Nonlinear adaptive control system design with asymptotically stable parameter estimation error
Mishkov, Rumen; Darmonski, Stanislav
2018-01-01
The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.
Zheng, Shiqi; Tang, Xiaoqi; Song, Bao; Lu, Shaowu; Ye, Bosheng
2013-07-01
In this paper, a stable adaptive PI control strategy based on the improved just-in-time learning (IJITL) technique is proposed for permanent magnet synchronous motor (PMSM) drive. Firstly, the traditional JITL technique is improved. The new IJITL technique has less computational burden and is more suitable for online identification of the PMSM drive system which is highly real-time compared to traditional JITL. In this way, the PMSM drive system is identified by IJITL technique, which provides information to an adaptive PI controller. Secondly, the adaptive PI controller is designed in discrete time domain which is composed of a PI controller and a supervisory controller. The PI controller is capable of automatically online tuning the control gains based on the gradient descent method and the supervisory controller is developed to eliminate the effect of the approximation error introduced by the PI controller upon the system stability in the Lyapunov sense. Finally, experimental results on the PMSM drive system show accurate identification and favorable tracking performance. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Chen, Weisheng; Ge, Shuzhi Sam; Wu, Jian; Gong, Maoguo
2015-09-01
This paper addresses the problem of globally stable direct adaptive backstepping neural network (NN) tracking control design for a class of uncertain strict-feedback systems under the assumption that the accuracy of the ultimate tracking error is given a priori. In contrast to the classical adaptive backstepping NN control schemes, this paper analyzes the convergence of the tracking error using Barbalat's Lemma via some nonnegative functions rather than the positive-definite Lyapunov functions. Thus, the accuracy of the ultimate tracking error can be determined and adjusted accurately a priori, and the closed-loop system is guaranteed to be globally uniformly ultimately bounded. The main technical novelty is to construct three new n th-order continuously differentiable functions, which are used to design the control law, the virtual control variables, and the adaptive laws. Finally, two simulation examples are given to illustrate the effectiveness and advantages of the proposed control method.
Directory of Open Access Journals (Sweden)
MOHAMED BAHITA
2012-02-01
Full Text Available In this paper, a direct adaptive control scheme for a class of nonlinear systems is proposed. The architecture employs a Gaussian radial basis function (RBF network to construct an adaptive controller. The parameters of the adaptive controller are adapted and changed according to a law derived using Lyapunov stability theory. The centres of the RBF network are adapted on line using the k-means algorithm. Asymptotic Lyapunov stability is established without the use of a supervisory (compensatory term in the control law and with the tracking errors converging to a neighbourhood of the origin. Finally, a simulation is provided to explore the feasibility of the proposed neuronal controller design method.
Application of stable adaptive schemes to nuclear reactor systems, (1)
International Nuclear Information System (INIS)
Fukuda, Toshio
1978-01-01
Parameter identification and adaptive control schemes are presented for a point reactor with internal feedbacks which lead to the nonlinearity of the overall system. Both are shown stable with new representation of the system, which corresponds to the nonminimal system representation, in the vein of the Model Reference Adaptive System (MRAS) via the Lyapunov's method. For the sake of the parameter identification, model parameters can be adjusted adaptively as soon as measurements start, while plant parameters can also adaptively be compensated through control input to reduce the output error between the model and the plant for the case of the adaptive control. In the case of the adaptive control, control schemes are presented for two cases, the case of the unknown decay constant of the delayed neutron and the case of the known constant. The adaptive control scheme for the latter case is shown extremely simpler than that for the former. Furthermore, when plant parameters vary slowly with time, computer simulations show that the proposed adaptive control scheme works satisfactorily enough to stabilize an unstable reactor and that it does even in the noise with small variance. (auth.)
Application of stable adaptive schemes to nuclear reactor systems, (2)
International Nuclear Information System (INIS)
Kukuda, Toshio
1979-01-01
The parameter identification and adaptive control schemes applied in a previous study to a nonlinear point reactor are extended to the case of a loosely-coupled-core reactor with internal feedbacks, constituting a nonlinear overall system. Both schemes are shown to be stable, with the system newly represented on the pattern of the Model Reference Adaptive System (MRAS) with use made of the Lyapunov's method. For either parameter identification or adaptive control of a loosely-coupled-core reactor, there exists no canonical form of multiple input-multiple output system which can be directly applied for deriving the MRAS with the matrix version of the Kalman-Yakubovich lemma as it was in the case of the point reactor. This difficulty is circumvented by the practical assumption that the neutron density can be directly measured on each core as reactivity change is applied as input into the coupled core as a whole. For parameter identification, the model parameters are adaptively adjusted to those of each core, while for the adaptive control, plant parameters of each core can be adaptively compensated, again through control inputs, to asymptotically reduce the output error between the model and the plant. The point reactor is shown to correspond to a special case. (author)
Predictor-Based Model Reference Adaptive Control
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.
Commande floue adaptative directe stable étendue appliquée à la ...
