1. Adaptive self-correcting control system

    International Nuclear Information System (INIS)

    Ellis, S.H.

    1984-01-01

    A control system for regulating a controlled device or process, such as a turbofan engine, produces independent multiple estimates of one or more controlled variables of the device or process by combining the signals from a plurality of feedback sensors, which provide information related to the controlled variables, in weighted nonordered pairs. The independent multiple estimates of each controlled variable are combined into a weighted average, and individual estimates which differ by more than a specified amount from the weighted average are edited and temporarily removed from consideration. A revised weighted average value of each controlled variable is then produced, and this value is used to limit or control operation of the device or process. Adaptive trim is provided to compensate for changes in the device or process being controlled, such as engine deterioration, by slowly trimming each individual estimate toward the mean, and includes error compensation which constrains the weighted sum of the adaptive trims to equal zero, thereby preventing the adaptive trim from changing the operating level of the device or process. A secondary editing circuit based on a majority rule principle identifies a failed feedback sensor and permanently excludes all individual estimates of the controlled variable based on the failed sensor. Editing boundaries are increased and adaptive trim rate is varied when a transient occurs in the operation of the device or process. Further transient compensation may be required for a system with more severe transient requirements, and this invention includes compensation to selected feedback parameters such as turbine temperature to account for differences between steady state and transient values

  2. Geospatial cryptography: enabling researchers to access private, spatially referenced, human subjects data for cancer control and prevention.

    Science.gov (United States)

    Jacquez, Geoffrey M; Essex, Aleksander; Curtis, Andrew; Kohler, Betsy; Sherman, Recinda; Emam, Khaled El; Shi, Chen; Kaufmann, Andy; Beale, Linda; Cusick, Thomas; Goldberg, Daniel; Goovaerts, Pierre

    2017-07-01

    As the volume, accuracy and precision of digital geographic information have increased, concerns regarding individual privacy and confidentiality have come to the forefront. Not only do these challenge a basic tenet underlying the advancement of science by posing substantial obstacles to the sharing of data to validate research results, but they are obstacles to conducting certain research projects in the first place. Geospatial cryptography involves the specification, design, implementation and application of cryptographic techniques to address privacy, confidentiality and security concerns for geographically referenced data. This article defines geospatial cryptography and demonstrates its application in cancer control and surveillance. Four use cases are considered: (1) national-level de-duplication among state or province-based cancer registries; (2) sharing of confidential data across cancer registries to support case aggregation across administrative geographies; (3) secure data linkage; and (4) cancer cluster investigation and surveillance. A secure multi-party system for geospatial cryptography is developed. Solutions under geospatial cryptography are presented and computation time is calculated. As services provided by cancer registries to the research community, de-duplication, case aggregation across administrative geographies and secure data linkage are often time-consuming and in some instances precluded by confidentiality and security concerns. Geospatial cryptography provides secure solutions that hold significant promise for addressing these concerns and for accelerating the pace of research with human subjects data residing in our nation's cancer registries. Pursuit of the research directions posed herein conceivably would lead to a geospatially encrypted geographic information system (GEGIS) designed specifically to promote the sharing and spatial analysis of confidential data. Geospatial cryptography holds substantial promise for accelerating the

  3. An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

    Directory of Open Access Journals (Sweden)

    Guo-Qiang Zeng

    2017-11-01

    Full Text Available As the penetration level of renewable distributed generations such as wind turbine generator and photovoltaic stations increases, the load frequency control issue of a multi-area interconnected power system becomes more challenging. This paper presents an adaptive model predictive load frequency control method for a multi-area interconnected power system with photovoltaic generation by considering some nonlinear features such as a dead band for governor and generation rate constraint for steam turbine. The dynamic characteristic of this system is formulated as a discrete-time state space model firstly. Then, the predictive dynamic model is obtained by introducing an expanded state vector, and rolling optimization of control signal is implemented based on a cost function by minimizing the weighted sum of square predicted errors and square future control values. The simulation results on a typical two-area power system consisting of photovoltaic and thermal generator have demonstrated the superiority of the proposed model predictive control method to these state-of-the-art control techniques such as firefly algorithm, genetic algorithm, and population extremal optimization-based proportional-integral control methods in cases of normal conditions, load disturbance and parameters uncertainty.

  4. Unsteady CFD modeling of micro-adaptive flow control for an axisymmetric body

    International Nuclear Information System (INIS)

    Sahu, J.; Heavey, K.R.

    2005-01-01

    This paper describes a computational study undertaken, as part of a grand challenge project, to consider the aerodynamic effect of micro-adaptive flow control as a means to provide the divert authority needed to maneuver a projectile at a low subsonic speed. A time-accurate Navier-Stokes computational technique has been used to obtain numerical solutions for the unsteady microjet-interaction flow field for the axisymmetric projectile body at subsonic speeds, Mach = 0.11 and 0.24 and angles of attack, 0 o to 4 o . Numerical solutions have been obtained using both Renolds-Averaged Navier-Stokes (RANS) and a hybrid RANS/Large Eddy Simulation (LES) turbulence models. Unsteady numerical results show the effect of the jet on the flow field and the aerodynamic coefficients, in particular the lift force. This research has provided an increased fundamental understanding of the complex, three-dimensional, time-dependent, aerodynamic interactions associated with micro-jet control for yawing spin-stabilized munitions. (author)

  5. Unsteady CFD modeling of micro-adaptive flow control for an axisymmetric body

    Energy Technology Data Exchange (ETDEWEB)

    Sahu, J.; Heavey, K.R. [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD (United States)]. E-mail: sahu@arl.army.mil

    2005-07-01

    This paper describes a computational study undertaken, as part of a grand challenge project, to consider the aerodynamic effect of micro-adaptive flow control as a means to provide the divert authority needed to maneuver a projectile at a low subsonic speed. A time-accurate Navier-Stokes computational technique has been used to obtain numerical solutions for the unsteady microjet-interaction flow field for the axisymmetric projectile body at subsonic speeds, Mach = 0.11 and 0.24 and angles of attack, 0{sup o} to 4{sup o}. Numerical solutions have been obtained using both Renolds-Averaged Navier-Stokes (RANS) and a hybrid RANS/Large Eddy Simulation (LES) turbulence models. Unsteady numerical results show the effect of the jet on the flow field and the aerodynamic coefficients, in particular the lift force. This research has provided an increased fundamental understanding of the complex, three-dimensional, time-dependent, aerodynamic interactions associated with micro-jet control for yawing spin-stabilized munitions. (author)

  6. Flight Test Approach to Adaptive Control Research

    Science.gov (United States)

    Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

    2011-01-01

    The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

  7. Automated Manipulation of Micro-Nano Objects with SPM by Using L1 Adaptive Controller

    Directory of Open Access Journals (Sweden)

    Qinmin Yang

    2012-12-01

    Full Text Available In this paper, a novel control methodology for automatically manipulating micro/nano particles by using a Scanning Probe Microscope (SPM is presented. First of all, a mathematical model of micro/nanomanipulation, including the interactive forces and dynamics between the tip, particle and substrate along with the roughness effect of the substrate, is described. Then, the L1 adaptive control design for the manipulation system of micro/nano objects is presented, which consists of a state predictor with fast adaptation, a piece-wise continuous adaptive law and a low-pass filtered control design. This control framework can handle nonlinear uncertainties and ensures uniformly bounded tracking performance. The tracking performance bound can be systematically improved by reducing the step size of integration. Rigorous mathematical proof is provided. Simulation results demonstrate the effectiveness of the presented L1 adaptive control law on the micro/nanomanipulation model.

  8. Adaptive Observer-Based Fault-Tolerant Control Design for Uncertain Systems

    Directory of Open Access Journals (Sweden)

    Huaming Qian

    2015-01-01

    Full Text Available This study focuses on the design of the robust fault-tolerant control (FTC system based on adaptive observer for uncertain linear time invariant (LTI systems. In order to improve robustness, rapidity, and accuracy of traditional fault estimation algorithm, an adaptive fault estimation algorithm (AFEA using an augmented observer is presented. By utilizing a new fault estimator model, an improved AFEA based on linear matrix inequality (LMI technique is proposed to increase the performance. Furthermore, an observer-based state feedback fault-tolerant control strategy is designed, which guarantees the stability and performance of the faulty system. Moreover, the adaptive observer and the fault-tolerant controller are designed separately, whose performance can be considered, respectively. Finally, simulation results of an aircraft application are presented to illustrate the effectiveness of the proposed design methods.

  9. Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

    Science.gov (United States)

    VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.

    2014-01-01

    Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a

  10. Nonlinear Constrained Adaptive Backstepping Tracking Control for a Hypersonic Vehicle with Uncertainty

    Directory of Open Access Journals (Sweden)

    Qin Zou

    2015-01-01

    Full Text Available The control problem of a flexible hypersonic vehicle is presented, where input saturation and aerodynamic uncertainty are considered. A control-oriented model including aerodynamic uncertainty is derived for simple controller design due to the nonlinearity and complexity of hypersonic vehicle model. Then it is separated into velocity subsystem and altitude subsystem. On the basis of the integration of robust adaptive control and backstepping technique, respective controller is designed for each subsystem, where an auxiliary signal provided by an additional dynamic system is used to compensate for the control saturation effect. Then to deal with the “explosion of terms” problem inherent in backstepping control, a novel first-order filter is proposed. Simulation results are included to demonstrate the effectiveness of the adaptive backstepping control scheme.

  11. Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control.

    Science.gov (United States)

    Shen, Gang; Zhu, Zhencai; Zhao, Jinsong; Zhu, Weidong; Tang, Yu; Li, Xiang

    2017-03-01

    This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H ∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement. Copyright © 2016. Published by Elsevier Ltd.

  12. Nonlinear adaptive PID control for greenhouse environment based on RBF network.

    Science.gov (United States)

    Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui

    2012-01-01

    This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production.

  13. Design of control system for piezoelectric deformable mirror based on fuzzy self-adaptive PID control

    Science.gov (United States)

    Xiao, Nan; Gao, Wei; Song, Zongxi

    2017-10-01

    With the rapid development of adaptive optics technology, it is widely used in the fields of astronomical telescope imaging, laser beam shaping, optical communication and so on. As the key component of adaptive optics systems, the deformable mirror plays a role in wavefront correction. In order to achieve the high speed and high precision of deformable mirror system tracking control, it is necessary to find out the influence of each link on the system performance to model the system and design the controller. This paper presents a method about the piezoelectric deformable mirror driving control system.

  14. Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

    Science.gov (United States)

    Nguyen, Nhan

    2013-01-01

    This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

  15. Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.

    Science.gov (United States)

    Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H

    2017-07-01

    In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.

  16. Simulation and Rapid Prototyping of Adaptive Control Systems using the Adaptive Blockset for Simulink

    DEFF Research Database (Denmark)

    Ravn, Ole

    1998-01-01

    The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller implement...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown.......The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...

  17. Standardization of a geo-referenced fishing data set for the Indian Ocean bigeye tuna, Thunnus obesus (1952-2014)

    Science.gov (United States)

    Wibawa, Teja A.; Lehodey, Patrick; Senina, Inna

    2017-02-01

    Geo-referenced catch and fishing effort data of the bigeye tuna fisheries in the Indian Ocean over 1952-2014 were analyzed and standardized to facilitate population dynamics modeling studies. During this 62-year historical period of exploitation, many changes occurred both in the fishing techniques and the monitoring of activity. This study includes a series of processing steps used for standardization of spatial resolution, conversion and standardization of catch and effort units, raising of geo-referenced catch into nominal catch level, screening and correction of outliers, and detection of major catchability changes over long time series of fishing data, i.e., the Japanese longline fleet operating in the tropical Indian Ocean. A total of 30 fisheries were finally determined from longline, purse seine and other-gears data sets, from which 10 longline and 4 purse seine fisheries represented 96 % of the whole historical geo-referenced catch. Nevertheless, one-third of total nominal catch is still not included due to a total lack of geo-referenced information and would need to be processed separately, accordingly to the requirements of the study. The geo-referenced records of catch, fishing effort and associated length frequency samples of all fisheries are available at PANGAEA.864154" target="_blank">doi:10.1594/PANGAEA.864154.

  18. Wind Turbine Pitch Control and Load Mitigation Using an L1 Adaptive Approach

    Directory of Open Access Journals (Sweden)

    Danyong Li

    2014-01-01

    Full Text Available We present an application of L1 adaptive output feedback control design to wind turbine collective pitch control and load mitigation. Our main objective is the design of an L1 output feedback controller without wind speed estimation, ensuring that the generator speed tracks the reference trajectory with robustness to uncertain parameters and time-varying disturbances (mainly the uniform wind disturbance across the wind turbine rotor. The wind turbine model CART (controls advanced research turbine developed by the national renewable energy laboratory (NREL is used to validate the performance of the proposed L1 adaptive controller using the FAST (fatigue, aerodynamics, structures, and turbulence code. A comparative study is also conducted between the proposed controller and the most popular methods in practice: gain scheduling PI (GSPI controls and disturbance accommodating control (DAC methods. The results show better performance of L1 output feedback controller over the other two methods. Moreover, based on the FAST software and LQR analysis in the reference model selection of L1 adaptive controller, tradeoff can be achieved between control performance and loads mitigation.

  19. Global Harmonic Current Rejection of Nonlinear Backstepping Control with Multivariable Adaptive Internal Model Principle for Grid-Connected Inverter under Distorted Grid Voltage

    Directory of Open Access Journals (Sweden)

    Yang Yu

    2013-01-01

    Full Text Available Based on a brief review on current harmonics generation mechanism for grid-connected inverter under distorted grid voltage, the harmonic disturbances and uncertain items are immersed into the original state-space differential equation of grid-connected inverter. A new algorithm of global current harmonic rejection based on nonlinear backstepping control with multivariable internal model principle is proposed for grid-connected inverter with exogenous disturbances and uncertainties. A type of multivariable internal model for a class of nonlinear harmonic disturbances is constructed. Based on application of backstepping control law of the nominal system, a multivariable adaptive state feedback controller combined with multivariable internal model and adaptive control law is designed to guarantee the closed-loop system globally uniformly bounded, which is proved by a constructed Lyapunov function. The presented algorithm extends rejection of nonlinear single-input systems to multivariable globally defined normal form, the correctness and effectiveness of which are verified by the simulation results.

  20. Towards an adaptive model for greenhouse control

    NARCIS (Netherlands)

    Speetjens, S.L.; Stigter, J.D.; Straten, van G.

    2009-01-01

    Application of advanced controllers in horticultural practice requires detailed models. Even highly sophisticated models require regular attention from the user due to changing circumstances like plant growth, changing material properties and modifications in greenhouse design and layout. Moreover,

  1. Anisotropic mesh adaptation for marine ice-sheet modelling

    Science.gov (United States)

    Gillet-Chaulet, Fabien; Tavard, Laure; Merino, Nacho; Peyaud, Vincent; Brondex, Julien; Durand, Gael; Gagliardini, Olivier

    2017-04-01

    Improving forecasts of ice-sheets contribution to sea-level rise requires, amongst others, to correctly model the dynamics of the grounding line (GL), i.e. the line where the ice detaches from its underlying bed and goes afloat on the ocean. Many numerical studies, including the intercomparison exercises MISMIP and MISMIP3D, have shown that grid refinement in the GL vicinity is a key component to obtain reliable results. Improving model accuracy while maintaining the computational cost affordable has then been an important target for the development of marine icesheet models. Adaptive mesh refinement (AMR) is a method where the accuracy of the solution is controlled by spatially adapting the mesh size. It has become popular in models using the finite element method as they naturally deal with unstructured meshes, but block-structured AMR has also been successfully applied to model GL dynamics. The main difficulty with AMR is to find efficient and reliable estimators of the numerical error to control the mesh size. Here, we use the estimator proposed by Frey and Alauzet (2015). Based on the interpolation error, it has been found effective in practice to control the numerical error, and has some flexibility, such as its ability to combine metrics for different variables, that makes it attractive. Routines to compute the anisotropic metric defining the mesh size have been implemented in the finite element ice flow model Elmer/Ice (Gagliardini et al., 2013). The mesh adaptation is performed using the freely available library MMG (Dapogny et al., 2014) called from Elmer/Ice. Using a setup based on the inter-comparison exercise MISMIP+ (Asay-Davis et al., 2016), we study the accuracy of the solution when the mesh is adapted using various variables (ice thickness, velocity, basal drag, …). We show that combining these variables allows to reduce the number of mesh nodes by more than one order of magnitude, for the same numerical accuracy, when compared to uniform mesh

  2. Adaptation in the fuzzy self-organising controller

    DEFF Research Database (Denmark)

    Jantzen, Jan; Poulsen, Niels Kjølstad

    2003-01-01

    This simulation study provides an analysis of the adaptation mechanism in the self-organising fuzzy controller, SOC. The approach is to apply a traditional adaptive control viewpoint. A simplified performance measure in the SOC controller is used in a loss function, and thus the MIT rule implies...... an update mechanism similar to the SOC update mechanism. Two simulations of proportionally controlled systems show the behaviour of the proportional gain as it adapts to a specified behaviour....

  3. What Drives Business Model Adaptation?

    DEFF Research Database (Denmark)

    Saebi, Tina; Lien, Lasse B.; Foss, Nicolai Juul

    2017-01-01

    Business models change as managers not only innovate business models, but also engage in more mundane adaptation in response to external changes, such as changes in the level or composition of demand. However, little is known about what causes such business model adaptation. We employ threat......-rigidity as well as prospect theory to examine business model adaptation in response to external threats and opportunities. Additionally, drawing on the behavioural theory of the firm, we argue that the past strategic orientation of a firm creates path dependencies that influence the propensity of the firm...... to adapt its business model. We test our hypotheses on a sample of 1196 Norwegian companies, and find that firms are more likely to adapt their business model under conditions of perceived threats than opportunities, and that strategic orientation geared towards market development is more conducive...

  4. Adaptive Tracking Control of an Electro-Pneumatic Clutch Actuator

    Directory of Open Access Journals (Sweden)

    Glenn-Ole Kaasa

    2003-10-01

    Full Text Available This paper deals with the application of a simple adaptive algorithm for robust tracking control of an electro-pneumatic clutch actuator with output feedback. We present a mathematical model of the strongly nonlinear system, and implement an adaptive algorithm, based on a parallel feedforward compensator (PFC to remove the relative-degree-1 restriction. We propose a practical method of constructing the PFC, and introduce a simple modification that removes an inherent restriction on bandwidth of the nonlinear system. We show that the adaptive algorithm deals well with nonlinearities, and we achieve tracking corresponding to a settling-time of 150 ms.