African Journals Online (AJOL)
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Commande floue adaptative directe stable étendue appliquée à la machine asynchrone. Stable direct adaptive fuzzy control extended applied to the asynchronous machine. Malika Fodil. 1. , Said Barkat. 1 et Djamel Boukhetala. 2. 1Université de M'sila, BP 166, rue Ichbillia, M'sila, Algérie. 2Laboratoire de Commande des ...
Generalization in adaptation to stable and unstable dynamics.
Directory of Open Access Journals (Sweden)
Abdelhamid Kadiallah
Full Text Available Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization.
Robust Optimal Adaptive Control Method with Large Adaptive Gain
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.
Adaptive friction compensation: a globally stable approach
Verbert, K.A.; Tóth, R.; Babuska, R.
2016-01-01
In this paper, an adaptive friction compensation scheme is proposed. The friction force is computed as a timevarying friction coefficient multiplied by the sign of the velocity and an on-line update law is designed to estimate this coefficient based on the actual position and velocity errors.
International Nuclear Information System (INIS)
Zhang, Z.; Sun, X.-H.; Tong, G.-N.; Huang, Z.-C.; He, Z.-H.; Pauw, A.; Es, J. van; Battiston, R.; Borsini, S.; Laudi, E.; Verlaat, B.; Gargiulo, C.
2011-01-01
A mechanically pumped CO 2 two-phase loop cooling system was developed for the temperature control of the silicon tracker of AMS-02, a cosmic particle detector to work in the International Space Station. The cooling system (called TTCS, or Tracker Thermal Control System), consists of two evaporators in parallel to collect heat from the tracker's front-end electronics, two radiators in parallel to emit the heat into space, and a centrifugal pump that circulates the CO 2 fluid that carries the heat to the radiators, and an accumulator that controls the pressure, and thus the temperature of the evaporators. Thermal vacuum tests were performed to check and qualify the system operation in simulated space thermal environment. In this paper, we reported the test results which show that the TTCS exhibited excellent temperature control ability, including temperature homogeneity and stability, and self-adaptive ability to the various external heat flux to the radiators. Highlights: → The active-pumped CO 2 two-phase cooling loop passed the thermal vacuum test. → It provides high temperature homogeneity and stability thermal boundaries. → Its working temperature is controllable in vacuum environment. → It possesses self-adaptive ability to imbalanced external heat fluxes.
Temperature and Humidity Control in Livestock Stables
DEFF Research Database (Denmark)
Hansen, Michael; Andersen, Palle; Nielsen, Kirsten M.
2010-01-01
The paper describes temperature and humidity control of a livestock stable. It is important to have a correct air flow pattern in the livestock stable in order to achieve proper temperature and humidity control as well as to avoid draught. In the investigated livestock stable the air flow...
Ibeas, Asier; de la Sen, Manuel
2006-10-01
The problem of controlling a tandem of robotic manipulators composing a teleoperation system with force reflection is addressed in this paper. The final objective of this paper is twofold: 1) to design a robust control law capable of ensuring closed-loop stability for robots with uncertainties and 2) to use the so-obtained control law to improve the tracking of each robot to its corresponding reference model in comparison with previously existing controllers when the slave is interacting with the obstacle. In this way, a multiestimation-based adaptive controller is proposed. Thus, the master robot is able to follow more accurately the constrained motion defined by the slave when interacting with an obstacle than when a single-estimation-based controller is used, improving the transparency property of the teleoperation scheme. The closed-loop stability is guaranteed if a minimum residence time, which might be updated online when unknown, between different controller parameterizations is respected. Furthermore, the analysis of the teleoperation and stability capabilities of the overall scheme is carried out. Finally, some simulation examples showing the working of the multiestimation scheme complete this paper.
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
Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets
Toft, I. E.; Bagnall, A. J.
This paper introduces a new adaptive sniping agent for the Continuous Double Auction. We begin by analysing the performance of the well known Kaplan sniper in two extremes of market conditions. We generate volatile and stable market conditions using the well known Zero Intelligence-Constrained agent and a new zero-intelligence agent Small Increment (SI). ZI-C agents submit random but profitable bids/offers and cause high volatility in prices and individual trader performance. Our new zero-intelligence agent, SI, makes small random adjustments to the outstanding bid/offer and hence is more cautious than ZI-C. We present results for SI in self-play and then analyse Kaplan in volatile and stable markets. We demonstrate that the non-adaptive Kaplan sniper can be configured to suit either market conditions, but no single configuration is performs well across both market types. We believe that in a dynamic auction environment where current or future market conditions cannot be predicted a viable sniping strategy should adapt its behaviour to suit prevailing market conditions. To this end, we propose the Adaptive Sniper (AS) agent for the CDA. AS traders classify sniping opportunities using a statistical model of market activity and adjust their classification thresholds using a Widrow-Hoff adapted search. Our AS agent requires little configuration, and outperforms the original Kaplan sniper in volatile and stable markets, and in a mixed trader type scenario that includes adaptive strategies from the literature.
Controlling smart grid adaptivity
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.
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.
Adaptive sequential controller
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.
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
Adaptive control for accelerators
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.
An Approach to Stable Walking over Uneven Terrain Using a Reflex-Based Adaptive Gait
Directory of Open Access Journals (Sweden)
Umar Asif
2011-01-01
Full Text Available This paper describes the implementation of an adaptive gait in a six-legged walking robot that is capable of generating reactive stepping actions with the same underlying control methodology as an insect for stable walking over uneven terrains. The proposed method of gait generation uses feedback data from onboard sensors to generate an adaptive gait in order to surmount obstacles, gaps and perform stable walking. The paper addresses its implementation through simulations in a visual dynamic simulation environment. Finally the paper draws conclusions about the significance and performance of the proposed gait in terms of tracking errors while navigating in difficult terrains.
Adaptive PI Controller for a Nonlinear System
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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.
Graceful degradation of cooperative adaptive cruise control
Ploeg, J.; Semsar-Kazerooni, E.; Lijster, G.; Wouw, N. van de; Nijmeijer, H.
2015-01-01
Cooperative adaptive cruise control (CACC) employs wireless intervehicle communication, in addition to onboard sensors, to obtain string-stable vehicle-following behavior at small intervehicle distances. As a consequence, however, CACC is vulnerable to communication impairments such as latency and
Adaptive filtering prediction and control
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
Adaptive hybrid control of manipulators
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.
Adaptive control of robotic manipulators
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.
Malfunction diagnosis and applications of stable adaptive schemes for a nuclear reactor system
International Nuclear Information System (INIS)
Fukuda, Toshio; Shibata, Heki.
1979-01-01
Malfunction diagnosis concerns a method to detect the abnormal phenomena during nuclear reactor operations, while stable adaptive schemes does the application of Model Reference Adaptive System (MRAS) to the nonlinear dynamics of a reactor for parameter identification and control. The new method for the malfunction diagnosis consists of the following ideas; an index defined as the sum of ratios of the square of a factor score to the contribution weight of the factor, which is evaluated by applying the multi-factor analysis technique to the data of the state of nuclear reactor systems like neutron flux, temperature, flow rate and so on. The excess of the index over some given threshold shows the reactor system would be in an abnormal state. Then a theory of optimal filtering by Kalman with the aid of the stochastic approximation is applied to estimate the neutron flux distribution at its abnormal state and subsequently the squared sum of difference between desirable and estimated flux distributions shows the spot at which the abnormal phenomena would have occurred in terms of the peak of its distribution. Parameter identification and adaptive control schemes are presented for a point reactor and a loosely-coupled-core reactor with internal feedbacks which lead to the nonlinearity of the overall system. Both schemes are shown stable with new representations of the systems, which correspond to the nonminimal system representation, in the vein of the MRAS via the Lyapunov's method. For the sake of the parameter identification, model parameters can be adjusted adaptively as soon as measurements start, while plant parameters can also adaptively be compensated through control input to reduce the output error between the model and the plant for the case of the adaptive control. Some experiments of parameter identification for the thermal-hydraulic system are carried out successfully using a simplified channel in which flow rate is varied in a binary form. (J.P.N.)
Adaptive Augmenting Control and Launch Vehicle Adaptive Control Flight Experiments
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...
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)....
Maritime adaptive optics beam control
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...
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.
Adaptive Control Of Remote Manipulator
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.
Hybrid Adaptive Flight Control with Model Inversion Adaptation
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.
Controlling smart grid adaptivity
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
Dynamics and control of twisting bi-stable structures
Arrieta, Andres F.; van Gemmeren, Valentin; Anderson, Aaron J.; Weaver, Paul M.
2018-02-01
Compliance-based morphing structures have the potential to offer large shape adaptation, high stiffness and low weight, while reducing complexity, friction, and scalability problems of mechanism based systems. A promising class of structure that enables these characteristics are multi-stable structures given their ability to exhibit large deflections and rotations without the expensive need for continuous actuation, with the latter only required intermittently. Furthermore, multi-stable structures exhibit inherently fast response due to the snap-through instability governing changes between stable states, enabling rapid configuration switching between the discrete number of programmed shapes of the structure. In this paper, the design and utilisation of the inherent nonlinear dynamics of bi-stable twisting I-beam structures for actuation with low strain piezoelectric materials is presented. The I-beam structure consists of three compliant components assembled into a monolithic single element, free of moving parts, and showing large deflections between two stable states. Finite element analysis is utilised to uncover the distribution of strain across the width of the flange, guiding the choice of positioning for piezoelectric actuators. In addition, the actuation authority is maximised by calculating the generalised coupling coefficient for different positions of the piezoelectric actuators. The results obtained are employed to tailor and test I-beam designs exhibiting desired large deflection between stable states, while still enabling the activation of snap-through with the low strain piezoelectric actuators. To this end, the dynamic response of the I-beams to piezoelectric excitation is investigated, revealing that resonant excitations are insufficient to dynamically trigger snap-through. A novel bang-bang control strategy, which exploits the nonlinear dynamics of the structure successfully triggers both single and constant snap-through between the stable states
Adaptive governance : Towards a stable, accountable and responsive government
Janssen, M.F.W.H.A.; van der Voort, H.G.