  5. Adaptive PID control based on orthogonal endocrine neural networks.

    Science.gov (United States)

    Milovanović, Miroslav B; Antić, Dragan S; Milojković, Marko T; Nikolić, Saša S; Perić, Staniša Lj; Spasić, Miodrag D

    2016-12-01

    A new intelligent hybrid structure used for online tuning of a PID controller is proposed in this paper. The structure is based on two adaptive neural networks, both with built-in Chebyshev orthogonal polynomials. First substructure network is a regular orthogonal neural network with implemented artificial endocrine factor (OENN), in the form of environmental stimuli, to its weights. It is used for approximation of control signals and for processing system deviation/disturbance signals which are introduced in the form of environmental stimuli. The output values of OENN are used to calculate artificial environmental stimuli (AES), which represent required adaptation measure of a second network-orthogonal endocrine adaptive neuro-fuzzy inference system (OEANFIS). OEANFIS is used to process control, output and error signals of a system and to generate adjustable values of proportional, derivative, and integral parameters, used for online tuning of a PID controller. The developed structure is experimentally tested on a laboratory model of the 3D crane system in terms of analysing tracking performances and deviation signals (error signals) of a payload. OENN-OEANFIS performances are compared with traditional PID and 6 intelligent PID type controllers. Tracking performance comparisons (in transient and steady-state period) showed that the proposed adaptive controller possesses performances within the range of other tested controllers. The main contribution of OENN-OEANFIS structure is significant minimization of deviation signals (17%-79%) compared to other controllers. It is recommended to exploit it when dealing with a highly nonlinear system which operates in the presence of undesirable disturbances. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Network models for solving the problem of multicriterial adaptive optimization of investment projects control with several acceptable technologies

    Science.gov (United States)

    Shorikov, A. F.; Butsenko, E. V.

    2017-10-01

    This paper discusses the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. On the basis of network modeling proposed a new economic and mathematical model and a method for solving the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. Network economic and mathematical modeling allows you to determine the optimal time and calendar schedule for the implementation of the investment project and serves as an instrument to increase the economic potential and competitiveness of the enterprise. On a meaningful practical example, the processes of forming network models are shown, including the definition of the sequence of actions of a particular investment projecting process, the network-based work schedules are constructed. The calculation of the parameters of network models is carried out. Optimal (critical) paths have been formed and the optimal time for implementing the chosen technologies of the investment project has been calculated. It also shows the selection of the optimal technology from a set of possible technologies for project implementation, taking into account the time and cost of the work. The proposed model and method for solving the problem of managing investment projects can serve as a basis for the development, creation and application of appropriate computer information systems to support the adoption of managerial decisions by business people.

  7. Constraint-Referenced Analytics of Algebra Learning

    Science.gov (United States)

    Sutherland, Scot M.; White, Tobin F.

    2016-01-01

    The development of the constraint-referenced analytics tool for monitoring algebra learning activities presented here came from the desire to firstly, take a more quantitative look at student responses in collaborative algebra activities, and secondly, to situate those activities in a more traditional introductory algebra setting focusing on…

  8. Adaptive fuzzy-neural-network control for maglev transportation system.

    Science.gov (United States)

    Wai, Rong-Jong; Lee, Jeng-Dao

    2008-01-01

    A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies.

  9. Adaptive control of 5 DOF upper-limb exoskeleton robot with improved safety.

    Science.gov (United States)

    Kang, Hao-Bo; Wang, Jian-Hui

    2013-11-01

    This paper studies an adaptive control strategy for a class of 5 DOF upper-limb exoskeleton robot with a special safety consideration. The safety requirement plays a critical role in the clinical treatment when assisting patients with shoulder, elbow and wrist joint movements. With the objective of assuring the tracking performance of the pre-specified operations, the proposed adaptive controller is firstly designed to be robust to the model uncertainties. To further improve the safety and fault-tolerance in the presence of unknown large parameter variances or even actuator faults, the adaptive controller is on-line updated according to the information provided by an adaptive observer without additional sensors. An output tracking performance is well achieved with a tunable error bound. The experimental example also verifies the effectiveness of the proposed control scheme. © 2013 ISA. Published by ISA. All rights reserved.

  10. Research on Adaptive Neural Network Control System Based on Nonlinear U-Model with Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Fengxia Xu

    2014-01-01

    Full Text Available U-model can approximate a large class of smooth nonlinear time-varying delay system to any accuracy by using time-varying delay parameters polynomial. This paper proposes a new approach, namely, U-model approach, to solving the problems of analysis and synthesis for nonlinear systems. Based on the idea of discrete-time U-model with time-varying delay, the identification algorithm of adaptive neural network is given for the nonlinear model. Then, the controller is designed by using the Newton-Raphson formula and the stability analysis is given for the closed-loop nonlinear systems. Finally, illustrative examples are given to show the validity and applicability of the obtained results.

  11. Simulation Research on Adaptive Control of a Six-degree-of-freedom Material-testing Machine

    Directory of Open Access Journals (Sweden)

    Dan Wang

    2014-02-01

    Full Text Available This paper presents an adaptive controller equipped with a stiffness estimation method for a novel material-testing machine, in order to alleviate the performance depression caused by the stiffness variance of the tested specimen. The dynamic model of the proposed machine is built using the Kane method, and kinematic model is established with a closed-form solution. The stiffness estimation method is developed based on the recursive least-squares method and the proposed stiffness equivalent matrix. Control performances of the adaptive controller are simulated in detail. The simulation results illustrate that the proposed controller can greatly improve the control performance of the target material-testing machine by online stiffness estimation and adaptive parameter tuning, especially in low-cycle fatigue (LCF and high-cycle fatigue (HCF tests.

  12. Multiple Estimation Architecture in Discrete-Time Adaptive Mixing Control

    Directory of Open Access Journals (Sweden)

    Simone Baldi

    2013-05-01

    Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.

  13. Monitoring the Performance of a Neuro-Adaptive Controller

    Science.gov (United States)

    Schumann, Johann; Gupta, Pramod

    2004-01-01

    Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.

  14. Adaptive Method Using Controlled Grid Deformation

    Directory of Open Access Journals (Sweden)

    Florin FRUNZULICA

    2011-09-01

    Full Text Available The paper presents an adaptive method using the controlled grid deformation over an elastic, isotropic and continuous domain. The adaptive process is controlled with the principal strains and principal strain directions and uses the finite elements method. Numerical results are presented for several test cases.

  15. Development of flank wear model of cutting tool by using adaptive feedback linear control system on machining AISI D2 steel and AISI 4340 steel

    Science.gov (United States)

    Orra, Kashfull; Choudhury, Sounak K.

    2016-12-01

    The purpose of this paper is to build an adaptive feedback linear control system to check the variation of cutting force signal to improve the tool life. The paper discusses the use of transfer function approach in improving the mathematical modelling and adaptively controlling the process dynamics of the turning operation. The experimental results shows to be in agreement with the simulation model and error obtained is less than 3%. The state space approach model used in this paper successfully check the adequacy of the control system through controllability and observability test matrix and can be transferred from one state to another by appropriate input control in a finite time. The proposed system can be implemented to other machining process under varying range of cutting conditions to improve the efficiency and observability of the system.

  16. Adaptive LQG controller tuning

    Czech Academy of Sciences Publication Activity Database

    Novák, Miroslav; Böhm, Josef; Nedoma, Petr; Tesař, Ludvík

    2003-01-01

    Roč. 150, č. 6 (2003), s. 655-665 ISSN 1350-2379 R&D Projects: GA ČR GA102/02/0204; GA AV ČR IBS1075102 Institutional research plan: CEZ:AV0Z1075907 Keywords : adaptive controller * LQG controller * controller design Subject RIV: JB - Sensors, Measurment, Regulation Impact factor: 0.745, year: 2003

  17. Robust adaptive multivariable higher-order sliding mode flight control for air-breathing hypersonic vehicle with actuator failures

    Directory of Open Access Journals (Sweden)

    Peng Li

    2016-10-01

    Full Text Available This article proposes an adaptive multivariable higher-order sliding mode control for the longitudinal model of an air-breathing vehicle under system uncertainties and actuator failures. Firstly, a fast finite-time control law is designed for a chain of integrators. Secondly, based on the input/output feedback linearization technique, the system uncertainty and external disturbances are modeled as additive certainty and the actuator failures are modeled as multiplicative uncertainty. By using the proposed fast finite-time control law, a robust multivariable higher-order sliding mode control is designed for the air-breathing hypersonic vehicle with actuator failures. Finally, adaptive laws are proposed for the adaptation of the parameters in the robust multivariable higher-order sliding mode control. Thus, the bounds of the uncertainties are not needed in the control system design. Simulation results show the effectiveness of the proposed robust adaptive multivariable higher-order sliding mode control.

  18. Roy's Adaptation Model-Guided Education and Promoting the Adaptation of Veterans With Lower Extremities Amputation.

    Science.gov (United States)

    Azarmi, Somayeh; Farsi, Zahra

    2015-10-01

    Any defect in extremities of the body can affect different life aspects. The purpose of this study was to investigate the effect of Roy's adaptation model-guided education on promoting the adaptation of veterans with lower extremities amputation. In a randomized clinical trial, 60 veterans with lower extremities amputation referring to Kowsar Orthotics and Prosthetics Center of veterans clinic in Tehran, Iran, were recruited with convenience method and were randomly assigned to intervention and control groups during 2013 - 2014. For data collection, Roy's adaptation model questionnaire was used. After completing the questionnaires in both groups, maladaptive behaviors were determined in the intervention group and an education program based on Roy's adaptation model was implemented. After two months, both groups completed the questionnaires again. Data was analyzed with SPSS software. Independent t-test showed statistically significant differences between the two groups in the post-test stage in terms of the total score of adaptation (P = 0.001) as well as physiologic (P = 0.0001) and role function modes (P = 0.004). The total score of adaptation (139.43 ± 5.45 to 127.54 ± 14.55, P = 0.006) as well as the scores of physiologic (60.26 ± 5.45 to 53.73 ± 7.79, P = 0.001) and role function (20.30 ± 2.42 to 18.13 ± 3.18, P = 0.01) modes in the intervention group significantly increased, whereas the scores of self-concept (42.10 ± 4.71 to 39.40 ± 5.67, P = 0.21) and interdependence (16.76 ± 2.22 to 16.30 ± 2.57, P = 0.44) modes in the two stages did not have a significant difference. Findings of this research indicated that the Roy's adaptation model-guided education promoted the adaptation level of physiologic and role function modes in veterans with lower extremities amputation. However, this intervention could not promote adaptation in self-concept and interdependence modes. More intervention is advised based on Roy's adaptation model for improving the

  19. Selecting Items for Criterion-Referenced Tests.

    Science.gov (United States)

    Mellenbergh, Gideon J.; van der Linden, Wim J.

    1982-01-01

    Three item selection methods for criterion-referenced tests are examined: the classical theory of item difficulty and item-test correlation; the latent trait theory of item characteristic curves; and a decision-theoretic approach for optimal item selection. Item contribution to the standardized expected utility of mastery testing is discussed. (CM)

  20. Tracking error constrained robust adaptive neural prescribed performance control for flexible hypersonic flight vehicle

    Directory of Open Access Journals (Sweden)

    Zhonghua Wu

    2017-02-01

    Full Text Available A robust adaptive neural control scheme based on a back-stepping technique is developed for the longitudinal dynamics of a flexible hypersonic flight vehicle, which is able to ensure the state tracking error being confined in the prescribed bounds, in spite of the existing model uncertainties and actuator constraints. Minimal learning parameter technique–based neural networks are used to estimate the model uncertainties; thus, the amount of online updated parameters is largely lessened, and the prior information of the aerodynamic parameters is dispensable. With the utilization of an assistant compensation system, the problem of actuator constraint is overcome. By combining the prescribed performance function and sliding mode differentiator into the neural back-stepping control design procedure, a composite state tracking error constrained adaptive neural control approach is presented, and a new type of adaptive law is constructed. As compared with other adaptive neural control designs for hypersonic flight vehicle, the proposed composite control scheme exhibits not only low-computation property but also strong robustness. Finally, two comparative simulations are performed to demonstrate the robustness of this neural prescribed performance controller.

  1. Adaptive Dynamic Surface Control for Generator Excitation Control System

    Directory of Open Access Journals (Sweden)

    Zhang Xiu-yu

    2014-01-01

    Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.

  2. Adaptive tracking control of nonholonomic systems: an example

    NARCIS (Netherlands)

    Lefeber, A.A.J.; Nijmeijer, Henk

    1999-01-01

    We study an example of an adaptive (state) tracking control problem for a four-wheel mobile robot, as it is an illustrative example of the general adaptive state-feedback tracking control problem. It turns out that formulating the adaptive state-feedback tracking control problem is not

  3. A diversified portfolio model of adaptability.

    Science.gov (United States)

    Chandra, Siddharth; Leong, Frederick T L

    2016-12-01

    A new model of adaptability, the diversified portfolio model (DPM) of adaptability, is introduced. In the 1950s, Markowitz developed the financial portfolio model by demonstrating that investors could optimize the ratio of risk and return on their portfolios through risk diversification. The DPM integrates attractive features of a variety of models of adaptability, including Linville's self-complexity model, the risk and resilience model, and Bandura's social cognitive theory. The DPM draws on the concept of portfolio diversification, positing that diversified investment in multiple life experiences, life roles, and relationships promotes positive adaptation to life's challenges. The DPM provides a new integrative model of adaptability across the biopsychosocial levels of functioning. More importantly, the DPM addresses a gap in the literature by illuminating the antecedents of adaptive processes studied in a broad array of psychological models. The DPM is described in relation to the biopsychosocial model and propositions are offered regarding its utility in increasing adaptiveness. Recommendations for future research are also offered. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  4. Maritime adaptive optics beam control

    OpenAIRE

    Corley, Melissa S.

    2010-01-01

    The Navy is interested in developing systems for horizontal, near ocean surface, high-energy laser propagation through the atmosphere. Laser propagation in the maritime environment requires adaptive optics control of aberrations caused by atmospheric distortion. In this research, a multichannel transverse adaptive filter is formulated in Matlab's Simulink environment and compared to a complex lattice filter that has previously been implemented in large system simulations. The adaptive fil...

  5. Command Filtered Adaptive Fuzzy Neural Network Backstepping Control for Marine Power System

    Directory of Open Access Journals (Sweden)

    Xin Zhang

    2014-01-01

    Full Text Available In order to retrain chaotic oscillation of marine power system which is excited by periodic electromagnetism perturbation, a novel command-filtered adaptive fuzzy neural network backstepping control method is designed. First, the mathematical model of marine power system is established based on the two parallel nonlinear model. Then, main results of command-filtered adaptive fuzzy neural network backstepping control law are given. And the Lyapunov stability theory is applied to prove that the system can remain closed-loop asymptotically stable with this controller. Finally, simulation results indicate that the designed controller can suppress chaotic oscillation with fast convergence speed that makes the system return to the equilibrium point quickly; meanwhile, the parameter which induces chaotic oscillation can also be discriminated.

  6. Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation

    Directory of Open Access Journals (Sweden)

    Yuzheng Yang

    2014-01-01

    Full Text Available An adaptive sliding controller using radial basis function (RBF network to approximate the unknown system dynamics microelectromechanical systems (MEMS gyroscope sensor is proposed. Neural controller is proposed to approximate the unknown system model and sliding controller is employed to eliminate the approximation error and attenuate the model uncertainties and external disturbances. Online neural network (NN weight tuning algorithms, including correction terms, are designed based on Lyapunov stability theory, which can guarantee bounded tracking errors as well as bounded NN weights. The tracking error bound can be made arbitrarily small by increasing a certain feedback gain. Numerical simulation for a MEMS angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive neural control scheme and demonstrate the satisfactory tracking performance and robustness.

  7. Adaptive critic learning techniques for engine torque and air-fuel ratio control.

    Science.gov (United States)

    Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

    2008-08-01

    A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

  8. Adaptive Torque Control of Variable Speed Wind Turbines

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, K. E.

    2004-08-01

    The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry for variable speed wind turbines below rated power. This adaptive controller uses a simple, highly intuitive gain adaptation law designed to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds.

  9. Adaptive online state-of-charge determination based on neuro-controller and neural network

    Energy Technology Data Exchange (ETDEWEB)

    Shen Yanqing, E-mail: network_hawk@126.co [Department of Automation, Chongqing Industry Polytechnic College, Jiulongpo District, Chongqing 400050 (China)

    2010-05-15

    This paper presents a novel approach using adaptive artificial neural network based model and neuro-controller for online cell State of Charge (SOC) determination. Taking cell SOC as model's predictive control input unit, radial basis function neural network, which can adjust its structure to prediction error with recursive least square algorithm, is used to simulate battery system. Besides that, neuro-controller based on Back-Propagation Neural Network (BPNN) and modified PID controller is used to decide the control input of battery system, i.e., cell SOC. Finally this algorithm is applied for the SOC determination of lead-acid batteries, and results of lab tests on physical cells, compared with model prediction, are presented. Results show that the ANN based battery system model adaptively simulates battery system with great accuracy, and the predicted SOC simultaneously converges to the real value quickly within the error of +-1 as time goes on.

  10. CONSTRUCTIVE MODEL OF ADAPTATION OF DATA STRUCTURES IN RAM. PART II. CONSTRUCTORS OF SCENARIOS AND ADAPTATION PROCESSES

    Directory of Open Access Journals (Sweden)

    V. I. Shynkarenko

    2016-04-01

    their processing with the performance criteria in the framework of unified approach and applied means. The developed models allow us to study the process of adaptation and control it. Practical value. The developed model and methods allow automatically changing the data placement in the RAM and their algorithmic connection depending on the operational requirements, the design features of the hardware and software operating environment.

  11. Dynamic modeling and simulation of an induction motor with adaptive backstepping design of an input-output feedback linearization controller in series hybrid electric vehicle

    Directory of Open Access Journals (Sweden)

    Jalalifar Mehran

    2007-01-01

    Full Text Available In this paper using adaptive backstepping approach an adaptive rotor flux observer which provides stator and rotor resistances estimation simultaneously for induction motor used in series hybrid electric vehicle is proposed. The controller of induction motor (IM is designed based on input-output feedback linearization technique. Combining this controller with adaptive backstepping observer the system is robust against rotor and stator resistances uncertainties. In additional, mechanical components of a hybrid electric vehicle are called from the Advanced Vehicle Simulator Software Library and then linked with the electric motor. Finally, a typical series hybrid electric vehicle is modeled and investigated. Various tests, such as acceleration traversing ramp, and fuel consumption and emission are performed on the proposed model of a series hybrid vehicle. Computer simulation results obtained, confirm the validity and performance of the proposed IM control approach using for series hybrid electric vehicle.