2016-01-01
Organizations are expected to adapt within a short time to deal with changes that might become disruptive if not adequately dealt with. Yet many organizations are unable to adapt effectively or quickly due to the established institutional arrangements and patterns of decision-making and
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...
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
Adaptive control of port-Hamiltonian systems
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
Adaptive Controller Effects on Pilot Behavior
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.
Stable controller reconfiguration through terminal connections
DEFF Research Database (Denmark)
Trangbæk, K; Stoustrup, Jakob; Bendtsen, Jan Dimon
2008-01-01
Often, when new sensor and/or actuator hardware becomes available for use in a control system, it is desirable to retain the existing controllers and apply the new control capabilities in a gradual, online fashion rather than decommissioning the entire existing system and replacing it with the ne...
Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model
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.
Stable Controller Reconfiguration through Terminal Connections
DEFF Research Database (Denmark)
Trangbæk, K; Bendtsen, Jan Dimon
2009-01-01
system from scratch again, it is often desirable to retain the existing control system in place and phase the new parts in gradually. This paper presents a method for introducing new control components in a smooth manner, providing stability guarantees during the transition phase, and retaining...
Disturbance Accommodating Adaptive Control with Application to Wind Turbines
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.
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.
Flight Test Approach to Adaptive Control Research
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.
Adaptive control method for core power control in TRIGA Mark II reactor
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.
An adaptive Cartesian control scheme for manipulators
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.
Direct adaptive control using feedforward neural networks
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...
How stable 'should' epigenetic modifications be? Insights from adaptive plasticity and bet hedging.
Herman, Jacob J; Spencer, Hamish G; Donohue, Kathleen; Sultan, Sonia E
2014-03-01
Although there is keen interest in the potential adaptive value of epigenetic variation, it is unclear what conditions favor the stability of these variants either within or across generations. Because epigenetic modifications can be environmentally sensitive, existing theory on adaptive phenotypic plasticity provides relevant insights. Our consideration of this theory suggests that stable maintenance of environmentally induced epigenetic states over an organism's lifetime is most likely to be favored when the organism accurately responds to a single environmental change that subsequently remains constant, or when the environmental change cues an irreversible developmental transition. Stable transmission of adaptive epigenetic states from parents to offspring may be selectively favored when environments vary across generations and the parental environment predicts the offspring environment. The adaptive value of stability beyond a single generation of parent-offspring transmission likely depends on the costs of epigenetic resetting. Epigenetic stability both within and across generations will also depend on the degree and predictability of environmental variation, dispersal patterns, and the (epi)genetic architecture underlying phenotypic responses to environment. We also discuss conditions that favor stability of random epigenetic variants within the context of bet hedging. We conclude by proposing research directions to clarify the adaptive significance of epigenetic stability. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
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.
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.
Active Fault Tolerant Control of Livestock Stable Ventilation System
DEFF Research Database (Denmark)
Gholami, Mehdi
2011-01-01
Modern stables and greenhouses are equipped with different components for providing a comfortable climate for animals and plant. A component malfunction may result in loss of production. Therefore, it is desirable to design a control system, which is stable, and is able to provide an acceptable d...... are not included, while due to the physical limitation, the input signal can not have any value. In continuing, a passive fault tolerant controller (PFTC) based on state feedback is proposed to track a reference signal while the control inputs are bounded....... of fault. Designing a fault tolerant control scheme for the climate control system. In the first step, a conceptual multi-zone model for climate control of a live-stock building is derived. The model is a nonlinear hybrid model. Hybrid systems contain both discrete and continuous components. The parameters...... affine (PWA) components such as dead-zones, saturation, etc or contain piecewise nonlinear models which is the case for the climate control systems of the stables. Fault tolerant controller (FTC) is based on a switching scheme between a set of predefined passive fault tolerant controller (PFTC...
Dynamic optimization and adaptive controller design
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.
Adaptive Control Methods for Soft Robots
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...
Commande floue adaptative directe stable étendue appliquée à la ...
African Journals Online (AJOL)
Administrateur
... Machine asynchrone- Systèmes flous- Commande par logique floue- Commande adaptative- lois adaptative floue- analyse de stabilité- fonction de Lyapunov. Abstract. Today, as a result of significant progress in thearea of control of electrical machines, new techniques and approaches have emerged. In order nonlinear ...
Quantum Transduction with Adaptive Control
Zhang, Mengzhen; Zou, Chang-Ling; Jiang, Liang
2018-01-01
Quantum transducers play a crucial role in hybrid quantum networks. A good quantum transducer can faithfully convert quantum signals from one mode to another with minimum decoherence. Most investigations of quantum transduction are based on the protocol of direct mode conversion. However, the direct protocol requires the matching condition, which in practice is not always feasible. Here we propose an adaptive protocol for quantum transducers, which can convert quantum signals without requiring the matching condition. The adaptive protocol only consists of Gaussian operations, feasible in various physical platforms. Moreover, we show that the adaptive protocol can be robust against imperfections associated with finite squeezing, thermal noise, and homodyne detection, and it can be implemented to realize quantum state transfer between microwave and optical modes.
Quantum Transduction with Adaptive Control.
Zhang, Mengzhen; Zou, Chang-Ling; Jiang, Liang
2018-01-12
Quantum transducers play a crucial role in hybrid quantum networks. A good quantum transducer can faithfully convert quantum signals from one mode to another with minimum decoherence. Most investigations of quantum transduction are based on the protocol of direct mode conversion. However, the direct protocol requires the matching condition, which in practice is not always feasible. Here we propose an adaptive protocol for quantum transducers, which can convert quantum signals without requiring the matching condition. The adaptive protocol only consists of Gaussian operations, feasible in various physical platforms. Moreover, we show that the adaptive protocol can be robust against imperfections associated with finite squeezing, thermal noise, and homodyne detection, and it can be implemented to realize quantum state transfer between microwave and optical modes.
Embedded Controller Design for Pig Stable Ventilation Systems
DEFF Research Database (Denmark)
Jessen, Jan Jacob
This thesis focuses on zone based climate control in pig stables and how to implement climate controllers in a new range of products. The presented controllers are based on simple models of climate dynamics and simple models of actuators. The implementation uses graphical point and click features....... The thesis is a collection of eight papers. The first two papers deal with the mplementation of controllers and how to integrate the development of controllers into a complete framework that can provide different services e.g. remote monitoring. The same framework is also capable of automatically generating...
Robust chaos synchronization using input-to-state stable control
Indian Academy of Sciences (India)
In this paper, we propose a new input-to-state stable (ISS) synchronization method for a general class of chaotic systems with disturbances. Based on Lyapunov theory and linear matrix inequality (LMI) approach, for the first time, the ISS synchronization controller is presented not only to guarantee the asymptotic ...
Adaptive Dynamic Programming for Control Algorithms and Stability
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
2013-01-01
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
Adaptive servo control for umbilical mating
Zia, Omar
1988-01-01
Robotic applications at Kennedy Space Center are unique and in many cases require the fime positioning of heavy loads in dynamic environments. Performing such operations is beyond the capabilities of an off-the-shelf industrial robot. Therefore Robotics Applications Development Laboratory at Kennedy Space Center has put together an integrated system that coordinates state of the art robotic system providing an excellent easy to use testbed for NASA sensor integration experiments. This paper reviews the ways of improving the dynamic response of the robot operating under force feedback with varying dynamic internal perturbations in order to provide continuous stable operations under variable load conditions. The goal is to improve the stability of the system with force feedback using the adaptive control feature of existing system over a wide range of random motions. The effect of load variations on the dynamics and the transfer function (order or values of the parameters) of the system has been investigated, more accurate models of the system have been determined and analyzed.
Adaptive Flight Control Research at NASA
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.
Adaptive fuzzy PID control of hydraulic servo control system for large axial flow compressor
Wang, Yannian; Wu, Peizhi; Liu, Chengtao
2017-09-01
To improve the stability of the large axial compressor, an efficient and special intelligent hydraulic servo control system is designed and implemented. The adaptive fuzzy PID control algorithm is used to control the position of the hydraulic servo cylinder steadily, which overcomes the drawback that the PID parameters should be adjusted based on the different applications. The simulation and the test results show that the system has a better dynamic property and a stable state performance.
Multiple model adaptive control with mixing
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
An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation
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.
Development of adaptive control applied to chaotic systems
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.
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...
Adaptive change in corporate control practices.
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.
Full Gradient Solution to Adaptive Hybrid Control
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.
Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification
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.
Fault tolerancy in cooperative adaptive cruise control
Nunen, E. van; Ploeg, J.; Medina, A.M.; Nijmeijer, H.
2013-01-01
Future mobility requires sound solutions in the field of fault tolerance in real-time applications amongst which Cooperative Adaptive Cruise Control (CACC). This control system cannot rely on the driver as a backup and is constantly active and therefore more prominent to the occurrences of faults
Modeling and (adaptive) control of greenhouse climates
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
Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.
Wei, Qinglai; Li, Benkai; Song, Ruizhuo
2018-04-01
In this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.
Factors controlling stable isotope composition of European precipitation
International Nuclear Information System (INIS)
Rozanski, K.; Sonntag, C.; Muennich, K.O.
1982-01-01
The seasonal and spatial variations of stable isotope ratios in present day European precipitation are simulated with a simple multibox model of the mean west-east horizontal transport of the atmospheric water vapour across the European continent. Isotope fractionation during the formation of precipitation leads to an increasing depletion of heavy isotopes in the residual air moisture as it moves towards the centre of the continent. This isotopic depletion is partly compensated, particularly in summer, by evapotranspiration, which is assumed to transfer soil water into the atmosphere without isotope fractionation. The model estimates are based on horizontal water vapour flux data, varying seasonally between 88 and 130 kg m -1 s -1 for the Atlantic coast region, and on the monthly precipitation, evapotranspiration and surface air temperature data available for various locations in Europe. Both continental and seasonal temperature effects observed in the stable isotope composition of European precipitation are fairly well reproduced by the model. The calculations show that the isotopic composition of local precipitation is primarily controlled by regional scale processes, i.e. by the water vapour transport patterns into the continent, and by the average precipitation-evapotranspiration history of the air masses precipitating at a given place. Local parameters such as the surface and/or cloud base temperature or the amount of precipitation modify the isotope ratios only slightly. Implications of the model predictions for the interpretation of stable isotope ratios in earlier periods as they are preserved in ice cores and in groundwater are also discussed. (Auth.)