  12. Robust model predictive cooperative adaptive cruise control subject to V2V impairments

    NARCIS (Netherlands)

    Van Nunen, Ellen; Verhaegh, Jan; Silvas, Emilia; Semsar-Kazerooni, Elham; Van De Wouw, Nathan

    2018-01-01

    To improve traffic throughput, Cooperative Adaptive Cruise Control (CACC) has been proposed as a solution. The usage of Vehicle-to-Vehicle (V2V) communication enables short following distances, thereby increasing road capacity and fuel reduction (especially for trucks). Control designs for CACC use

  13. Adaptive Sliding Mode Control Method Based on Nonlinear Integral Sliding Surface for Agricultural Vehicle Steering Control

    Directory of Open Access Journals (Sweden)

    Taochang Li

    2014-01-01

    Full Text Available Automatic steering control is the key factor and essential condition in the realization of the automatic navigation control of agricultural vehicles. In order to get satisfactory steering control performance, an adaptive sliding mode control method based on a nonlinear integral sliding surface is proposed in this paper for agricultural vehicle steering control. First, the vehicle steering system is modeled as a second-order mathematic model; the system uncertainties and unmodeled dynamics as well as the external disturbances are regarded as the equivalent disturbances satisfying a certain boundary. Second, a transient process of the desired system response is constructed in each navigation control period. Based on the transient process, a nonlinear integral sliding surface is designed. Then the corresponding sliding mode control law is proposed to guarantee the fast response characteristics with no overshoot in the closed-loop steering control system. Meanwhile, the switching gain of sliding mode control is adaptively adjusted to alleviate the control input chattering by using the fuzzy control method. Finally, the effectiveness and the superiority of the proposed method are verified by a series of simulation and actual steering control experiments.

  14. Sector-condition-based results for adaptive control and synchronization of chaotic systems under input saturation

    International Nuclear Information System (INIS)

    Iqbal, Muhammad; Rehan, Muhammad; Hong, Keum-Shik; Khaliq, Abdul; Saeed-ur-Rehman

    2015-01-01

    This paper addresses the design of adaptive feedback controllers for two problems (namely, stabilization and synchronization) of chaotic systems with unknown parameters by considering input saturation constraints. A novel generalized sector condition is developed to deal with the saturation nonlinearities for synthesizing the nonlinear and the adaptive controllers for the stabilization and synchronization control objectives. By application of the proposed sector condition and rigorous regional stability analysis, control and adaptation laws are formulated to guarantee local stabilization of a nonlinear system under actuator saturation. Further, simple control and adaptation laws are developed to synchronize two chaotic systems under uncertain parameters and input saturation nonlinearity. Numerical simulation results for Rössler and FitzHugh–Nagumo models are provided to demonstrate the effectiveness of the proposed adaptive stabilization and synchronization control methodologies

  15. Social referencing in dog-owner dyads?

    Science.gov (United States)

    Merola, I; Prato-Previde, E; Marshall-Pescini, S

    2012-03-01

    Social referencing is the seeking of information from another individual to form one's own understanding and guide action. In this study, adult dogs were tested in a social referencing paradigm involving their owner and a potentially scary object. Dogs received either a positive or negative message from the owner. The aim was to evaluate the presence of referential looking to the owner, behavioural regulation based on the owner's (vocal and facial) emotional message and observational conditioning following the owner's actions towards the object. Most dogs (83%) looked referentially to the owner after looking at the strange object, thus they appear to seek information about the environment from the human, but little differences were found between dogs in the positive and negative groups as regards behavioural regulation: possible explanations for this are discussed. Finally, a strong effect of observational conditioning was found with dogs in the positive group moving closer to the fan and dogs in the negative group moving away, both mirroring their owner's behaviour. Results are discussed in relation to studies on human-dog communication, attachment and social learning.

  16. Sliding-mode control combined with improved adaptive feedforward for wafer scanner

    Science.gov (United States)

    Li, Xiaojie; Wang, Yiguang

    2018-03-01

    In this paper, a sliding-mode control method combined with improved adaptive feedforward is proposed for wafer scanner to improve the tracking performance of the closed-loop system. Particularly, In addition to the inverse model, the nonlinear force ripple effect which may degrade the tracking accuracy of permanent magnet linear motor (PMLM) is considered in the proposed method. The dominant position periodicity of force ripple is determined by using the Fast Fourier Transform (FFT) analysis for experimental data and the improved feedforward control is achieved by the online recursive least-squares (RLS) estimation of the inverse model and the force ripple. The improved adaptive feedforward is given in a general form of nth-order model with force ripple effect. This proposed method is motivated by the motion controller design of the long-stroke PMLM and short-stroke voice coil motor for wafer scanner. The stability of the closed-loop control system and the convergence of the motion tracking are guaranteed by the proposed sliding-mode feedback and adaptive feedforward methods theoretically. Comparative experiments on a precision linear motion platform can verify the correctness and effectiveness of the proposed method. The experimental results show that comparing to traditional method the proposed one has better performance of rapidity and robustness, especially for high speed motion trajectory. And, the improvements on both tracking accuracy and settling time can be achieved.

  17. A new approach to adaptive control of manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    An approach in which the manipulator inverse is used as a feedforward controller is employed in the adaptive control of manipulators in order to achieve trajectory tracking by the joint angles. The desired trajectory is applied as an input to the feedforward controller, and the controller output is used as the driving torque for the manipulator. An adaptive algorithm obtained from MRAC theory is used to update the controller gains to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal enhance closed-loop stability and achieve faster adaptation. Simulation results demonstrate the effectiveness of the proposed control scheme for different reference trajectories, and despite large variations in the payload.

  18. Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

    Science.gov (United States)

    Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

    2003-01-01

    An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

  19. Spatial Domain Adaptive Control of Nonlinear Rotary Systems Subject to Spatially Periodic Disturbances

    Directory of Open Access Journals (Sweden)

    Yen-Hsiu Yang

    2012-01-01

    Full Text Available We propose a generic spatial domain control scheme for a class of nonlinear rotary systems of variable speeds and subject to spatially periodic disturbances. The nonlinear model of the rotary system in time domain is transformed into one in spatial domain employing a coordinate transformation with respect to angular displacement. Under the circumstances that measurement of the system states is not available, a nonlinear state observer is established for providing the estimated states. A two-degree-of-freedom spatial domain control configuration is then proposed to stabilize the system and improve the tracking performance. The first control module applies adaptive backstepping with projected parametric update and concentrates on robust stabilization of the closed-loop system. The second control module introduces an internal model of the periodic disturbances cascaded with a loop-shaping filter, which not only further reduces the tracking error but also improves parametric adaptation. The overall spatial domain output feedback adaptive control system is robust to model uncertainties and state estimated error and capable of rejecting spatially periodic disturbances under varying system speeds. Stability proof of the overall system is given. A design example with simulation demonstrates the applicability of the proposed design.

  20. Front tracking based modeling of the solid grain growth on the adaptive control volume grid

    Science.gov (United States)

    Seredyński, Mirosław; Łapka, Piotr

    2017-07-01

    The paper presents the micro-scale model of unconstrained solidification of the grain immersed in under-cooled liquid, based on the front tracking approach. For this length scale, the interface tracked through the domain is meant as the solid-liquid boundary. To prevent generation of huge meshes the energy transport equation is discretized on the adaptive control volume (c.v.) mesh. The coupling of dynamically changing mesh and moving front position is addressed. Preliminary results of simulation of a test case, the growth of single grain, are presented and discussed.

  1. Design of sewage treatment system by applying fuzzy adaptive PID controller

    Science.gov (United States)

    Jin, Liang-Ping; Li, Hong-Chan

    2013-03-01

    In the sewage treatment system, the dissolved oxygen concentration control, due to its nonlinear, time-varying, large time delay and uncertainty, is difficult to establish the exact mathematical model. While the conventional PID controller only works with good linear not far from its operating point, it is difficult to realize the system control when the operating point far off. In order to solve the above problems, the paper proposed a method which combine fuzzy control with PID methods and designed a fuzzy adaptive PID controller based on S7-300 PLC .It employs fuzzy inference method to achieve the online tuning for PID parameters. The control algorithm by simulation and practical application show that the system has stronger robustness and better adaptability.

  2. A technique for improved stability of adaptive feedforward controllers without detailed uncertainty measurements

    International Nuclear Information System (INIS)

    Berkhoff, A P

    2012-01-01

    Model errors in adaptive controllers for the reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. Previous research on active structures with small damping has shown that the addition of a low-authority controller which increases damping in the system may lead to improved performance of an adaptive, high-authority controller. Other researchers have suggested the use of frequency dependent regularization based on measured uncertainties. In this paper an alternative method is presented that avoids the disadvantages of these methods, namely the additional complex hardware and the need to obtain detailed information on the uncertainties. An analysis is made of an adaptive feedforward controller in which a difference exists between the secondary path and the model as used in the controller. The real parts of the eigenvalues that determine the stability of the system are expressed in terms of the amount of uncertainty and the singular values of the secondary path. Modifications of the feedforward control scheme are suggested that aim to improve performance without requiring detailed uncertainty measurements. (paper)

  3. Backstepping-based nonlinear adaptive control for coal-fired utility boiler-turbine units

    International Nuclear Information System (INIS)

    Fang, Fang; Wei, Le

    2011-01-01

    The control system of boiler-turbine unit plays an important role in improving efficiency and reducing emissions of power generation unit. The nonlinear, coupling and uncertainty of the unit caused by varying working conditions should be fully considered during the control system design. This paper presents an efficient control scheme based on backstepping theory for improving load adaptability of boiler-turbines in wide operation range. The design process of the scheme includes model preprocessing, control Lyapunov functions selection, interlaced computation of adaptive control laws, etc. For simplification and accuracy, differential of steam pipe inlet pressure and integral terms of target errors are adopted. Also, to enhance practicality, implementation steps of the scheme are proposed. A practical nonlinear model of a 500 MW coal-fired boiler-turbine unit is used to test the efficiency of the proposed scheme in different conditions.

  4. Effect of Treatment Education Based on the Roy Adaptation Model on Adjustment of Hemodialysis Patients.

    Science.gov (United States)

    Kacaroglu Vicdan, Ayse; Gulseven Karabacak, Bilgi

    2016-01-01

    The Roy Adaptation Model examines the individual in 4 fields: physiological mode, self-concept mode, role function mode, and interdependence mode. Hemodialysis treatment is associated with the Roy Adaptation Model as it involves fields that might be needed by the individual with chronic renal disease. This research was conducted as randomized controlled experiment with the aim of determining the effect of the education given in accordance with the Roy Adaptation Model on physiological, psychological, and social adaptation of individuals undergoing hemodialysis treatment. This was a random controlled experimental study. The study was conducted at a dialysis center in Konya-Aksehir in Turkey between July 1 and December 31, 2012. The sample was composed of 82 individuals-41 experimental and 41 control. In the second interview, there was a decrease in the systolic blood pressures and body weights of the experimental group, an increase in the scores of functional performance and self-respect, and a decrease in the scores of psychosocial adaptation. In the control group, on the other hand, there was a decrease in the scores of self-respect and an increase in the scores of psychosocial adaptation. The 2 groups were compared in terms of adaptation variables and a difference was determined on behalf of the experimental group. The training that was provided and evaluated for individuals receiving hemodialysis according to 4 modes of the Roy Adaptation Model increased physical, psychological, and social adaptation.

  5. Direct adaptive control using feedforward neural networks

    OpenAIRE

    Cajueiro, Daniel Oliveira; Hemerly, Elder Moreira

    2003-01-01

    ABSTRACT: This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the conver...

  6. Adaptive Sliding Mode Control of MEMS AC Voltage Reference Source

    Directory of Open Access Journals (Sweden)

    Ehsan Ranjbar

    2017-01-01

    Full Text Available The accuracy of physical parameters of a tunable MEMS capacitor, as the major part of MEMS AC voltage reference, is of great importance to achieve an accurate output voltage free of the malfunctioning noise and disturbance. Even though strenuous endeavors are made to fabricate MEMS tunable capacitors with desiderated accurate physical characteristics and ameliorate exactness of physical parameters’ values, parametric uncertainties ineluctably emerge in fabrication process attributable to imperfections in micromachining process. First off, this paper considers applying an adaptive sliding mode controller design in the MEMS AC voltage reference source so that it is capable of giving off a well-regulated output voltage in defiance of jumbling parametric uncertainties in the plant dynamics and also aggravating external disturbance imposed on the system. Secondly, it puts an investigatory comparison with the designed model reference adaptive controller and the pole-placement state feedback one into one’s prospective. Not only does the tuned adaptive sliding mode controller show remarkable robustness against slow parameter variation and external disturbance being compared to the pole-placement state feedback one, but also it immensely gets robust against the external disturbance in comparison with the conventional adaptive controller. The simulation results are promising.

  7. Robust Adaptive Stabilization of Linear Time-Invariant Dynamic Systems by Using Fractional-Order Holds and Multirate Sampling Controls

    Directory of Open Access Journals (Sweden)

    S. Alonso-Quesada

    2010-01-01

    Full Text Available This paper presents a strategy for designing a robust discrete-time adaptive controller for stabilizing linear time-invariant (LTI continuous-time dynamic systems. Such systems may be unstable and noninversely stable in the worst case. A reduced-order model is considered to design the adaptive controller. The control design is based on the discretization of the system with the use of a multirate sampling device with fast-sampled control signal. A suitable on-line adaptation of the multirate gains guarantees the stability of the inverse of the discretized estimated model, which is used to parameterize the adaptive controller. A dead zone is included in the parameters estimation algorithm for robustness purposes under the presence of unmodeled dynamics in the controlled dynamic system. The adaptive controller guarantees the boundedness of the system measured signal for all time. Some examples illustrate the efficacy of this control strategy.

  8. L1 Adaptive Manoeuvring Control of Unmanned High-speed Water Craft

    DEFF Research Database (Denmark)

    Svendsen, Casper H.; Holck, Niels Ole; Galeazzi, Roberto

    2012-01-01

    This work addresses the issue of designing an adaptive robust control system to govern the steering of a high speed unmanned personal watercraft (PWC) maintaining equal performance across the craft’s envelope of operation. The maneuvering dynamics of a high speed PWC is presented and a strong var......-of-freedom surge-sway-yaw-roll model. An L1 adaptive autopilot is then designed, which allows to achieve fast adaption to system parameters’ changes and robustness of the closed loop system....

  9. Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server

    Science.gov (United States)

    Du, Bing; Ruan, Chun

    With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.

  10. A novel adaptive force control method for IPMC manipulation

    International Nuclear Information System (INIS)

    Hao, Lina; Sun, Zhiyong; Su, Yunquan; Gao, Jianchao; Li, Zhi

    2012-01-01

    IPMC is a type of electro-active polymer material, also called artificial muscle, which can generate a relatively large deformation under a relatively low input voltage (generally speaking, less than 5 V), and can be implemented in a water environment. Due to these advantages, IPMC can be used in many fields such as biomimetics, service robots, bio-manipulation, etc. Until now, most existing methods for IPMC manipulation are displacement control not directly force control, however, under most conditions, the success rate of manipulations for tiny fragile objects is limited by the contact force, such as using an IPMC gripper to fix cells. Like most EAPs, a creep phenomenon exists in IPMC, of which the generated force will change with time and the creep model will be influenced by the change of the water content or other environmental factors, so a proper force control method is urgently needed. This paper presents a novel adaptive force control method (AIPOF control—adaptive integral periodic output feedback control), based on employing a creep model of which parameters are obtained by using the FRLS on-line identification method. The AIPOF control method can achieve an arbitrary pole configuration as long as the plant is controllable and observable. This paper also designs the POF and IPOF controller to compare their test results. Simulation and experiments of micro-force-tracking tests are carried out, with results confirming that the proposed control method is viable. (paper)

  11. Pilot-Induced Oscillation Suppression by Using 1 Adaptive Control

    Directory of Open Access Journals (Sweden)

    Chuan Wang

    2012-01-01

    research activities that aim to alleviate this problem. In this paper, the L1 adaptive controller has been introduced to suppress the PIO, which is caused by rate limiting and pure time delay. Due to its architecture, the L1 adaptive controller will achieve a desired response with fast adaptation. The analysis of PIO and its suppression by L1 adaptive controller are presented in detail in the paper. The simulation results indicate that the L1 adaptive control is efficient in solving this kind of problem.

  12. Neural adaptive control for vibration suppression in composite fin-tip of aircraft.

    Science.gov (United States)

    Suresh, S; Kannan, N; Sundararajan, N; Saratchandran, P

    2008-06-01

    In this paper, we present a neural adaptive control scheme for active vibration suppression of a composite aircraft fin tip. The mathematical model of a composite aircraft fin tip is derived using the finite element approach. The finite element model is updated experimentally to reflect the natural frequencies and mode shapes very accurately. Piezo-electric actuators and sensors are placed at optimal locations such that the vibration suppression is a maximum. Model-reference direct adaptive neural network control scheme is proposed to force the vibration level within the minimum acceptable limit. In this scheme, Gaussian neural network with linear filters is used to approximate the inverse dynamics of the system and the parameters of the neural controller are estimated using Lyapunov based update law. In order to reduce the computational burden, which is critical for real-time applications, the number of hidden neurons is also estimated in the proposed scheme. The global asymptotic stability of the overall system is ensured using the principles of Lyapunov approach. Simulation studies are carried-out using sinusoidal force functions of varying frequency. Experimental results show that the proposed neural adaptive control scheme is capable of providing significant vibration suppression in the multiple bending modes of interest. The performance of the proposed scheme is better than the H(infinity) control scheme.

  13. Control algorithms and applications of the wavefront sensorless adaptive optics

    Science.gov (United States)

    Ma, Liang; Wang, Bin; Zhou, Yuanshen; Yang, Huizhen

    2017-10-01

    Compared with the conventional adaptive optics (AO) system, the wavefront sensorless (WFSless) AO system need not to measure the wavefront and reconstruct it. It is simpler than the conventional AO in system architecture and can be applied to the complex conditions. Based on the analysis of principle and system model of the WFSless AO system, wavefront correction methods of the WFSless AO system were divided into two categories: model-free-based and model-based control algorithms. The WFSless AO system based on model-free-based control algorithms commonly considers the performance metric as a function of the control parameters and then uses certain control algorithm to improve the performance metric. The model-based control algorithms include modal control algorithms, nonlinear control algorithms and control algorithms based on geometrical optics. Based on the brief description of above typical control algorithms, hybrid methods combining the model-free-based control algorithm with the model-based control algorithm were generalized. Additionally, characteristics of various control algorithms were compared and analyzed. We also discussed the extensive applications of WFSless AO system in free space optical communication (FSO), retinal imaging in the human eye, confocal microscope, coherent beam combination (CBC) techniques and extended objects.

  14. An adaptive robust controller for time delay maglev transportation systems

    Science.gov (United States)

    Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

    2012-12-01

    For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

  15. Robust adaptive control for Unmanned Aerial Vehicles

    Science.gov (United States)

    Kahveci, Nazli E.

    anti-windup compensation. Our analysis on the indirect adaptive scheme reveals that the perturbation terms due to parameter errors do not cause any unbounded signals in the closed-loop. The stability of the adaptive system is established, and the properties of the proposed control scheme are demonstrated through simulations on a UAV model with input magnitude saturation constraints. The robust adaptive control design is further developed to extend our results to rate-saturated systems.