Neuronal control of adaptive thermogenesis
Directory of Open Access Journals (Sweden)
Xiaoyong eYang
2015-09-01
Full Text Available The obesity epidemic continues rising as a global health challenge, despite the increasing public awareness and the use of lifestyle and medical interventions. The biomedical community is urged to develop new treatments to obesity. Excess energy is stored as fat in white adipose tissue (WAT, dysfunction of which lie at the core of obesity and associated metabolic disorders. In contrast, brown adipose tissue (BAT burns fat and dissipates chemical energy as heat. The development and activation of brown-like adipocytes, also known as beige cells, result in WAT browning and thermogenesis. The recent discovery of brown and beige adipocytes in adult humans has sparked the exploration of the development, regulation, and function of these thermogenic adipocytes. The central nervous system (CNS drives the sympathetic nerve activity in BAT and WAT to control heat production and energy homeostasis. This review provides an overview of the integration of thermal, hormonal, and nutritional information on hypothalamic circuits in thermoregulation.
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.
Designing a stable feedback control system for blind image deconvolution.
Cheng, Shichao; Liu, Risheng; Fan, Xin; Luo, Zhongxuan
2018-05-01
Blind image deconvolution is one of the main low-level vision problems with wide applications. Many previous works manually design regularization to simultaneously estimate the latent sharp image and the blur kernel under maximum a posterior framework. However, it has been demonstrated that such joint estimation strategies may lead to the undesired trivial solution. In this paper, we present a novel perspective, using a stable feedback control system, to simulate the latent sharp image propagation. The controller of our system consists of regularization and guidance, which decide the sparsity and sharp features of latent image, respectively. Furthermore, the formational model of blind image is introduced into the feedback process to avoid the image restoration deviating from the stable point. The stability analysis of the system indicates the latent image propagation in blind deconvolution task can be efficiently estimated and controlled by cues and priors. Thus the kernel estimation used for image restoration becomes more precision. Experimental results show that our system is effective on image propagation, and can perform favorably against the state-of-the-art blind image deconvolution methods on different benchmark image sets and special blurred images. Copyright © 2018 Elsevier Ltd. All rights reserved.
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...
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
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.
Bayesian nonparametric adaptive control using Gaussian processes.
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.
Fourier transform wavefront control with adaptive prediction of the atmosphere.
Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre
2007-09-01
Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.
Adaptive control of solar energy collector systems
Lemos, João M; Igreja, José M
2014-01-01
This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts
Reactive gas control of non-stable plasma conditions
International Nuclear Information System (INIS)
Bellido-Gonzalez, V.; Daniel, B.; Counsell, J.; Monaghan, D.
2006-01-01
Most industrial plasma processes are dependant upon the control of plasma properties for repeatable and reliable production. The speed of production and range of properties achieved depend on the degree of control. Process control involves all the aspects of the vacuum equipment, substrate preparation, plasma source condition, power supplies, process drift, valves (inputs/outputs), signal and data processing and the user's understanding and ability. In many cases, some of the processes which involve the manufacturing of interesting coating structures, require a precise control of the process in a reactive environment [S.J. Nadel, P. Greene, 'High rate sputtering technology for throughput and quality', International Glass Review, Issue 3, 2001, p. 45. ]. Commonly in these circumstances the plasma is not stable if all the inputs and outputs of the system were to remain constant. The ideal situation is to move a process from set-point A to B in zero time and maintain the monitored signal with a fluctuation equal to zero. In a 'real' process that's not possible but improvements in the time response and energy delivery could be achieved with an appropriate algorithm structure. In this paper an advanced multichannel reactive plasma gas control system is presented. The new controller offers both high-speed gas control combined with a very flexible control structure. The controller uses plasma emission monitoring, target voltage or any process sensor monitoring as the input into a high-speed control algorithm for gas input. The control algorithm and parameters can be tuned to different process requirements in order to optimize response times
Adaptive Critic Nonlinear Robust Control: A Survey.
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.
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
Cooperative adaptive cruise control : tradeoffs between control and network specifications
Oncu, S.; Wouw, van de N.; Nijmeijer, H.
2011-01-01
In this study, we consider a Cooperative Adaptive Cruise Control (CACC) system which regulates inter-vehicle distances in a vehicle string. Improved performance can be achieved by utilizing information exchange between vehicles through wireless communication besides local sensor measurements.
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 ...
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.
Robust and Adaptive Control With Aerospace Applications
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 ...
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.