  16. Age Differences in Self-Referencing: Evidence for Common and Distinct Encoding Strategies

    Science.gov (United States)

    Gutchess, Angela H.; Sokal, Rebecca; Coleman, Jennifer A.; Gotthilf, Gina; Grewal, Lauren; Rosa, Nicole

    2014-01-01

    Although engagement of medial prefrontal cortex (MPFC) underlies self-referencing of information for younger and older adults, the region has not consistently been implicated across age groups for the encoding of self-referenced information. We sought to determine whether making judgments about others as well as the self influenced findings in the previous study. During an fMRI session, younger and older adults encoded adjectives using only a self-reference task. For items later remembered compared to those later forgotten, both age groups robustly recruited medial prefrontal cortex, indicating common neural regions support encoding across younger and older adults when participants make only self-reference judgments. Focal age differences emerged in regions related to emotional processing and cognitive control, though these differences are more limited than in tasks in which judgments also are made about others. We conclude that making judgments about another person differently affects the ways that younger and older adults make judgments about the self, with results of a follow-up behavioral study supporting this interpretation. PMID:25223905

  17. The beauty of simple adaptive control and new developments in nonlinear systems stability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Barkana, Itzhak, E-mail: ibarkana@gmail.com [BARKANA Consulting, Ramat Hasharon (Israel)

    2014-12-10

    Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.

  18. Simulation study of multi-step model algorithmic control of the nuclear reactor thermal power tracking system

    International Nuclear Information System (INIS)

    Shi Xiaoping; Xu Tianshu

    2001-01-01

    The classical control method is usually hard to ensure the thermal power tracking accuracy, because the nuclear reactor system is a complex nonlinear system with uncertain parameters and disturbances. A sort of non-parameter model is constructed with the open-loop impulse response of the system. Furthermore, a sort of thermal power tracking digital control law is presented using the multi-step model algorithmic control principle. The control method presented had good tracking performance and robustness. It can work despite the existence of unmeasurable disturbances. The simulation experiment testifies the correctness and effectiveness of the method. The high accuracy matching between the thermal power and the referenced load is achieved

  19. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    OpenAIRE

    Su, Xiaoling; Han, Minxiao; Guerrero, Josep M.; Sun, Hai

    2015-01-01

    This paper presents a microgrid stability controller (MSC) in order to provide existing distributed generation units (DGs) the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics and mathematical models of the MSC indicate that the system is inherently nonlinear and time-variable. Therefore, this paper proposes an adaptive robust total sliding...

  20. Adaptive filters and internal models: multilevel description of cerebellar function.

    Science.gov (United States)

    Porrill, John; Dean, Paul; Anderson, Sean R

    2013-11-01

    Cerebellar function is increasingly discussed in terms of engineering schemes for motor control and signal processing that involve internal models. To address the relation between the cerebellum and internal models, we adopt the chip metaphor that has been used to represent the combination of a homogeneous cerebellar cortical microcircuit with individual microzones having unique external connections. This metaphor indicates that identifying the function of a particular cerebellar chip requires knowledge of both the general microcircuit algorithm and the chip's individual connections. Here we use a popular candidate algorithm as embodied in the adaptive filter, which learns to decorrelate its inputs from a reference ('teaching', 'error') signal. This algorithm is computationally powerful enough to be used in a very wide variety of engineering applications. However, the crucial issue is whether the external connectivity required by such applications can be implemented biologically. We argue that some applications appear to be in principle biologically implausible: these include the Smith predictor and Kalman filter (for state estimation), and the feedback-error-learning scheme for adaptive inverse control. However, even for plausible schemes, such as forward models for noise cancellation and novelty-detection, and the recurrent architecture for adaptive inverse control, there is unlikely to be a simple mapping between microzone function and internal model structure. This initial analysis suggests that cerebellar involvement in particular behaviours is therefore unlikely to have a neat classification into categories such as 'forward model'. It is more likely that cerebellar microzones learn a task-specific adaptive-filter operation which combines a number of signal-processing roles. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Tat-Bao-Thien Nguyen

    2014-01-01

    Full Text Available In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.

  2. Adaptive Engine Torque Compensation with Driveline Model

    Directory of Open Access Journals (Sweden)

    Park Jinrak

    2018-01-01

    Full Text Available Engine net torque is the total torque generated by the engine side, and includes the fuel combustion torque, the friction torque, and additionally the starter motor torque in case of hybrid vehicles. The engine net torque is utilized to control powertrain items such as the engine itself, the transmission clutch, also the engine clutch, and it must be accurate for the precise powertrain control. However, this net torque can vary with the engine operating conditions like the engine wear, the changes of the atmospheric pressure and the friction torque. Thus, this paper proposes the adaptive engine net torque compensator using driveline model which can cope with the net torque change according to engine operating conditions. The adaptive compensator was applied on the parallel hybrid vehicle and investigated via MATLAB Simcape Driveline simulation.

  3. Dynamic Modelling and Adaptive Traction Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    A. Albagul

    2004-09-01

    Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.

  4. Flatness-based adaptive fuzzy control of chaotic finance dynamics

    Science.gov (United States)

    Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.

    2017-11-01

    A flatness-based adaptive fuzzy control is applied to the problem of stabilization of the dynamics of a chaotic finance system, describing interaction between the interest rate, the investment demand and the price exponent. By proving that the system is differentially flat and by applying differential flatness diffeomorphisms, its transformation to the linear canonical (Brunovsky) is performed. For the latter description of the system, the design of a stabilizing state feedback controller becomes possible. A first problem in the design of such a controller is that the dynamic model of the finance system is unknown and thus it has to be identified with the use neurofuzzy approximators. The estimated dynamics provided by the approximators is used in the computation of the control input, thus establishing an indirect adaptive control scheme. The learning rate of the approximators is chosen from the requirement the system's Lyapunov function to have always a negative first-order derivative. Another problem that has to be dealt with is that the control loop is implemented only with the use of output feedback. To estimate the non-measurable state vector elements of the finance system, a state observer is implemented in the control loop. The computation of the feedback control signal requires the solution of two algebraic Riccati equations at each iteration of the control algorithm. Lyapunov stability analysis demonstrates first that an H-infinity tracking performance criterion is satisfied. This signifies elevated robustness against modelling errors and external perturbations. Moreover, the global asymptotic stability is proven for the control loop.

  5. A GPS inspired Terrain Referenced Navigation algorithm

    NARCIS (Netherlands)

    Vaman, D.

    2014-01-01

    Terrain Referenced Navigation (TRN) refers to a form of localization in which measurements of distances to the terrain surface are matched with a digital elevation map allowing a vehicle to estimate its own position within the map. The main goal of this dissertation is to improve TRN performance

  6. Nonlinear discrete-time multirate adaptive control of non-linear vibrations of smart beams

    Science.gov (United States)

    Georgiou, Georgios; Foutsitzi, Georgia A.; Stavroulakis, Georgios E.

    2018-06-01

    The nonlinear adaptive digital control of a smart piezoelectric beam is considered. It is shown that in the case of a sampled-data context, a multirate control strategy provides an appropriate framework in order to achieve vibration regulation, ensuring the stability of the whole control system. Under parametric uncertainties in the model parameters (damping ratios, frequencies, levels of non linearities and cross coupling, control input parameters), the scheme is completed with an adaptation law deduced from hyperstability concepts. This results in the asymptotic satisfaction of the control objectives at the sampling instants. Simulation results are presented.

  7. Finite-time adaptive sliding mode force control for electro-hydraulic load simulator based on improved GMS friction model

    Science.gov (United States)

    Kang, Shuo; Yan, Hao; Dong, Lijing; Li, Changchun

    2018-03-01

    This paper addresses the force tracking problem of electro-hydraulic load simulator under the influence of nonlinear friction and uncertain disturbance. A nonlinear system model combined with the improved generalized Maxwell-slip (GMS) friction model is firstly derived to describe the characteristics of load simulator system more accurately. Then, by using particle swarm optimization (PSO) algorithm ​combined with the system hysteresis characteristic analysis, the GMS friction parameters are identified. To compensate for nonlinear friction and uncertain disturbance, a finite-time adaptive sliding mode control method is proposed based on the accurate system model. This controller has the ability to ensure that the system state moves along the nonlinear sliding surface to steady state in a short time as well as good dynamic properties under the influence of parametric uncertainties and disturbance, which further improves the force loading accuracy and rapidity. At the end of this work, simulation and experimental results are employed to demonstrate the effectiveness of the proposed sliding mode control strategy.

  8. Base isolation technique for tokamak type fusion reactor using adaptive control

    International Nuclear Information System (INIS)

    Koizumi, T.; Tsujiuchi, N.; Kishimoto, F.; Iida, H.; Fujita, T.

    1991-01-01

    In this paper relating to the isolation device of heavy structure such as nuclear fusion reactor, a control rule for reducing the response acceleration and relative displacement simultaneously was formulated, and the aseismic performance was improved by employing the adaptive control method of changing the damping factors of the system adaptively every moment. The control rule was studied by computer simulation, and the aseismic effect was evaluated in an experiment employing a scale model. As a results, the following conclusions were obtained. (1) By employing the control rule presented in this paper, both absolute acceleration and relative displacement can be reduced simultaneously without making the system unstable. (2) By introducing this control rule in a scale model assuming the Tokamak type fusion reactor, the response acceleration can be suppressed down to 78 % and also the relative displacement to 79 % as compared with the conventional aseismic method. (3) The sensitivities of absolute acceleration and relative displacement with respect to the control gain are not equal. However, by employing the relative weighting factor between the absolute acceleration and relative displacement, it is possible to increase the control capability for any kind of objective structures and appliances. (author)

  9. Adaptive change in corporate control practices.

    Science.gov (United States)

    Alexander, J A

    1991-03-01

    Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes.

  10. Characteristics of Criterion-Referenced Instruments: Implications for Materials Selection for the Learning Disabled.

    Science.gov (United States)

    Blasi, Joyce F.

    Discussed are characteristics of criterion referenced reading tests for use with learning disabled (LD) children, and analyzed are the Basic Educational Skills Inventory (BESI), the Prescriptive Reading Inventory (PRI), and the Cooper-McGuire Diagnostic Work-Analysis Test (CooperMcGuire). Criterion referenced tests are defined; and problems in…

  11. A model-based exploration of the role of pattern generating circuits during locomotor adaptation.

    Science.gov (United States)

    Marjaninejad, Ali; Finley, James M

    2016-08-01

    In this study, we used a model-based approach to explore the potential contributions of central pattern generating circuits (CPGs) during adaptation to external perturbations during locomotion. We constructed a neuromechanical modeled of locomotion using a reduced-phase CPG controller and an inverted pendulum mechanical model. Two different forms of locomotor adaptation were examined in this study: split-belt treadmill adaptation and adaptation to a unilateral, elastic force field. For each simulation, we first examined the effects of phase resetting and varying the model's initial conditions on the resulting adaptation. After evaluating the effect of phase resetting on the adaptation of step length symmetry, we examined the extent to which the results from these simple models could explain previous experimental observations. We found that adaptation of step length symmetry during split-belt treadmill walking could be reproduced using our model, but this model failed to replicate patterns of adaptation observed in response to force field perturbations. Given that spinal animal models can adapt to both of these types of perturbations, our findings suggest that there may be distinct features of pattern generating circuits that mediate each form of adaptation.

  12. Linear Perturbation Adaptive Control of Hydraulically Driven Manipulators

    DEFF Research Database (Denmark)

    Andersen, T.O.; Hansen, M.R.; Conrad, Finn

    2004-01-01

    control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each......A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...

  13. The ADaptation and Anticipation Model (ADAM) of sensorimotor synchronization

    Science.gov (United States)

    van der Steen, M. C. (Marieke); Keller, Peter E.

    2013-01-01

    A constantly changing environment requires precise yet flexible timing of movements. Sensorimotor synchronization (SMS)—the temporal coordination of an action with events in a predictable external rhythm—is a fundamental human skill that contributes to optimal sensory-motor control in daily life. A large body of research related to SMS has focused on adaptive error correction mechanisms that support the synchronization of periodic movements (e.g., finger taps) with events in regular pacing sequences. The results of recent studies additionally highlight the importance of anticipatory mechanisms that support temporal prediction in the context of SMS with sequences that contain tempo changes. To investigate the role of adaptation and anticipatory mechanisms in SMS we introduce ADAM: an ADaptation and Anticipation Model. ADAM combines reactive error correction processes (adaptation) with predictive temporal extrapolation processes (anticipation) inspired by the computational neuroscience concept of internal models. The combination of simulations and experimental manipulations based on ADAM creates a novel and promising approach for exploring adaptation and anticipation in SMS. The current paper describes the conceptual basis and architecture of ADAM. PMID:23772211

  14. Adaptive control of chaotic systems with stochastic time varying unknown parameters

    Energy Technology Data Exchange (ETDEWEB)

    Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

    2008-10-15

    In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.

  15. Feedback control and adaptive control of the energy resource chaotic system

    International Nuclear Information System (INIS)

    Sun Mei; Tian Lixin; Jiang Shumin; Xu Jun

    2007-01-01

    In this paper, the problem of control for the energy resource chaotic system is considered. Two different method of control, feedback control (include linear feedback control, non-autonomous feedback control) and adaptive control methods are used to suppress chaos to unstable equilibrium or unstable periodic orbits. The Routh-Hurwitz criteria and Lyapunov direct method are used to study the conditions of the asymptotic stability of the steady states of the controlled system. The designed adaptive controller is robust with respect to certain class of disturbances in the energy resource chaotic system. Numerical simulations are presented to show these results

  16. Numbering of vertebrae on MRI using a PACS cross-referencing tool

    International Nuclear Information System (INIS)

    Paik, Nam Chull; Lim, Chun Soo; Jang, Ho Suk

    2012-01-01

    Background: For the detection and documentation of numeric variations on spine magnetic resonance imaging (MRI), different techniques have previously been introduced. However, these methods require additional special imaging algorithms, software, or devices. We intend to introduce a vertebral numbering method using the existing picture archiving and communication system (PACS) and MRI system. Purpose: To assess the accuracy of a method for numbering presacral vertebrae based on the cross-referencing of two sagittal MRI series. Material and Methods: This study was a retrospective review of 224 consecutive patients who underwent both lumbar MRI with cervicothoracic scan and whole spine radiographic examinations. A radiologist and a neurosurgeon independently counted the number of presacral vertebrae in a cranial-to-caudal approach with cross-referencing of cervicothoracic and lumbar MRI sagittal series on the PACS workstation. Radiographic numbering from the cervical through the thoracic to the lumbar vertebrae, as a reference standard, was completed independently by the two reviewers. An analysis of the inter-observer and intermodality agreements of radiography and MRI was done. Results: In all cases except one, concordant numbering existed between the two modalities of MRI cross-referencing and radiographs combination. Both observers agreed completely, with no inter-observer discordance. Conclusion: The number of vertebrae could be identified consistently by counting caudally from C2 with cross-referencing cervicothoracic and lumbosacral sagittal MRI scans on the PACS workstation

  17. Numbering of vertebrae on MRI using a PACS cross-referencing tool

    Energy Technology Data Exchange (ETDEWEB)

    Paik, Nam Chull [Dept. of Radiology, Arumdaun Wooldul Spine Hospital, Ulsan (Korea, Republic of)], e-mail: srsna@freechal.com; Lim, Chun Soo; Jang, Ho Suk [Dept. of Neurosurgery, Arumdaun Wooldul Spine Hospital, Ulsan (Korea, Republic of)

    2012-09-15

    Background: For the detection and documentation of numeric variations on spine magnetic resonance imaging (MRI), different techniques have previously been introduced. However, these methods require additional special imaging algorithms, software, or devices. We intend to introduce a vertebral numbering method using the existing picture archiving and communication system (PACS) and MRI system. Purpose: To assess the accuracy of a method for numbering presacral vertebrae based on the cross-referencing of two sagittal MRI series. Material and Methods: This study was a retrospective review of 224 consecutive patients who underwent both lumbar MRI with cervicothoracic scan and whole spine radiographic examinations. A radiologist and a neurosurgeon independently counted the number of presacral vertebrae in a cranial-to-caudal approach with cross-referencing of cervicothoracic and lumbar MRI sagittal series on the PACS workstation. Radiographic numbering from the cervical through the thoracic to the lumbar vertebrae, as a reference standard, was completed independently by the two reviewers. An analysis of the inter-observer and intermodality agreements of radiography and MRI was done. Results: In all cases except one, concordant numbering existed between the two modalities of MRI cross-referencing and radiographs combination. Both observers agreed completely, with no inter-observer discordance. Conclusion: The number of vertebrae could be identified consistently by counting caudally from C2 with cross-referencing cervicothoracic and lumbosacral sagittal MRI scans on the PACS workstation.

  18. Rotor Field Oriented Control with adaptive Iron Loss Compensation

    DEFF Research Database (Denmark)

    Rasmussen, Henrik; Vadstrup, P.; Børsting, H.

    1999-01-01

    of the motor referenced to the rotor magnetizing current, and with the extension of an iron loss resistor added in parallel to the magnetizing inductance. The resistor estimator is based on the observation that the actual applied stator voltages deviates from the voltage estimated, when a motor is current......It is well known from the literature that iron loses in an induction motor implies field angle estimation errors and hence detuning problems. In this paper a new method for estimating the iron loss resistor in an induction motor is presented. The method is based on a traditional dynamic model...

  19. Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

    Science.gov (United States)

    Mai, Huanhuan; Song, Gangbing; Liao, Xiaofeng

    2013-01-01

    Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller.

  20. Design and Modeling of an Adaptively Controlled Rainwater Harvesting System

    Directory of Open Access Journals (Sweden)

    David Roman

    2017-12-01

    Full Text Available Management of urban stormwater to mitigate Combined Sewer Overflows (CSOs is a priority for many cities; yet, few truly innovative approaches have been proposed to address the problem. Recent advances in information technology are now, however, providing cost-effective opportunities to achieve better performance of conventional stormwater infrastructure through a Continuous Monitoring and Adaptive Control (CMAC approach. The primary objective of this study was to demonstrate that a CMAC approach can be applied to a conventional rainwater harvesting system in New York City to improve performance by minimizing discharge to the combined sewer during rainfall events, reducing water use for irrigation of local vegetation, and optimizing vegetation health. To achieve this objective, a hydrologic and hydraulic model was developed for a planned and designed rainwater harvesting system to explore multiple potential scenarios prior to the system’s actual construction. Model results indicate that the CMAC rainwater harvesting system is expected to provide significant performance improvements over conventional rainwater harvesting systems. The CMAC system is expected to capture and retain 76.6% of roof runoff per year on average, as compared to just 14.8% and 41.3% for conventional moisture and timer based systems, respectively. Similarly, the CMAC system is expected to use 81.4% and 18.0% less harvested rainwater than conventional moisture and timer based irrigation approaches, respectively. The flexibility of the CMAC approach to meet competing objectives is promising for widespread implementation in New York City and other heavily urbanized areas challenged by stormwater management issues.

  1. Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.

    Science.gov (United States)

    Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo

    2017-03-01

    In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.

  2. Electronics. Criterion-Referenced Test (CRT) Item Bank.

    Science.gov (United States)

    Davis, Diane, Ed.

    This document contains 519 criterion-referenced multiple choice and true or false test items for a course in electronics. The test item bank is designed to work with both the Vocational Instructional Management System (VIMS) and the Vocational Administrative Management System (VAMS) in Missouri. The items are grouped into 15 units covering the…

  3. Adaptive fuzzy control for a simulation of hydraulic analogy of a nuclear reactor

    International Nuclear Information System (INIS)

    Ruan, D.; Li, X.; Eynde, G. van den

    2000-01-01

    In the framework of the on-going R and D project on fuzzy control applications to the Belgian Reactor 1 (BR1) at the Belgian Nuclear Research Centre (SCK-CEN), we have constructed a real fuzzy-logic-control demo model. The demo model is suitable for us to test and compare some new algorithms of fuzzy control and intelligent systems, which is advantageous because it is always difficult and time consuming, due to safety aspects, to do all experiments in a real nuclear environment. In this chapter, we first report briefly on the construction of the demo model, and then introduce the results of a fuzzy control, a proportional-integral-derivative (PID) control and an advanced fuzzy control, in which the advanced fuzzy control is a fuzzy control with an adaptive function that can self-regulate the fuzzy control rules. Afterwards, we present a comparative study of those three methods. The results have shown that fuzzy control has more advantages in terms of flexibility, robustness, and easily updated facilities with respect to the PID control of the demo model, but that PID control has much higher regulation resolution due to its integration terms. The adaptive fuzzy control can dynamically adjust the rule base, therefore it is more robust and suitable to those very uncertain occasions. (orig.)

  4. Adaptive Superheat Control of a Refrigeration Plant using Backstepping

    DEFF Research Database (Denmark)

    Rasmussen, Henrik

    2008-01-01

    This paper proposes a novel method for superheat and capacity control of refrigeration systems. The new idea is to control the superheat by the compressor speed and capacity by the refrigerant flow. This gives a highly nonlinear transfer operator from compressor speed input to the superheat output....... A new low order nonlinear model of the evaporator is developed and used in a backstepping design of an adaptive nonlinear controller.  The stability of the proposed method is validated theoretically by Lyapunov analysis and experimental results shows the performance of the system for a wide range...

  5. A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance Model

    Science.gov (United States)

    Mathe, Nathalie; Chen, James

    1994-01-01

    Rapid and effective to information in large electronic documentation systems can be facilitated if information relevant in an individual user's content can be automatically supplied to this user. However most of this knowledge on contextual relevance is not found within the contents of documents, it is rather established incrementally by users during information access. We propose a new model for interactively learning contextual relevance during information retrieval, and incrementally adapting retrieved information to individual user profiles. The model, called a relevance network, records the relevance of references based on user feedback for specific queries and user profiles. It also generalizes such knowledge to later derive relevant references for similar queries and profiles. The relevance network lets users filter information by context of relevance. Compared to other approaches, it does not require any prior knowledge nor training. More importantly, our approach to adaptivity is user-centered. It facilitates acceptance and understanding by users by giving them shared control over the adaptation without disturbing their primary task. Users easily control when to adapt and when to use the adapted system. Lastly, the model is independent of the particular application used to access information, and supports sharing of adaptations among users.

  6. Development of Adaptive Acoustic Impedance Control Technologies of Acoustic Duct Liner

    Directory of Open Access Journals (Sweden)

    Hiroshi Kobayashi

    2011-01-01

    Full Text Available This paper describes the development of adaptive acoustic impedance control (AAC technologies to achieve a larger fan noise reduction, by adaptively adjusting reactance and resistance of the acoustic liner impedance. For the actual proof of the AAC technology III performance, the advanced fan noise absorption control duct liner II was made on trial basis, with the simple control system and the plain device. And, then, the duct liner II was examined for the AAC technology I, II, and III models, using the high speed fan test facility. The test results made clear that the duct liner II of the AAC technology III model could achieve the fan noise reduction higher than O.A. SPL 10 dB (A at the maximum fan speed 6000 rpm, containing the reduction of fundamental BPF tone of 18 dB and 2nd BPF tone of 10 dB in response to the fan peed change from 3000 to 6000 rpm.

  7. Adaptation of the MAST passive current simulation model for real-time plasma control

    International Nuclear Information System (INIS)

    McArdle, G.J.; Taylor, D.

    2008-01-01

    Successful equilibrium reconstruction on MAST depends on a reliable estimate of the passive current induced in the thick vacuum vessel (which also acts as the load assembly) and other toroidally continuous internal support structures. For the EFIT reconstruction code, a pre-processing program takes the measured plasma and PF coil current evolution and uses a sectional model of the passive structure to solve the ODEs for electromagnetic induction. The results are written to a file, which is treated by EFIT as a set of virtual measurements of the passive current in each section. However, when a real-time version of EFIT was recently installed in the MAST plasma control system, a similar function was required for real-time estimation of the instantaneous passive current. This required several adaptation steps for the induction model to reduce the computational overhead to the absolute minimum, whilst preserving accuracy of the result. These include: ·conversion of the ODE to use an auxiliary variable, avoiding the need to calculate the time derivative of current; ·minimise the order of the system via model reduction techniques with a state-space representation of the problem; ·transformation to eigenmode form, to diagonalise the main matrix for faster computation; ·discretisation of the ODE; ·hand-optimisation to use vector instruction extensions in the real-time processor; ·splitting the task into two parts: the time-critical feedback part, and the next cycle pre-calculation part. After these optimisations, the algorithm was successfully implemented at a cost of just 65 μs per 500 μs control cycle, with only 27 μs added to the control latency. The results show good agreement with the original off-line version. Some of these optimisations have also been used subsequently to improve the performance of the off-line version

  8. UAV Controller Based on Adaptive Neuro-Fuzzy Inference System and PID

    Directory of Open Access Journals (Sweden)

    Ali Moltajaei Farid

    2013-01-01

    Full Text Available ANFIS is combining a neural network with a fuzzy system results in a hybrid neuro-fuzzy system, capable of reasoning and learning in an uncertain and imprecise environment. In this paper, an adaptive neuro-fuzzy inference system (ANFIS is employed to control an unmanned aircraft vehicle (UAV.  First, autopilots structure is defined, and then ANFIS controller is applied, to control UAVs lateral position. The results of ANFIS and PID lateral controllers are compared, where it shows the two controllers have similar results. ANFIS controller is capable to adaptation in nonlinear conditions, while PID has to be tuned to preserves proper control in some conditions. The simulation results generated by Matlab using Aerosim Aeronautical Simulation Block Set, which provides a complete set of tools for development of six degree-of-freedom. Nonlinear Aerosonde unmanned aerial vehicle model with ANFIS controller is simulated to verify the capability of the system. Moreover, the results are validated by FlightGear flight simulator.

  9. A stage structure pest management model with impulsive state feedback control

    Science.gov (United States)

    Pang, Guoping; Chen, Lansun; Xu, Weijian; Fu, Gang

    2015-06-01

    A stage structure pest management model with impulsive state feedback control is investigated. We get the sufficient condition for the existence of the order-1 periodic solution by differential equation geometry theory and successor function. Further, we obtain a new judgement method for the stability of the order-1 periodic solution of the semi-continuous systems by referencing the stability analysis for limit cycles of continuous systems, which is different from the previous method of analog of Poincarè criterion. Finally, we analyze numerically the theoretical results obtained.

  10. An adaptation model for trabecular bone at different mechanical levels

    Directory of Open Access Journals (Sweden)

    Lv Linwei

    2010-07-01

    Full Text Available Abstract Background Bone has the ability to adapt to mechanical usage or other biophysical stimuli in terms of its mass and architecture, indicating that a certain mechanism exists for monitoring mechanical usage and controlling the bone's adaptation behaviors. There are four zones describing different bone adaptation behaviors: the disuse, adaptation, overload, and pathologic overload zones. In different zones, the changes of bone mass, as calculated by the difference between the amount of bone formed and what is resorbed, should be different. Methods An adaptation model for the trabecular bone at different mechanical levels was presented in this study based on a number of experimental observations and numerical algorithms in the literature. In the proposed model, the amount of bone formation and the probability of bone remodeling activation were proposed in accordance with the mechanical levels. Seven numerical simulation cases under different mechanical conditions were analyzed as examples by incorporating the adaptation model presented in this paper with the finite element method. Results The proposed bone adaptation model describes the well-known bone adaptation behaviors in different zones. The bone mass and architecture of the bone tissue within the adaptation zone almost remained unchanged. Although the probability of osteoclastic activation is enhanced in the overload zone, the potential of osteoblasts to form bones compensate for the osteoclastic resorption, eventually strengthening the bones. In the disuse zone, the disuse-mode remodeling removes bone tissue in disuse zone. Conclusions The study seeks to provide better understanding of the relationships between bone morphology and the mechanical, as well as biological environments. Furthermore, this paper provides a computational model and methodology for the numerical simulation of changes of bone structural morphology that are caused by changes of mechanical and biological

  11. Nonlinear adaptive robust back stepping force control of hydraulic load simulator: Theory and experiments

    International Nuclear Information System (INIS)

    Yao, Jianyong; Jiao, Zongxia; Yao, Bin

    2014-01-01

    High performance robust force control of hydraulic load simulator with constant but unknown hydraulic parameters is considered. In contrast to the linear control based on hydraulic linearization equations, hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative (PID) control not yield to high performance requirements. Furthermore, the hydraulic system may be subjected to non-smooth and discontinuous nonlinearities due to the directional change of valve opening. In this paper, based on a nonlinear system model of hydraulic load simulator, a discontinuous projection-based nonlinear adaptive robust back stepping controller is developed with servo valve dynamics. The proposed controller constructs a novel stable adaptive controller and adaptation laws with additional pressure dynamic related unknown parameters, which can compensate for the system nonlinearities and uncertain parameters, meanwhile a well-designed robust controller is also synthesized to dominate the model uncertainties coming from both parametric uncertainties and uncertain nonlinearities including unmodeled and ignored system dynamics. The controller theoretically guarantee a prescribed transient performance and final tracking accuracy in presence of both parametric uncertainties and uncertain nonlinearities; while achieving asymptotic output tracking in the absence of unstructured uncertainties. The implementation issues are also discussed for controller simplification. Some comparative results are obtained to verify the high-performance nature of the proposed controller.

  12. Nonlinear adaptive robust back stepping force control of hydraulic load simulator: Theory and experiments

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Jianyong [Nanjing University of Science and Technology, Nanjing (China); Jiao, Zongxia [Beihang University, Beijing (China); Yao, Bin [Purdue University, West Lafayette (United States)

    2014-04-15

    High performance robust force control of hydraulic load simulator with constant but unknown hydraulic parameters is considered. In contrast to the linear control based on hydraulic linearization equations, hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative (PID) control not yield to high performance requirements. Furthermore, the hydraulic system may be subjected to non-smooth and discontinuous nonlinearities due to the directional change of valve opening. In this paper, based on a nonlinear system model of hydraulic load simulator, a discontinuous projection-based nonlinear adaptive robust back stepping controller is developed with servo valve dynamics. The proposed controller constructs a novel stable adaptive controller and adaptation laws with additional pressure dynamic related unknown parameters, which can compensate for the system nonlinearities and uncertain parameters, meanwhile a well-designed robust controller is also synthesized to dominate the model uncertainties coming from both parametric uncertainties and uncertain nonlinearities including unmodeled and ignored system dynamics. The controller theoretically guarantee a prescribed transient performance and final tracking accuracy in presence of both parametric uncertainties and uncertain nonlinearities; while achieving asymptotic output tracking in the absence of unstructured uncertainties. The implementation issues are also discussed for controller simplification. Some comparative results are obtained to verify the high-performance nature of the proposed controller.

  13. Adaptive Controller Design for Continuous Stirred Tank Reactor

    OpenAIRE

    K. Prabhu; V. Murali Bhaskaran

    2014-01-01

    Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of C...

  14. Fuzzy model-based adaptive synchronization of time-delayed chaotic systems

    International Nuclear Information System (INIS)

    Vasegh, Nastaran; Majd, Vahid Johari

    2009-01-01

    In this paper, fuzzy model-based synchronization of a class of first order chaotic systems described by delayed-differential equations is addressed. To design the fuzzy controller, the chaotic system is modeled by Takagi-Sugeno fuzzy system considering the properties of the nonlinear part of the system. Assuming that the parameters of the chaotic system are unknown, an adaptive law is derived to estimate these unknown parameters, and the stability of error dynamics is guaranteed by Lyapunov theory. Numerical examples are given to demonstrate the validity of the proposed adaptive synchronization approach.

  15. Projection-Based Adaptive Backstepping Control of a Transport Aircraft for Heavyweight Airdrop

    Directory of Open Access Journals (Sweden)

    Ri Liu

    2015-01-01

    Full Text Available An autopilot inner loop that combines backstepping control with adaptive function approximation is developed for airdrop operations. The complex nonlinear uncertainty of the aircraft-cargo model is factorized into a known matrix and an uncertainty function, and a projection-based adaptive approach is proposed to estimate this function. Using projection in the adaptation law bounds the estimated function and guarantees the robustness of the controller against time-varying external disturbances and uncertainties. The convergence properties and robustness of the control method are proved via Lyapunov theory. Simulations are conducted under the condition that one transport aircraft performs a maximum load airdrop task at a height of 82 ft, using single row single platform mode. The results show good performance and robust operation of the controller, and the airdrop mission performance indexes are satisfied, even in the presence of ±15% uncertainty in the aerodynamic coefficients, ±0.01 rad/s pitch rate disturbance, and 20% actuators faults.

  16. Adaptive neuro-fuzzy controller of switched reluctance motor

    Directory of Open Access Journals (Sweden)

    Tahour Ahmed

    2007-01-01

    Full Text Available This paper presents an application of adaptive neuro-fuzzy (ANFIS control for switched reluctance motor (SRM speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. The results of applying the adaptive neuro-fuzzy controller to a SRM give better performance and high robustness than those obtained by the application of a conventional controller (PI.

  17. Robustness study of the pseudo open-loop controller for multiconjugate adaptive optics.

    Science.gov (United States)

    Piatrou, Piotr; Gilles, Luc

    2005-02-20

    Robustness of the recently proposed "pseudo open-loop control" algorithm against various system errors has been investigated for the representative example of the Gemini-South 8-m telescope multiconjugate adaptive-optics system. The existing model to represent the adaptive-optics system with pseudo open-loop control has been modified to account for misalignments, noise and calibration errors in deformable mirrors, and wave-front sensors. Comparison with the conventional least-squares control model has been done. We show with the aid of both transfer-function pole-placement analysis and Monte Carlo simulations that POLC remains remarkably stable and robust against very large levels of system errors and outperforms in this respect least-squares control. Approximate stability margins as well as performance metrics such as Strehl ratios and rms wave-front residuals averaged over a 1-arc min field of view have been computed for different types and levels of system errors to quantify the expected performance degradation.

  18. Effect of Roy's Adaptation Model-Guided Education on Coping Strategies of the Veterans with Lower Extremities Amputation: A Double-Blind Randomized Controlled Clinical Trial.

    Science.gov (United States)

    Farsi, Zahra; Azarmi, Somayeh

    2016-04-01

    Any defect in the extremities of the body can affect different life aspects. The purpose of this study was to investigate the effect of Roy's adaptation model-guided education on coping strategies of the veterans with lower extremities amputation. In a double-blind randomized controlled clinical trial, 60 veterans with lower extremities amputation referring to Kowsar Orthotics and Prosthetics Center of Veterans Clinic in Tehran, Iran were recruited using convenience method and randomly assigned to intervention and control groups in 2013-2014. Lazarus and Folkman coping strategies questionnaire was used to collect the data. After completing the questionnaires in both groups, maladaptive behaviours were determined in the intervention group and an education program based on Roy's adaptation model was implemented. After 2 months, both groups completed the questionnaires again. Data were analyzed using SPSS software. Independent T-test showed that the score of the dimensions of coping strategies did not have a statistically significant difference between the intervention and control groups in the pre-intervention stage (P>0.05). This test showed a statistically significant difference between the two groups in the post-intervention stage in terms of the scores of different dimensions of coping strategies (P>0.05), except in dimensions of social support seeking and positive appraisal (P>0.05). The findings of this research indicated that the Roy's adaptation model-guided education improved the majority of coping strategies in veterans with lower extremities amputation. It is recommended that further interventions based on Roy's adaptation model should be performed to improve the coping of the veterans with lower extremities amputation. IRCT2014081118763N1.

  19. Explicit MPC design and performance-based tuning of an Adaptive Cruise Control Stop-&-Go

    NARCIS (Netherlands)

    Naus, G.J.L.; Ploeg, J.; Molengraft, M.J.G. van de; Steinbuch, M.

    2008-01-01

    This paper presents the synthesis, the implementation and the performance-based tuning of an Adaptive Cruise Control (ACC) Stop-&-Go (S&G) design. A Model Predictive Control (MPC) framework is adopted to design the controller. Performance of the controller is evaluated, distinguishing between

  20. Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

    International Nuclear Information System (INIS)

    Mai, Huanhuan; Liao, Xiaofeng; Song, Gangbing

    2013-01-01

    Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller. (paper)

  1. Adaptive control of bifurcation and chaos in a time-delayed system

    International Nuclear Information System (INIS)

    Li Ning; Zhang Qing-Ling; Yuan Hui-Qun; Sun Hai-Yi

    2013-01-01

    In this paper, the stabilization of a continuous time-delayed system is considered. To control the bifurcation and chaos in a time-delayed system, a parameter perturbation control and a hybrid control are proposed. Then, to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes, the adaptive control idea is introduced, i.e., the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws, respectively. The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem. The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods. They have the advantages of increased stability, adaptability to the changes of the system parameters, control cost saving, and simplicity. Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods. A comparison of the two adaptive control methods is also made in an experimental study

  2. Self-referenced memory, social cognition, and symptom presentation in autism.

    Science.gov (United States)

    Henderson, Heather A; Zahka, Nicole E; Kojkowski, Nicole M; Inge, Anne P; Schwartz, Caley B; Hileman, Camilla M; Coman, Drew C; Mundy, Peter C

    2009-07-01

    We examined performance on a self-referenced memory (SRM) task for higher-functioning children with autism (HFA) and a matched comparison group. SRM performance was examined in relation to symptom severity and social cognitive tests of mentalizing. Sixty-two children (31 HFA, 31 comparison; 8-16 years) completed a SRM task in which they read a list of words and decided whether the word described something about them, something about Harry Potter, or contained a certain number of letters. They then identified words that were familiar from a longer list. Dependent measures were memory performance (d') in each of the three encoding conditions as well as a self-memory bias score (d' self-d' other). Children completed The Strange Stories Task and The Children's Eyes Test as measures of social cognition. Parents completed the SCQ and ASSQ as measures of symptom severity. Children in the comparison sample showed the standard SRM effect in which they recognized significantly more self-referenced words relative to words in the other-referenced and letter conditions. In contrast, HFA children showed comparable rates of recognition for self- and other-referenced words. For all children, SRM performance improved with age and enhanced SRM performance was related to lower levels of social problems. These associations were not accounted for by performance on the mentalizing tasks. Children with HFA did not show the standard enhanced processing of self- vs. other-relevant information. Individual differences in the tendency to preferentially process self-relevant information may be associated with social cognitive processes that serve to modify the expression of social symptoms in children with autism.