Indirect adaptive control of discrete chaotic systems
International Nuclear Information System (INIS)
Salarieh, Hassan; Shahrokhi, Mohammad
2007-01-01
In this paper an indirect adaptive control algorithm is proposed to stabilize the fixed points of discrete chaotic systems. It is assumed that the functionality of the chaotic dynamics is known but the system parameters are unknown. This assumption is usually applicable to many chaotic systems, such as the Henon map, logistic and many other nonlinear maps. Using the recursive-least squares technique, the system parameters are identified and based on the feedback linearization method an adaptive controller is designed for stabilizing the fixed points, or unstable periodic orbits of the chaotic maps. The stability of the proposed scheme has been shown and the effectiveness of the control algorithm has been demonstrated through computer simulations
Neural network-based model reference adaptive control system.
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.
Adaptive Control with Reference Model Modification
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
Tip-over Prevention: Adaptive Control Development
2015-05-30
Tip-over Prevention: Adaptive Control Development Leah Kelley Massachusetts Institute of Technology Cambridge, MA 02139 Email: lckelley@mit.edu Kurt...Papadopoulos and D. Rey, Proc. IEEE ICRA, vol.4, 1996, pp. 3111. [7] S. Ali, A. Moosavian, and K. Alipour, Robotics, Automation and Mechatronics , 2006 IEEE Conf...on, 2006, pp. 1–6. [8] K. Talke, L. Kelley, P. Longhini, and G. Catron, Proc. SPIE 9084, Unmanned Systems Technology XVI, June 2014, pp. 90 840L–11
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.
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.
Development of a microprocessor-controlled coulometric system for stable ph control
Bergveld, Piet; van der Schoot, B.H.
1983-01-01
The coulometric pH control system utilizes a programmable coulostat for controlling the pH of a certain volume of unbuffered solution. Based on theoretical considerations, conditions are established which guarantee stable operation with maximum suppression of disturbances from the dissolution of
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.
Adaptive H∞ synchronization of chaotic systems via linear and nonlinear feedback control
International Nuclear Information System (INIS)
Fu Shi-Hui; Lu Qi-Shao; Du Ying
2012-01-01
Adaptive H ∞ synchronization of chaotic systems via linear and nonlinear feedback control is investigated. The chaotic systems are redesigned by using the generalized Hamiltonian systems and observer approach. Based on Lyapunov's stability theory, linear and nonlinear feedback control of adaptive H ∞ synchronization is established in order to not only guarantee stable synchronization of both master and slave systems but also reduce the effect of external disturbance on an H ∞ -norm constraint. Adaptive H ∞ synchronization of chaotic systems via three kinds of control is investigated with applications to Lorenz and Chen systems. Numerical simulations are also given to identify the effectiveness of the theoretical analysis. (general)
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.
Robust adaptive control for Unmanned Aerial Vehicles
Kahveci, Nazli E.
The objective of meeting higher endurance requirements remains a challenging task for any type and size of Unmanned Aerial Vehicles (UAVs). According to recent research studies significant energy savings can be realized through utilization of thermal currents. The navigation strategies followed across thermal regions, however, are based on rather intuitive assessments of remote pilots and lack any systematic path planning approaches. Various methods to enhance the autonomy of UAVs in soaring applications are investigated while seeking guarantees for flight performance improvements. The dynamics of the aircraft, small UAVs in particular, are affected by the environmental conditions, whereas unmodeled dynamics possibly become significant during aggressive flight maneuvers. Besides, the demanded control inputs might have a magnitude range beyond the limits dictated by the control surface actuators. The consequences of ignoring these issues can be catastrophic. Supporting this claim NASA Dryden Flight Research Center reports considerable performance degradation and even loss of stability in autonomous soaring flight tests with the subsequent risk of an aircraft crash. The existing control schemes are concluded to suffer from limited performance. Considering the aircraft dynamics and the thermal characteristics we define a vehicle-specific trajectory optimization problem to achieve increased cross-country speed and extended range of flight. In an environment with geographically dispersed set of thermals of possibly limited lifespan, we identify the similarities to the Vehicle Routing Problem (VRP) and provide both exact and approximate guidance algorithms for the navigation of automated UAVs. An additional stochastic approach is used to quantify the performance losses due to incorrect thermal data while dealing with random gust disturbances and onboard sensor measurement inaccuracies. One of the main contributions of this research is a novel adaptive control design with
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.
A Methodology for Investigating Adaptive Postural Control
McDonald, P. V.; Riccio, G. E.