  3. Controlling chaos based on an adaptive adjustment mechanism

    International Nuclear Information System (INIS)

    Zheng Yongai

    2006-01-01

    In this paper, we extend the ideas and techniques developed by Huang [Huang W. Stabilizing nonlinear dynamical systems by an adaptive adjustment mechanism. Phys Rev E 2000;61:R1012-5] for controlling discrete-time chaotic system using adaptive adjustment mechanism to continuous-time chaotic system. Two control approaches, namely adaptive adjustment mechanism (AAM) and modified adaptive adjustment mechanism (MAAM), are investigated. In both case sufficient conditions for the stabilization of chaotic systems are given analytically. The simulation results on Chen chaotic system have verified the effectiveness of the proposed techniques

  4. Stabilizing periodic orbits of chaotic systems using fuzzy adaptive sliding mode control

    Energy Technology Data Exchange (ETDEWEB)

    Layeghi, Hamed [Department of Mechanical Engineering, Sharif University of Technology, Center of Excellence in Design, Robotics and Automation, Azadi Avenue, Postal Code 11365-9567 Tehran (Iran, Islamic Republic of)], E-mail: layeghi@mech.sharif.edu; Arjmand, Mehdi Tabe [Department of Mechanical Engineering, Sharif University of Technology, Center of Excellence in Design, Robotics and Automation, Azadi Avenue, Postal Code 11365-9567 Tehran (Iran, Islamic Republic of)], E-mail: arjmand@mech.sharif.edu; Salarieh, Hassan [Department of Mechanical Engineering, Sharif University of Technology, Center of Excellence in Design, Robotics and Automation, Azadi Avenue, Postal Code 11365-9567 Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Department of Mechanical Engineering, Sharif University of Technology, Center of Excellence in Design, Robotics and Automation, Azadi Avenue, Postal Code 11365-9567 Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

    2008-08-15

    In this paper by using a combination of fuzzy identification and the sliding mode control a fuzzy adaptive sliding mode scheme is designed to stabilize the unstable periodic orbits of chaotic systems. The chaotic system is assumed to have an affine form x{sup (n)} = f(X) + g(X)u where f and g are unknown functions. Using only the input-output data obtained from the underlying dynamical system, two fuzzy systems are constructed for identification of f and g. Two distinct methods are utilized for fuzzy modeling, the least squares and the gradient descent techniques. Based on the estimated fuzzy models, an adaptive controller, which works through the sliding mode control, is designed to make the system track the desired unstable periodic orbits. The stability analysis of the overall closed loop system is presented in the paper and the effectiveness of the proposed adaptive scheme is numerically investigated. As a case of study, modified Duffing system is selected for applying the proposed method to stabilize its 2{pi} and 4{pi} periodic orbits. Simulation results show the high performance of the method for stabilizing the unstable periodic orbits of unknown chaotic systems.

  5. Connection adaption for control of networked mobile chaotic agents.

    Science.gov (United States)

    Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Xiao, Gaoxi; Boccaletti, S

    2017-11-22

    In this paper, we propose a strategy for the control of mobile chaotic oscillators by adaptively rewiring connections between nearby agents with local information. In contrast to the dominant adaptive control schemes where coupling strength is adjusted continuously according to the states of the oscillators, our method does not request adaption of coupling strength. As the resulting interaction structure generated by this proposed strategy is strongly related to unidirectional chains, by investigating synchronization property of unidirectional chains, we reveal that there exists a certain coupling range in which the agents could be controlled regardless of the length of the chain. This feature enables the adaptive strategy to control the mobile oscillators regardless of their moving speed. Compared with existing adaptive control strategies for networked mobile agents, our proposed strategy is simpler for implementation where the resulting interaction networks are kept unweighted at all time.

  6. Adaptive learning fuzzy control of a mobile robot

    International Nuclear Information System (INIS)

    Tsukada, Akira; Suzuki, Katsuo; Fujii, Yoshio; Shinohara, Yoshikuni

    1989-11-01

    In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)

  7. Adaptive mechanism-based congestion control for networked systems

    Science.gov (United States)

    Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

    2013-03-01

    In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

  8. Active vibration control for piezoelectricity cantilever beam: an adaptive feedforward control method

    Science.gov (United States)

    Zhu, Qiao; Yue, Jun-Zhou; Liu, Wei-Qun; Wang, Xu-Dong; Chen, Jun; Hu, Guang-Di

    2017-04-01

    This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Due to that the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is employed to put an equivalent disturbance into the input channel. In this situation, the vibration control can be achieved by setting the control input be the identified EID. Then, for the EID with known multiple frequencies, the AFC is introduced to perfectly reject the vibration but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of EID in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis (TFA) method is employed to precisely identify the unknown frequencies. Consequently, a TFA-based AFC algorithm is proposed to the active vibration control with unknown frequencies. Finally, four cases are given to illustrate the efficiency of the proposed TFA-based AFC algorithm by experiment.

  9. ADEX optimized adaptive controllers and systems from research to industrial practice

    CERN Document Server

    Martín-Sánchez, Juan M

    2015-01-01

    This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...

  10. AN ALGORITHM OF ADAPTIVE TORQUE CONTROL IN INJECTOR INTERNAL COMBUSTION ENGINE

    Directory of Open Access Journals (Sweden)

    D. N. Gerasimov

    2015-07-01

    Full Text Available Subject of Research. Internal combustion engine as a plant is a highly nonlinear complex system that works mostly in dynamic regimes in the presence of noise and disturbances. A number of engine characteristics and parameters is not known or known approximately due to the complex structure and multimode operating of the engine. In this regard the problem of torque control is not trivial and motivates the use of modern techniques of control theory that give the possibility to overcome the mentioned problems. As a consequence, a relatively simple algorithm of adaptive torque control of injector engine is proposed in the paper. Method. Proposed method is based on nonlinear dynamic model with parametric and functional uncertainties (static characteristics which are suppressed by means of adaptive control algorithm with single adjustable parameter. The algorithm is presented by proportional control law with adjustable feedback gain and provides the exponential convergence of the control error to the neighborhood of zero equilibrium. It is shown that the radius of the neighborhood can be arbitrary reduced by the change of controller design parameters. Main Results. A dynamical nonlinear model of the engine has been designed for the purpose of control synthesis and simulation of the closed-loop system. The parameters and static functions of the model are identified with the use of data aquired during Federal Test Procedure (USA of Chevrolet Tahoe vehicle with eight cylinders 5,7L engine. The algorithm of adaptive torque control is designed, and the properties of the closed-loop system are analyzed with the use of Lyapunov functions approach. The closed-loop system operating is verified by means of simulation in the MatLab/Simulink environment. Simulation results show that the controller provides the boundedness of all signals and convergence of the control error to the neighborhood of zero equilibrium despite significant variations of engine speed. The

  11. Robust Adaptive Speed Control of Induction Motor Drives

    DEFF Research Database (Denmark)

    Bidstrup, N.

    , (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...... adaptive speed control of the CVC drive. A direct truly adaptive speed controller has been implemented. The adaptive controller is a moving Average Self-Tuning Regulator which is abbreviated MASTR throughout the thesis. Two practical implementations of this controller were proposed. They were denoted MASTR...... and measurement noise in general, were the major reasons for the drifting parameters. Two approaches was proposed to robustify MASTR2 against the output noise. The first approach consists of filtering the output. Output filtering had a significant effect in simulations, but the robustness against the output noise...

  12. Adaptive Control Methods for Soft Robots

    Data.gov (United States)

    National Aeronautics and Space Administration — I propose to develop methods for soft and inflatable robots that will allow the control system to adapt and change control parameters based on changing conditions...

  13. Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control

    Science.gov (United States)

    Eshak, Peter B.

    Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID to estimate and update the controller parameter. Finally, a new controller design was introduced, which integrated both direct and indirect control laws. This controller is known as hybrid adaptive controller. This last control design outperformed the two earlier designs in terms of less NNs effort and better tracking quality. The performance of online PID has an important role in the quality of the hybrid controller; therefore, the quality of the estimation will be of a great importance. Unfortunately, PID is not perfect and the online estimation process has some inherited issues; the online PID estimates are primarily affected by delays and biases. In order to ensure updating reliable estimates to the controller, the estimator consumes some time to converge. Moreover, the estimator will often converge to a biased value. This thesis conducts a sensitivity analysis for the estimation issues, delay and bias, and their effect on the tracking quality. In addition, the performance of the hybrid controller as compared to direct adaptive controller is explored. In order to serve this purpose, a simulation environment in MATLAB/SIMULINK has been created. The simulation environment is customized to provide the user with the flexibility to add different combinations of biases and delays to

  14. Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

    Science.gov (United States)

    Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

    2016-01-01

    Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

  15. Adaptive landing gear concept—feedback control validation

    Science.gov (United States)

    Mikulowski, Grzegorz M.; Holnicki-Szulc, Jan

    2007-12-01

    The objective of this paper is to present an integrated feedback control concept for adaptive landing gears (ALG) and its experimental validation. Aeroplanes are subjected to high dynamic loads as a result of the impact during each landing. Classical landing gears, which are in common use, are designed in accordance with official regulations in a way that ensures the optimal energy dissipation for the critical (maximum) sink speed. The regulations were formulated in order to ensure the functional capability of the landing gears during an emergency landing. However, the landing gears, whose characteristics are optimized for these critical conditions, do not perform well under normal impact conditions. For that situation it is reasonable to introduce a system that would adapt the characteristics of the landing gears according to the sink speed of landing. The considered system assumes adaptation of the damping force generated by the landing gear, which would perform optimally in an emergency situation and would adapt itself for regular landings as well. This research covers the formulation and design of the control algorithms for an adaptive landing gear based on MR fluid, implementation of the algorithms on an FPGA platform and experimental verification on a lab-scale landing gear device. The main challenge of the research was to develop a control methodology that could operate effectively within 50 ms, which is assumed to be the total duration of the phenomenon. The control algorithm proposed in this research was able to control the energy dissipation process on the experimental stand.

  16. Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

    Science.gov (United States)

    Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

    2016-04-01

    Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

  17. Adaptive Neural-Sliding Mode Control of Active Suspension System for Camera Stabilization

    Directory of Open Access Journals (Sweden)

    Feng Zhao

    2015-01-01

    Full Text Available The camera always suffers from image instability on the moving vehicle due to the unintentional vibrations caused by road roughness. This paper presents a novel adaptive neural network based on sliding mode control strategy to stabilize the image captured area of the camera. The purpose is to suppress vertical displacement of sprung mass with the application of active suspension system. Since the active suspension system has nonlinear and time varying characteristics, adaptive neural network (ANN is proposed to make the controller robustness against systematic uncertainties, which release the model-based requirement of the sliding model control, and the weighting matrix is adjusted online according to Lyapunov function. The control system consists of two loops. The outer loop is a position controller designed with sliding mode strategy, while the PID controller in the inner loop is to track the desired force. The closed loop stability and asymptotic convergence performance can be guaranteed on the basis of the Lyapunov stability theory. Finally, the simulation results show that the employed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance.

  18. Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

    Science.gov (United States)

    Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

    2017-01-01

    This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

  19. New aspects of the adaptive synchronization and hyperchaos suppression of a financial model

    International Nuclear Information System (INIS)

    Jajarmi, Amin; Hajipour, Mojtaba; Baleanu, Dumitru

    2017-01-01

    This paper mainly focuses on the analysis of a hyperchaotic financial system as well as its chaos control and synchronization. The phase diagrams of the above system are plotted and its dynamical behaviours like equilibrium points, stability, hyperchaotic attractors and Lyapunov exponents are investigated. In order to control the hyperchaos, an efficient optimal controller based on the Pontryagin’s maximum principle is designed and an adaptive controller established by the Lyapunov stability theory is also implemented. Furthermore, two identical financial models are globally synchronized by using an interesting adaptive control scheme. Finally, a fractional economic model is introduced which can also generate hyperchaotic attractors. In this case, a linear state feedback controller together with an active control technique are used in order to control the hyperchaos and realize the synchronization, respectively. Numerical simulations verifying the theoretical analysis are included.

  20. Neural and Fuzzy Adaptive Control of Induction Motor Drives

    International Nuclear Information System (INIS)

    Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

    2008-01-01

    This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller

  1. Bio-inspired adaptive feedback error learning architecture for motor control.

    Science.gov (United States)

    Tolu, Silvia; Vanegas, Mauricio; Luque, Niceto R; Garrido, Jesús A; Ros, Eduardo

    2012-10-01

    This study proposes an adaptive control architecture based on an accurate regression method called Locally Weighted Projection Regression (LWPR) and on a bio-inspired module, such as a cerebellar-like engine. This hybrid architecture takes full advantage of the machine learning module (LWPR kernel) to abstract an optimized representation of the sensorimotor space while the cerebellar component integrates this to generate corrective terms in the framework of a control task. Furthermore, we illustrate how the use of a simple adaptive error feedback term allows to use the proposed architecture even in the absence of an accurate analytic reference model. The presented approach achieves an accurate control with low gain corrective terms (for compliant control schemes). We evaluate the contribution of the different components of the proposed scheme comparing the obtained performance with alternative approaches. Then, we show that the presented architecture can be used for accurate manipulation of different objects when their physical properties are not directly known by the controller. We evaluate how the scheme scales for simulated plants of high Degrees of Freedom (7-DOFs).

  2. Adaptive robust control of the EBR-II reactor

    International Nuclear Information System (INIS)

    Power, M.A.; Edwards, R.M.

    1996-01-01

    Simulation results are presented for an adaptive H ∞ controller, a fixed H ∞ controller, and a classical controller. The controllers are applied to a simulation of the Experimental Breeder Reactor II primary system. The controllers are tested for the best robustness and performance by step-changing the demanded reactor power and by varying the combined uncertainty in initial reactor power and control rod worth. The adaptive H ∞ controller shows the fastest settling time, fastest rise time and smallest peak overshoot when compared to the fixed H ∞ and classical controllers. This makes for a superior and more robust controller

  3. Adaptive Finite-Time Control for a Flexible Hypersonic Vehicle with Actuator Fault

    Directory of Open Access Journals (Sweden)

    Jie Wang

    2013-01-01

    Full Text Available The problem of robust fault-tolerant tracking control is investigated. Simulation on the longitudinal model of a flexible air-breathing hypersonic vehicle (FAHV with actuator faults and uncertainties is conducted. In order to guarantee that the velocity and altitude track their desired commands in finite time with the partial loss of actuator effectiveness, an adaptive fault-tolerant control strategy is presented based on practical finite-time sliding mode method. The adaptive update laws are used to estimate the upper bound of uncertainties and the minimum value of actuator efficiency factor. Finally, simulation results show that the proposed control strategy is effective in rejecting uncertainties even in the presence of actuator faults.

  4. Maneuvering control and configuration adaptation of a biologically inspired morphing aircraft

    Science.gov (United States)

    Abdulrahim, Mujahid

    Natural flight as a source of inspiration for aircraft design was prominent with early aircraft but became marginalized as aircraft became larger and faster. With recent interest in small unmanned air vehicles, biological inspiration is a possible technology to enhance mission performance of aircraft that are dimensionally similar to gliding birds. Serial wing joints, loosely modeling the avian skeletal structure, are used in the current study to allow significant reconfiguration of the wing shape. The wings are reconfigured to optimize aerodynamic performance and maneuvering metrics related to specific mission tasks. Wing shapes for each mission are determined and related to the seagulls, falcons, albatrosses, and non-migratory African swallows on which the aircraft are based. Variable wing geometry changes the vehicle dynamics, affording versatility in flight behavior but also requiring appropriate compensation to maintain stability and controllability. Time-varying compensation is in the form of a baseline controller which adapts to both the variable vehicle dynamics and to the changing mission requirements. Wing shape is adapted in flight to minimize a cost function which represents energy, temporal, and spatial efficiency. An optimal control architecture unifies the control and adaptation tasks.

  5. Adaptive suboptimal second-order sliding mode control for microgrids

    Science.gov (United States)

    Incremona, Gian Paolo; Cucuzzella, Michele; Ferrara, Antonella

    2016-09-01

    This paper deals with the design of adaptive suboptimal second-order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second-order systems in Brunovsky canonical form, characterised by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analysed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies, the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state space of the auxiliary system becomes attractive. In the other two strategies, a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady state. The microgrid system in a grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.

  6. Short-Cut Estimators of Criterion-Referenced Test Consistency.

    Science.gov (United States)

    Brown, James Dean

    1990-01-01

    Presents simplified methods for deriving estimates of the consistency of criterion-referenced, English-as-a-Second-Language tests, including (1) the threshold loss agreement approach using agreement or kappa coefficients, (2) the squared-error loss agreement approach using the phi(lambda) dependability approach, and (3) the domain score…

  7. Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

    Science.gov (United States)

    Nguyen, Nhan T.

    2018-01-01

    Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

  8. Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals.

    Science.gov (United States)

    Rajasekaran, Vijaykumar; López-Larraz, Eduardo; Trincado-Alonso, Fernando; Aranda, Joan; Montesano, Luis; Del-Ama, Antonio J; Pons, Jose L

    2018-01-03

    Gait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI). A user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user's motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation. The exoskeleton demonstrated an adaptive assistance depending on the patients' performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the

  9. Adaptive piezoelectric sensoriactuators for active structural acoustic control

    Science.gov (United States)

    Vipperman, Jeffrey Stuart

    1997-09-01

    A new transducer technology with application to active control systems, modal analysis, and autonomous system health monitoring, is brought to fruition in this work. It has the advantages of being lightweight, potentially cost-effective, self-tuning, has negligible dynamics, and most importantly (from a robustness perspective), it provides a colocated sensor/actuator pair. The transducer consists of a piezoceramic element which serves as both an actuator and a sensor and will be referred to in this work as a sensoriactuator. Simple, adaptive signal processing in conjunction with a voltage controlled amplifier, reference capacitor, and a common-mode rejection circuit extract the mechanical response from the total response of the piezoelectric sensoriactuator for sensing. The digital portion of the adaptive piezoelectric sensoriactuator merely serves to tune the circuit, avoiding the potentially destabilizing effects of introducing a digital delay in the signal path, when used for feedback control applications. Adaptive compensation of the sensoriactuator is necessary since the signal to noise ratio is typically greater than 40 dB, making it prohibitive to tune the circuit manually. In addition, the constitutive properties of piezoceramics vary with time and environment, necessitating that the circuit be periodically re-tuned. The analog portion of the hardware is based upon op-amp circuits and an AD632 analog multiplier chip, which serves as both a voltage controlled amplifier (VCA) and a common mode rejection (CMR) circuit. A single coefficient least-mean square (LMS) adaptive filter continuously adjusts the gain of the VCA circuit as necessary. Nonideal behavior of piezoceramics is discussed along with methods to counter the consequential deterioration in circuit performance. A multiple input multiple output (MIMO) implementation of the adaptive piezoelectric sensoriactuator is developed using orthogonal white noise training signals for each sensoriactuator. Two

  10. Adaptive Critic Nonlinear Robust Control: A Survey.

    Science.gov (United States)

    Wang, Ding; He, Haibo; Liu, Derong

    2017-10-01

    Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

  11. Fault diagnosis and fault-tolerant control based on adaptive control approach

    CERN Document Server

    Shen, Qikun; Shi, Peng

    2017-01-01

    This book provides recent theoretical developments in and practical applications of fault diagnosis and fault tolerant control for complex dynamical systems, including uncertain systems, linear and nonlinear systems. Combining adaptive control technique with other control methodologies, it investigates the problems of fault diagnosis and fault tolerant control for uncertain dynamic systems with or without time delay. As such, the book provides readers a solid understanding of fault diagnosis and fault tolerant control based on adaptive control technology. Given its depth and breadth, it is well suited for undergraduate and graduate courses on linear system theory, nonlinear system theory, fault diagnosis and fault tolerant control techniques. Further, it can be used as a reference source for academic research on fault diagnosis and fault tolerant control, and for postgraduates in the field of control theory and engineering. .

  12. Adaptive Trajectory Tracking Control using Reinforcement Learning for Quadrotor

    Directory of Open Access Journals (Sweden)

    Wenjie Lou

    2016-02-01

    Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.

  13. Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

    Directory of Open Access Journals (Sweden)

    Quanzhen Huang

    2017-01-01

    Full Text Available Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

  14. Synthesis of adaptive traffic control discrete neminimalno-phase system

    Directory of Open Access Journals (Sweden)

    В.М. Азарсков

    2007-01-01

    Full Text Available  An adaptive approach to synthesizing the digital tracking system with direct set-point coupling is extended under conditions when a plant is non-minimum phase. Some bounded set of belonging of servo drive unknown parameters vector is believed to be known. The object’s model non-singularity condition is established. The asymptotical properties of control system are studied. Simulation results are given.

  15. Robust nonlinear control of nuclear reactors under model uncertainty

    International Nuclear Information System (INIS)

    Park, Moon Ghu

    1993-02-01

    A nonlinear model-based control method is developed for the robust control of a nuclear reactor. The nonlinear plant model is used to design a unique control law which covers a wide operating range. The robustness is a crucial factor for the fully automatic control of reactor power due to time-varying, uncertain parameters, and state estimation error, or unmodeled dynamics. A variable structure control (VSC) method is introduced which consists of an adaptive performance specification (fime control) after the tracking error reaches the narrow boundary-layer by a time-optimal control (coarse control). Variable structure control is a powerful method for nonlinear system controller design which has inherent robustness to parameter variations or external disturbances using the known uncertainty bounds, and it requires very low computational efforts. In spite of its desirable properties, conventional VSC presents several important drawbacks that limit its practical applicability. One of the most undesirable phenomena is chattering, which implies extremely high control activity and may excite high-frequency unmodeled dynamics. This problem is due to the neglected actuator time-delay or sampling effects. The problem was partially remedied by replacing chattering control by a smooth control inter-polation in a boundary layer neighnboring a time-varying sliding surface. But, for the nuclear reactor systems which has very fast dynamic response, the sampling effect may destroy the narrow boundary layer when a large uncertainty bound is used. Due to the very short neutron life time, large uncertainty bound leads to the high gain in feedback control. To resolve this problem, a derivative feedback is introduced that gives excellent performance by reducing the uncertainty bound. The stability of tracking error dynamics is guaranteed by the second method of Lyapunov using the two-level uncertainty bounds that are obtained from the knowledge of uncertainty bound and the estimated

  16. Flight Results of the NF-15B Intelligent Flight Control System (IFCS) Aircraft with Adaptation to a Longitudinally Destabilized Plant

    Science.gov (United States)

    Bosworth, John T.

    2008-01-01

    Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.

  17. Energy Referencing in LANL HE-EOS Codes

    Energy Technology Data Exchange (ETDEWEB)

    Leiding, Jeffery Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Coe, Joshua Damon [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-10-19

    Here, We briefly describe the choice of energy referencing in LANL's HE-EOS codes, HEOS and MAGPIE. Understanding this is essential to comparing energies produced by different EOS codes, as well as to the correct calculation of shock Hugoniots of HEs and other materials. In all equations after (3) throughout this report, all energies, enthalpies and volumes are assumed to be molar quantities.

  18. Parametric recursive system identification and self-adaptive modeling of the human energy metabolism for adaptive control of fat weight.

    Science.gov (United States)

    Őri, Zsolt P

    2017-05-01

    A mathematical model has been developed to facilitate indirect measurements of difficult to measure variables of the human energy metabolism on a daily basis. The model performs recursive system identification of the parameters of the metabolic model of the human energy metabolism using the law of conservation of energy and principle of indirect calorimetry. Self-adaptive models of the utilized energy intake prediction, macronutrient oxidation rates, and daily body composition changes were created utilizing Kalman filter and the nominal trajectory methods. The accuracy of the models was tested in a simulation study utilizing data from the Minnesota starvation and overfeeding study. With biweekly macronutrient intake measurements, the average prediction error of the utilized carbohydrate intake was -23.2 ± 53.8 kcal/day, fat intake was 11.0 ± 72.3 kcal/day, and protein was 3.7 ± 16.3 kcal/day. The fat and fat-free mass changes were estimated with an error of 0.44 ± 1.16 g/day for fat and -2.6 ± 64.98 g/day for fat-free mass. The daily metabolized macronutrient energy intake and/or daily macronutrient oxidation rate and the daily body composition change from directly measured serial data are optimally predicted with a self-adaptive model with Kalman filter that uses recursive system identification.

  19. Adaptive Fuzzy Robust Control for a Class of Nonlinear Systems via Small Gain Theorem

    Directory of Open Access Journals (Sweden)

    Xingjian Wang

    2013-01-01

    Full Text Available Practical nonlinear systems can usually be represented by partly linearizable models with unknown nonlinearities and external disturbances. Based on this consideration, we propose a novel adaptive fuzzy robust control (AFRC algorithm for such systems. The AFRC effectively combines techniques of adaptive control and fuzzy control, and it improves the performance by retaining the advantages of both methods. The linearizable part will be linearly parameterized with unknown but constant parameters, and the discontinuous-projection-based adaptive control law is used to compensate these parts. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown nonlinearities. Robust control law ensures the robustness of closed-loop control system. A systematic design procedure of the AFRC algorithm by combining the backstepping technique and small-gain approach is presented. Then the closed-loop stability is studied by using small gain theorem, and the result indicates that the closed-loop system is semiglobally uniformly ultimately bounded.

  20. Adaptive Backstepping Sliding-Mode Control of the Electronic Throttle System in Modern Automobiles

    Directory of Open Access Journals (Sweden)

    Rui Bai

    2014-01-01

    Full Text Available In modern automobiles, electronic throttle is a DC-motor-driven valve that regulates air inflow into the vehicle’s combustion system. The electronic throttle is increasingly being used in order to improve the vehicle drivability, fuel economy, and emissions. Electronic throttle system has the nonlinear dynamical characteristics with the unknown disturbance and parameters. At first, the dynamical nonlinear model of the electronic throttle is built in this paper. Based on the model and using the backstepping design technique, a new adaptive backstepping sliding-mode controller of the electronic throttle is developed. During the backstepping design process, parameter adaptive law is designed to estimate the unknown parameter, and sliding-mode control term is applied to compensate the unknown disturbance. The proposed controller can make the actual angle of the electronic throttle track its set point with the satisfactory performance. Finally, a computer simulation is performed, and simulation results verify that the proposed control method can achieve favorable tracking performance.

  1. Prediction errors to emotional expressions: the roles of the amygdala in social referencing.

    Science.gov (United States)

    Meffert, Harma; Brislin, Sarah J; White, Stuart F; Blair, James R

    2015-04-01

    Social referencing paradigms in humans and observational learning paradigms in animals suggest that emotional expressions are important for communicating valence. It has been proposed that these expressions initiate stimulus-reinforcement learning. Relatively little is known about the role of emotional expressions in reinforcement learning, particularly in the context of social referencing. In this study, we examined object valence learning in the context of a social referencing paradigm. Participants viewed objects and faces that turned toward the objects and displayed a fearful, happy or neutral reaction to them, while judging the gender of these faces. Notably, amygdala activation was larger when the expressions following an object were less expected. Moreover, when asked, participants were both more likely to want to approach, and showed stronger amygdala responses to, objects associated with happy relative to objects associated with fearful expressions. This suggests that the amygdala plays two roles in social referencing: (i) initiating learning regarding the valence of an object as a function of prediction errors to expressions displayed toward this object and (ii) orchestrating an emotional response to the object when value judgments are being made regarding this object. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

  2. Model of aircraft noise adaptation

    Science.gov (United States)

    Dempsey, T. K.; Coates, G. D.; Cawthorn, J. M.

    1977-01-01

    Development of an aircraft noise adaptation model, which would account for much of the variability in the responses of subjects participating in human response to noise experiments, was studied. A description of the model development is presented. The principal concept of the model, was the determination of an aircraft adaptation level which represents an annoyance calibration for each individual. Results showed a direct correlation between noise level of the stimuli and annoyance reactions. Attitude-personality variables were found to account for varying annoyance judgements.

  3. Analysis technique for controlling system wavefront error with active/adaptive optics

    Science.gov (United States)

    Genberg, Victor L.; Michels, Gregory J.

    2017-08-01

    The ultimate goal of an active mirror system is to control system level wavefront error (WFE). In the past, the use of this technique was limited by the difficulty of obtaining a linear optics model. In this paper, an automated method for controlling system level WFE using a linear optics model is presented. An error estimate is included in the analysis output for both surface error disturbance fitting and actuator influence function fitting. To control adaptive optics, the technique has been extended to write system WFE in state space matrix form. The technique is demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.

  4. Adaptive feedforward in the LANL rf control system

    International Nuclear Information System (INIS)

    Ziomek, C.D.

    1992-01-01

    This paper describes an adaptive feedforward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF field feedback control system can be eliminated with a feedforward system. Many RF field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feedforward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feedforward system are presented

  5. Adaptive-network models of collective dynamics

    Science.gov (United States)

    Zschaler, G.

    2012-09-01

    Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

  6. Tracking Control of a 2-DOF Arm Actuated by Pneumatic Muscle Actuators Using Adaptive Fuzzy Sliding Mode Control

    Science.gov (United States)

    Chang, Ming-Kun; Wu, Jui-Chi

    Pneumatic muscle actuators (PMAs) have the highest power/weight ratio and power/volume ratio of any actuator. Therefore, they can be used not only in the rehabilitation engineering, but also as an actuator in robots, including industrial robots and therapy robots. It is difficult to achieve excellent tracking performance using classical control methods because the compressibility of gas and the nonlinear elasticity of bladder container causes parameter variations. An adaptive fuzzy sliding mode control is developed in this study. The fuzzy sliding surface can be used to reduce fuzzy rule numbers, and the adaptive control law is used to modify fuzzy rules on-line. A model matching technique is then adopted to adjust scaling factors. The experimental results show that this control strategy can attain excellent tracking performance.

  7. Adaptive nonlinear control using input normalized neural networks

    International Nuclear Information System (INIS)

    Leeghim, Henzeh; Seo, In Ho; Bang, Hyo Choong

    2008-01-01

    An adaptive feedback linearization technique combined with the neural network is addressed to control uncertain nonlinear systems. The neural network-based adaptive control theory has been widely studied. However, the stability analysis of the closed-loop system with the neural network is rather complicated and difficult to understand, and sometimes unnecessary assumptions are involved. As a result, unnecessary assumptions for stability analysis are avoided by using the neural network with input normalization technique. The ultimate boundedness of the tracking error is simply proved by the Lyapunov stability theory. A new simple update law as an adaptive nonlinear control is derived by the simplification of the input normalized neural network assuming the variation of the uncertain term is sufficiently small

  8. Experimental Investigation on Adaptive Robust Controller Designs Applied to Constrained Manipulators

    Directory of Open Access Journals (Sweden)

    Marco H. Terra

    2013-04-01

    Full Text Available In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear H∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose.

  9. Adaptive slope compensation for high bandwidth digital current mode controller

    DEFF Research Database (Denmark)

    Taeed, Fazel; Nymand, Morten

    2015-01-01

    An adaptive slope compensation method for digital current mode control of dc-dc converters is proposed in this paper. The compensation slope is used for stabilizing the inner current loop in peak current mode control. In this method, the compensation slope is adapted with the variations...... in converter duty cycle. The adaptive slope compensation provides optimum controller operation in term of bandwidth over wide range of operating points. In this paper operation principle of the controller is discussed. The proposed controller is implemented in an FPGA to control a 100 W buck converter...

  10. Adaptive fuzzy controller based MPPT for photovoltaic systems

    International Nuclear Information System (INIS)

    Guenounou, Ouahib; Dahhou, Boutaib; Chabour, Ferhat

    2014-01-01

    Highlights: • We propose a fuzzy controller with adaptive output scaling factor as a maximum power point tracker of photovoltaic system. • The proposed controller integrates two different rule bases defined on error and change of error. • Our controller can track the maximum power point with better performances when compared to its conventional counterpart. - Abstract: This paper presents an intelligent approach to optimize the performances of photovoltaic systems. The system consists of a PV panel, a DC–DC boost converter, a maximum power point tracker controller and a resistive load. The key idea of the proposed approach is the use of a fuzzy controller with an adaptive gain as a maximum power point tracker. The proposed controller integrates two different rule bases. The first is used to adjust the duty cycle of the boost converter as in the case of a conventional fuzzy controller while the second rule base is designed for an online adjusting of the controller’s gain. The performances of the adaptive fuzzy controller are compared with those obtained using a conventional fuzzy controllers with different gains and in each case, the proposed controller outperforms its conventional counterpart

  11. Estimation of Total Nitrogen and Phosphorus in New England Streams Using Spatially Referenced Regression Models

    Science.gov (United States)

    Moore, Richard Bridge; Johnston, Craig M.; Robinson, Keith W.; Deacon, Jeffrey R.

    2004-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA) and the New England Interstate Water Pollution Control Commission (NEIWPCC), has developed a water-quality model, called SPARROW (Spatially Referenced Regressions on Watershed Attributes), to assist in regional total maximum daily load (TMDL) and nutrient-criteria activities in New England. SPARROW is a spatially detailed, statistical model that uses regression equations to relate total nitrogen and phosphorus (nutrient) stream loads to nutrient sources and watershed characteristics. The statistical relations in these equations are then used to predict nutrient loads in unmonitored streams. The New England SPARROW models are built using a hydrologic network of 42,000 stream reaches and associated watersheds. Watershed boundaries are defined for each stream reach in the network through the use of a digital elevation model and existing digitized watershed divides. Nutrient source data is from permitted wastewater discharge data from USEPA's Permit Compliance System (PCS), various land-use sources, and atmospheric deposition. Physical watershed characteristics include drainage area, land use, streamflow, time-of-travel, stream density, percent wetlands, slope of the land surface, and soil permeability. The New England SPARROW models for total nitrogen and total phosphorus have R-squared values of 0.95 and 0.94, with mean square errors of 0.16 and 0.23, respectively. Variables that were statistically significant in the total nitrogen model include permitted municipal-wastewater discharges, atmospheric deposition, agricultural area, and developed land area. Total nitrogen stream-loss rates were significant only in streams with average annual flows less than or equal to 2.83 cubic meters per second. In streams larger than this, there is nondetectable in-stream loss of annual total nitrogen in New England. Variables that were statistically significant in the total

  12. Adaptive Functional-Based Neuro-Fuzzy-PID Incremental Controller Structure

    Directory of Open Access Journals (Sweden)

    Ashraf Ahmed Fahmy

    2014-03-01

    Full Text Available This paper presents an adaptive functional-based Neuro-fuzzy-PID incremental (NFPID controller structure that can be tuned either offline or online according to required controller performance. First, differential membership functions are used to represent the fuzzy membership functions of the input-output space of the three term controller. Second, controller rules are generated based on the discrete proportional, derivative, and integral function for the fuzzy space. Finally, a fully differentiable fuzzy neural network is constructed to represent the developed controller for either offline or online controller parameter adaptation.  Two different adaptation methods are used for controller tuning, offline method based on controller transient performance cost function optimization using Bees Algorithm, and online method based on tracking error minimization using back-propagation with momentum algorithm. The proposed control system was tested to show the validity of the controller structure over a fixed PID controller gains to control SCARA type robot arm.

  13. Design of a biped locomotion controller based on adaptive neuro-fuzzy inference systems

    Energy Technology Data Exchange (ETDEWEB)

    Shieh, M-Y; Chang, K-H [Department of E. E., Southern Taiwan University, 1 Nantai St., YungKang City, Tainan County 71005, Taiwan (China); Lia, Y-S [Executive Director Office, ITRI, Southern Taiwan Innovation Park, Tainan County, Taiwan (China)], E-mail: myshieh@mail.stut.edu.tw

    2008-02-15

    This paper proposes a method for the design of a biped locomotion controller based on the ANFIS (Adaptive Neuro-Fuzzy Inference System) inverse learning model. In the model developed here, an integrated ANFIS structure is trained to function as the system identifier for the modeling of the inverse dynamics of a biped robot. The parameters resulting from the modeling process are duplicated and integrated as those of the biped locomotion controller to provide favorable control action. As the simulation results show, the proposed controller is able to generate a stable walking cycle for a biped robot. Moreover, the experimental results demonstrate that the performance of the proposed controller is satisfactory under conditions when the robot stands in different postures or moves on a rugged surface.

  14. Design of a biped locomotion controller based on adaptive neuro-fuzzy inference systems

    International Nuclear Information System (INIS)

    Shieh, M-Y; Chang, K-H; Lia, Y-S

    2008-01-01

    This paper proposes a method for the design of a biped locomotion controller based on the ANFIS (Adaptive Neuro-Fuzzy Inference System) inverse learning model. In the model developed here, an integrated ANFIS structure is trained to function as the system identifier for the modeling of the inverse dynamics of a biped robot. The parameters resulting from the modeling process are duplicated and integrated as those of the biped locomotion controller to provide favorable control action. As the simulation results show, the proposed controller is able to generate a stable walking cycle for a biped robot. Moreover, the experimental results demonstrate that the performance of the proposed controller is satisfactory under conditions when the robot stands in different postures or moves on a rugged surface

  15. Adaptive Sliding-Mode Control in Bus Voltage for an Islanded DC Microgrid

    Directory of Open Access Journals (Sweden)

    Dan Zhang

    2017-01-01

    Full Text Available The control of bus voltage is a crucial task for the stable operation of islanded DC microgrids. To improve the DC bus voltage control dynamics and stability, this paper proposes an adaptive sliding-mode control method based on large-signal model. The sliding-mode control, adaptive observation, and fix-frequency pulse width modulation technology are adopted and combined efficiently, which guarantee stable bus voltage and the constant switching frequency of closed-loop system, regardless of how the parameters vary with the variable constant-power loads and uncertainties. In addition, the reference values can be quickly tracked by the state variables using the proposed method without any additional sensors/hardware circuits. Therefore, this method is beneficial for the scalability and plug-play of the distributed generators and loads within the DC microgrids. The performance of the proposed control method has been successfully verified in simulation.

  16. Sport Skill-Specific Expertise Biases Sensory Integration for Spatial Referencing and Postural Control.

    Science.gov (United States)

    Thalassinos, Michalis; Fotiadis, Giorgos; Arabatzi, Fotini; Isableu, Brice; Hatzitaki, Vassilia

    2017-09-15

    The authors asked how sport expertise modulates visual field dependence and sensory reweighting for controlling posture. Experienced soccer athletes, ballet dancers, and nonathletes performed (a) a Rod and Frame test and (b) a 100-s bipedal stance task during which vision and proprioception were successively or concurrently disrupted in 20-s blocks. Postural adaptation was assessed in the mean center of pressure displacement, root mean square of center of pressure velocity and ankle muscles integrated electromyography activity. Soccer athletes were more field dependent than were nonathletes. During standing, dancers were more destabilized by vibration and required more time to reweigh sensory information compared with the other 2 groups. These findings reveal a sport skill-specific bias in the reweighing of sensory inputs for spatial orientation and postural control.

  17. Adaptive twisting sliding mode algorithm for hypersonic reentry vehicle attitude control based on finite-time observer.

    Science.gov (United States)

    Guo, Zongyi; Chang, Jing; Guo, Jianguo; Zhou, Jun

    2018-06-01

    This paper focuses on the adaptive twisting sliding mode control for the Hypersonic Reentry Vehicles (HRVs) attitude tracking issue. The HRV attitude tracking model is transformed into the error dynamics in matched structure, whereas an unmeasurable state is redefined by lumping the existing unmatched disturbance with the angular rate. Hence, an adaptive finite-time observer is used to estimate the unknown state. Then, an adaptive twisting algorithm is proposed for systems subject to disturbances with unknown bounds. The stability of the proposed observer-based adaptive twisting approach is guaranteed, and the case of noisy measurement is analyzed. Also, the developed control law avoids the aggressive chattering phenomenon of the existing adaptive twisting approaches because the adaptive gains decrease close to the disturbance once the trajectories reach the sliding surface. Finally, numerical simulations on the attitude control of the HRV are conducted to verify the effectiveness and benefit of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Application of simple adaptive control to water hydraulic servo cylinder system

    Science.gov (United States)

    Ito, Kazuhisa; Yamada, Tsuyoshi; Ikeo, Shigeru; Takahashi, Koji

    2012-09-01

    Although conventional model reference adaptive control (MRAC) achieves good tracking performance for cylinder control, the controller structure is much more complicated and has less robustness to disturbance in real applications. This paper discusses the use of simple adaptive control (SAC) for positioning a water hydraulic servo cylinder system. Compared with MRAC, SAC has a simpler and lower order structure, i.e., higher feasibility. The control performance of SAC is examined and evaluated on a water hydraulic servo cylinder system. With the recent increased concerns over global environmental problems, the water hydraulic technique using pure tap water as a pressure medium has become a new drive source comparable to electric, oil hydraulic, and pneumatic drive systems. This technique is also preferred because of its high power density, high safety against fire hazards in production plants, and easy availability. However, the main problems for precise control in a water hydraulic system are steady state errors and overshoot due to its large friction torque and considerable leakage flow. MRAC has been already applied to compensate for these effects, and better control performances have been obtained. However, there have been no reports on the application of SAC for water hydraulics. To make clear the merits of SAC, the tracking control performance and robustness are discussed based on experimental results. SAC is confirmed to give better tracking performance compared with PI control, and a control precision comparable to MRAC (within 10 μm of the reference position) and higher robustness to parameter change, despite the simple controller. The research results ensure a wider application of simple adaptive control in real mechanical systems.

  19. Optimal inverse magnetorheological damper modeling using shuffled frog-leaping algorithm–based adaptive neuro-fuzzy inference system approach

    Directory of Open Access Journals (Sweden)

    Xiufang Lin

    2016-08-01

    Full Text Available Magnetorheological dampers have become prominent semi-active control devices for vibration mitigation of structures which are subjected to severe loads. However, the damping force cannot be controlled directly due to the inherent nonlinear characteristics of the magnetorheological dampers. Therefore, for fully exploiting the capabilities of the magnetorheological dampers, one of the challenging aspects is to develop an accurate inverse model which can appropriately predict the input voltage to control the damping force. In this article, a hybrid modeling strategy combining shuffled frog-leaping algorithm and adaptive-network-based fuzzy inference system is proposed to model the inverse dynamic characteristics of the magnetorheological dampers for improving the modeling accuracy. The shuffled frog-leaping algorithm is employed to optimize the premise parameters of the adaptive-network-based fuzzy inference system while the consequent parameters are tuned by a least square estimation method, here known as shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach. To evaluate the effectiveness of the proposed approach, the inverse modeling results based on the shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach are compared with those based on the adaptive-network-based fuzzy inference system and genetic algorithm–based adaptive-network-based fuzzy inference system approaches. Analysis of variance test is carried out to statistically compare the performance of the proposed methods and the results demonstrate that the shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system strategy outperforms the other two methods in terms of modeling (training accuracy and checking accuracy.

  20. Adaptive traffic control systems for urban networks

    Directory of Open Access Journals (Sweden)

    Radivojević Danilo

    2017-01-01

    Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

  1. Dogs' social referencing towards owners and strangers.

    Science.gov (United States)

    Merola, Isabella; Prato-Previde, Emanuela; Marshall-Pescini, Sarah

    2012-01-01

    Social referencing is a process whereby an individual uses the emotional information provided by an informant about a novel object/stimulus to guide his/her own future behaviour towards it. In this study adult dogs were tested in a social referencing paradigm involving a potentially scary object with either their owner or a stranger acting as the informant and delivering either a positive or negative emotional message. The aim was to evaluate the influence of the informant's identity on the dogs' referential looking behaviour and behavioural regulation when the message was delivered using only vocal and facial emotional expressions. Results show that most dogs looked referentially at the informant, regardless of his/her identity. Furthermore, when the owner acted as the informant dogs that received a positive emotional message changed their behaviour, looking at him/her more often and spending more time approaching the object and close to it; conversely, dogs that were given a negative message took longer to approach the object and to interact with it. Fewer differences in the dog's behaviour emerged when the informant was the stranger, suggesting that the dog-informant relationship may influence the dog's behavioural regulation. Results are discussed in relation to studies on human-dog communication, attachment, mood modification and joint attention.

  2. Dogs' social referencing towards owners and strangers.

    Directory of Open Access Journals (Sweden)

    Isabella Merola

    Full Text Available Social referencing is a process whereby an individual uses the emotional information provided by an informant about a novel object/stimulus to guide his/her own future behaviour towards it. In this study adult dogs were tested in a social referencing paradigm involving a potentially scary object with either their owner or a stranger acting as the informant and delivering either a positive or negative emotional message. The aim was to evaluate the influence of the informant's identity on the dogs' referential looking behaviour and behavioural regulation when the message was delivered using only vocal and facial emotional expressions. Results show that most dogs looked referentially at the informant, regardless of his/her identity. Furthermore, when the owner acted as the informant dogs that received a positive emotional message changed their behaviour, looking at him/her more often and spending more time approaching the object and close to it; conversely, dogs that were given a negative message took longer to approach the object and to interact with it. Fewer differences in the dog's behaviour emerged when the informant was the stranger, suggesting that the dog-informant relationship may influence the dog's behavioural regulation. Results are discussed in relation to studies on human-dog communication, attachment, mood modification and joint attention.

  3. Adaptive Control of Electromagnetic Suspension System by HOPF Bifurcation

    Directory of Open Access Journals (Sweden)

    Aming Hao

    2013-01-01

    Full Text Available EMS-type maglev system is essentially nonlinear and unstable. It is complicated to design a stable controller for maglev system which is under large-scale disturbance and parameter variance. Theory analysis expresses that this phenomenon corresponds to a HOPF bifurcation in mathematical model. An adaptive control law which adjusts the PID control parameters is given in this paper according to HOPF bifurcation theory. Through identification of the levitated mass, the controller adjusts the feedback coefficient to make the system far from the HOPF bifurcation point and maintain the stability of the maglev system. Simulation result indicates that adjusting proportion gain parameter using this method can extend the state stability range of maglev system and avoid the self-excited vibration efficiently.

  4. Adaptive Control Using Fully Online Sequential-Extreme Learning Machine and a Case Study on Engine Air-Fuel Ratio Regulation

    Directory of Open Access Journals (Sweden)

    Pak Kin Wong

    2014-01-01

    Full Text Available Most adaptive neural control schemes are based on stochastic gradient-descent backpropagation (SGBP, which suffers from local minima problem. Although the recently proposed regularized online sequential-extreme learning machine (ReOS-ELM can overcome this issue, it requires a batch of representative initial training data to construct a base model before online learning. The initial data is usually difficult to collect in adaptive control applications. Therefore, this paper proposes an improved version of ReOS-ELM, entitled fully online sequential-extreme learning machine (FOS-ELM. While retaining the advantages of ReOS-ELM, FOS-ELM discards the initial training phase, and hence becomes suitable for adaptive control applications. To demonstrate its effectiveness, FOS-ELM was applied to the adaptive control of engine air-fuel ratio based on a simulated engine model. Besides, controller parameters were also analyzed, in which it is found that large hidden node number with small regularization parameter leads to the best performance. A comparison among FOS-ELM and SGBP was also conducted. The result indicates that FOS-ELM achieves better tracking and convergence performance than SGBP, since FOS-ELM tends to learn the unknown engine model globally whereas SGBP tends to “forget” what it has learnt. This implies that FOS-ELM is more preferable for adaptive control applications.

  5. A Criterion-Referenced Approach to Student Ratings of Instruction

    Science.gov (United States)

    Meyer, J. Patrick; Doromal, Justin B.; Wei, Xiaoxin; Zhu, Shi

    2017-01-01

    We developed a criterion-referenced student rating of instruction (SRI) to facilitate formative assessment of teaching. It involves four dimensions of teaching quality that are grounded in current instructional design principles: Organization and structure, Assessment and feedback, Personal interactions, and Academic rigor. Using item response…

  6. Multivariable robust adaptive sliding mode control of an industrial boiler-turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller.

    Science.gov (United States)

    Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

    2015-09-01

    To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Application of adaptive fuzzy control technology to pressure control of a pressurizer

    Institute of Scientific and Technical Information of China (English)

    YANG Ben-kun; BIAN Xin-qian; GUO Wei-lai

    2005-01-01

    A pressurizer is one of important equipment in a pressurized water reactor plant. It is used to maintain the pressure of primary coolant within allowed range because the sharp change of coolant pressure affects the security of reactor,therefor,the study of pressurizer's pressure control methods is very important. In this paper, an adaptive fuzzy controller is presented for pressure control of a pressurizer in a nuclear power plant. The controller can on-line tune fuzzy control rules and parameters by self-learning in the actual control process, which possesses the way of thinking like human to make a decision. The simulation results for a pressurized water reactor plant show that the adaptive fuzzy controller has optimum and intelligent characteristics, which prove the controller is effective.

  8. Fuzzy model predictive control algorithm applied in nuclear power plant

    International Nuclear Information System (INIS)

    Zuheir, Ahmad

    2006-01-01

    The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

  9. Control uncertain Genesio-Tesi chaotic system: Adaptive sliding mode approach

    International Nuclear Information System (INIS)

    Dadras, Sara; Momeni, Hamid Reza

    2009-01-01

    An adaptive sliding mode control (ASMC) technique is introduced in this paper for a chaotic dynamical system (Genesio-Tesi system). Using the sliding mode control technique, a sliding surface is determined and the control law is established. An adaptive sliding mode control law is derived to make the states of the Genesio-Tesi system asymptotically track and regulate the desired state. The designed control scheme can control the uncertain chaotic behaviors to a desired state without oscillating very fast and guarantee the property of asymptotical stability. An illustrative simulation result is given to demonstrate the effectiveness of the proposed adaptive sliding mode control design.

  10. A theoretical adaptive model of thermal comfort - Adaptive Predicted Mean Vote (aPMV)

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Runming [School of Construction Management and Engineering, The University of Reading (United Kingdom); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Li, Baizhan [Key Laboratory of the Three Gorges Reservoir Region' s Eco-Environment (Ministry of Education), Chongqing University (China); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Liu, Jing [School of Construction Management and Engineering, The University of Reading (United Kingdom)

    2009-10-15

    This paper presents in detail a theoretical adaptive model of thermal comfort based on the ''Black Box'' theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient ({lambda}) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results. (author)

  11. A guide to the Harvard referencing system.

    Science.gov (United States)

    Dwyer, M

    This article explains how to reference an academic work using the Harvard system. Instructions comply with the relevant British standards, i.e. BS 5605:1990, BS 1629:1989 and BS 6371:1983. The importance of referencing in an approved manner is discussed and problem areas such as joint authors, corporate authorship and unpublished works are examined. The issue of second-hand references that are not addressed by the standards is also explained.

  12. Modern referencing trends in philosophical research papers

    OpenAIRE

    Muñoz-Alonso López, Gemma

    2006-01-01

    El artículo propone unificar los criterios para citar y elaborar bibliografías en la investigación en filosofía y en ciencias humanas. Se analizan las ventajas y los inconvenientes del sistema tradicional y del sistema Harvard.The paper attempts to unify criteria for referencing documents and elaborating bibliographies in philosophy and human sciences research. The advantages and disadvantages of the Harvard system are confronted with more traditional methods.

  13. Robust Adaptive Reactive Power Control for Doubly Fed Induction Generator

    Directory of Open Access Journals (Sweden)

    Huabin Wen

    2014-01-01

    Full Text Available The problem of reactive power control for mains-side inverter (MSI in doubly fed induction generator (DFIG is studied in this paper. To accommodate the modelling nonlinearities and inherent uncertainties, a novel robust adaptive control algorithm for MSI is proposed by utilizing Lyapunov theory that ensures asymptotic stability of the system under unpredictable external disturbances and significant parametric uncertainties. The distinguishing benefit of the aforementioned scheme consists in its capabilities to maintain satisfactory performance under varying operation conditions without the need for manually redesigning or reprogramming the control gains in contrast to the commonly used PI/PID control. Simulations are also built to confirm the correctness and benefits of the control scheme.

  14. Management of information for mission operations using automated keyword referencing

    Science.gov (United States)

    Davidson, Roger A.; Curran, Patrick S.

    1993-01-01

    Although millions of dollars have helped to improve the operability and technology of ground data systems for mission operations, almost all mission documentation remains bound in printed volumes. This form of documentation is difficult and timeconsuming to use, may be out-of-date, and is usually not cross-referenced with other related volumes of mission documentation. A more effective, automated method of mission information access is needed. A new method of information management for mission operations using automated keyword referencing is proposed. We expound on the justification for and the objectives of this concept. The results of a prototype tool for mission information access that uses a hypertextlike user interface and existing mission documentation are shared. Finally, the future directions and benefits of our proposed work are described.

  15. [Development of a structural equation model for children's adaptation in divorced families].

    Science.gov (United States)

    Shin, Sung Hee

    2010-02-01

    This study was designed to develop and test a structural model for children's adaptation in divorced families. The hypothetical model was constructed based on the Family Resilience Model by McCubbin and McCubbin. Data were collected using self-report questionnaires from 219 children (3-6th grade) in divorced families. The children attended one of 22 community agencies, 8 after-school programs, 3 elementary schools in three cities in South Korea. The collected data were analyzed using LISREL program to test the hypothetical model. The modified model was constructed by deleting four paths in accordance with the statistical and theoretical criteria. Compared to the hypothetical model, the revised one had a better fit to the data. Self-esteem, and beliefs about parental divorce had direct effects, and family communication and internal control had indirect effects on children's adaptation in divorced families. These variables explained 56% of the variance in children's adaptation. The modified model was supported by empirical data. This model could be applied to family nursing interventions with divorced families or any other suffering family transition. When working with children experiencing parental divorce, it is important for nurses to enhance children's self-esteem, family communication and to decrease children's negative beliefs about parental divorce to help in their adaptation.

  16. Modified Adaptive Control for Region 3 Operation in the Presence of Wind Turbine Structural Modes

    Science.gov (United States)

    Frost, Susan Alane; Balas, Mark J.; Wright, Alan D.

    2010-01-01

    Many challenges exist for the operation of wind turbines in an efficient manner that is reliable and avoids component fatigue and failure. Turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, possibly causing component fatigue and failure. Wind turbine manufacturers are highly motivated to reduce component fatigue and failure that can lead to loss of revenue due to turbine down time and maintenance costs. The trend in wind turbine design is toward larger, more flexible turbines that are ideally suited to adaptive control methods due to the complexity and expense required to create accurate models of their dynamic characteristics. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed horizontal axis wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the excitation of structural modes in the wind turbine. The control objective is accomplished by collectively pitching the turbine blades. The adaptive collective pitch controller for Region 3 was compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller. The adaptive controller will demonstrate the ability to regulate generator speed in Region 3, while accommodating gusts, and reducing the excitation of certain structural modes in the wind turbine.

  17. A novel discrete adaptive sliding-mode-like control method for ionic polymer–metal composite manipulators

    International Nuclear Information System (INIS)

    Sun, Zhiyong; Hao, Lina; Liu, Liqun; Chen, Wenlin; Li, Zhi

    2013-01-01

    Ionic polymer–metal composite (IPMC), also called artificial muscle, is an EAP material which can generate a relatively large deformation with a low driving voltage (generally less than 5 V). Like other EAP materials, IPMC possesses strong nonlinear properties, which can be described as a hybrid of back-relaxation (BR) and hysteresis characteristics, which also vary with water content, environmental temperature and even the usage consumption. Nowadays, many control approaches have been developed to tune the IPMC actuators, among which adaptive methods show a particular striking performance. To deal with IPMCs’ nonlinear problem, this paper represents a robust discrete adaptive inverse (AI) control approach, which employs an on-line identification technique based on the BR operator and Prandtl–Ishlinskii (PI) hysteresis operator hybrid model estimation method. Here the newly formed control approach is called discrete adaptive sliding-mode-like control (DASMLC) due to the similarity of its design method to that of a sliding mode controller. The weighted least mean squares (WLMS) identification method was employed to estimate the hybrid IPMC model because of its advantage of insensitivity to environmental noise. Experiments with the DASMLC approach and a conventional PID controller were carried out to compare and demonstrate the proposed controller’s better performance. (paper)

  18. Adaptive Non-linear Control of Hydraulic Actuator Systems

    DEFF Research Database (Denmark)

    Hansen, Poul Erik; Conrad, Finn

    1998-01-01

    Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....

  19. Adaptive control for accelerators

    International Nuclear Information System (INIS)

    Eaton, L.E.; Jachim, S.P.; Natter, E.F.

    1991-01-01

    This patent describes an adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity

  20. Adaptive control for accelerators

    Science.gov (United States)

    Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.

    1991-01-01

    An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.