1999-01-01
Our research on postural control and human-environment interactions provides an appropriate scientific foundation for understanding the skill of mass handling by astronauts in weightless conditions (e.g., extravehicular activity or EVA). We conducted an investigation of such skills in NASA's principal mass-handling simulator, the Precision Air-Bearing Floor, at the Johnson Space Center. We have studied skilled movement-body within a multidisciplinary context that draws on concepts and methods from biological and behavioral sciences (e.g., psychology, kinesiology and neurophysiology) as well as bioengineering. Our multidisciplinary research has led to the development of measures, for manual interactions between individuals and the substantial environment, that plausibly are observable by human sensory systems. We consider these methods to be the most important general contribution of our EVA investigation. We describe our perspective as control theoretic because it draws more on fundamental concepts about control systems in engineering than it does on working constructs from the subdisciplines of biomechanics and motor control in the bio-behavioral sciences. At the same time, we have attempted to identify the theoretical underpinnings of control-systems engineering that are most relevant to control by human beings. We believe that these underpinnings are implicit in the assumptions that cut across diverse methods in control-systems engineering, especially the various methods associated with "nonlinear control", "fuzzy control," and "adaptive control" in engineering. Our methods are based on these theoretical foundations rather than on the mathematical formalisms that are associated with particular methods in control-systems engineering. The most important aspects of the human-environment interaction in our investigation of mass handling are the functional consequences that body configuration and stability have for the pick up of information or the achievement of
Adaptive control of a Stewart platform-based manipulator
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.
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.
Mechanosensation and Adaptive Motor Control in Insects.
Tuthill, John C; Wilson, Rachel I
2016-10-24
The ability of animals to flexibly navigate through complex environments depends on the integration of sensory information with motor commands. The sensory modality most tightly linked to motor control is mechanosensation. Adaptive motor control depends critically on an animal's ability to respond to mechanical forces generated both within and outside the body. The compact neural circuits of insects provide appealing systems to investigate how mechanical cues guide locomotion in rugged environments. Here, we review our current understanding of mechanosensation in insects and its role in adaptive motor control. We first examine the detection and encoding of mechanical forces by primary mechanoreceptor neurons. We then discuss how central circuits integrate and transform mechanosensory information to guide locomotion. Because most studies in this field have been performed in locusts, cockroaches, crickets, and stick insects, the examples we cite here are drawn mainly from these 'big insects'. However, we also pay particular attention to the tiny fruit fly, Drosophila, where new tools are creating new opportunities, particularly for understanding central circuits. Our aim is to show how studies of big insects have yielded fundamental insights relevant to mechanosensation in all animals, and also to point out how the Drosophila toolkit can contribute to future progress in understanding mechanosensory processing. Copyright © 2016 Elsevier Ltd. All rights reserved.
Error-controlled adaptive finite elements in solid mechanics
National Research Council Canada - National Science Library
Stein, Erwin; Ramm, E
2003-01-01
... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Error-controlled Adaptive Finite-element-methods . . . . . . . . . . . . Missing Features and Properties of Today's General Purpose FE Programs for Structural...
Adaptive Control Using Residual Mode Filters Applied to Wind Turbines
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.
Adaptive tracking control of nonholonomic systems: an example
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
Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems
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.
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.
Stable Myoelectric Control of a Hand Prosthesis using Non-Linear Incremental Learning
Directory of Open Access Journals (Sweden)
Arjan eGijsberts
2014-02-01
Full Text Available Stable myoelectric control of hand prostheses remains an open problem. The only successful human-machine interface is surface electromyography, typically allowing control of a few degrees of freedom. Machine learning techniques may have the potential to remove these limitations, but their performance is thus far inadequate: myoelectric signals change over time under the influence of various factors, deteriorating control performance. It is therefore necessary, in the standard approach, to regularly retrain a new model from scratch.We hereby propose a non-linear incremental learning method in which occasional updates with a modest amount of novel training data allow continual adaptation to the changes in the signals. In particular, Incremental Ridge Regression and an approximation of the Gaussian Kernel known as Random Fourier Features are combined to predict finger forces from myoelectric signals, both finger-by-finger and grouped in grasping patterns.We show that the approach is effective and practically applicable to this problem by first analyzing its performance while predicting single-finger forces. Surface electromyography and finger forces were collected from 10 intact subjects during four sessions spread over two different days; the results of the analysis show that small incremental updates are indeed effective to maintain a stable level of performance.Subsequently, we employed the same method on-line to teleoperate a humanoid robotic arm equipped with a state-of-the-art commercial prosthetic hand. The subject could reliably grasp, carry and release everyday-life objects, enforcing stable grasping irrespective of the signal changes, hand/arm movements and wrist pronation and supination.
An implicit adaptation algorithm for a linear model reference control system
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.
Stereoscopic-3D display design: a new paradigm with Intel Adaptive Stable Image Technology [IA-SIT
Jain, Sunil
2012-03-01
Stereoscopic-3D (S3D) proliferation on personal computers (PC) is mired by several technical and business challenges: a) viewing discomfort due to cross-talk amongst stereo images; b) high system cost; and c) restricted content availability. Users expect S3D visual quality to be better than, or at least equal to, what they are used to enjoying on 2D in terms of resolution, pixel density, color, and interactivity. Intel Adaptive Stable Image Technology (IA-SIT) is a foundational technology, successfully developed to resolve S3D system design challenges and deliver high quality 3D visualization at PC price points. Optimizations in display driver, panel timing firmware, backlight hardware, eyewear optical stack, and synch mechanism combined can help accomplish this goal. Agnostic to refresh rate, IA-SIT will scale with shrinking of display transistors and improvements in liquid crystal and LED materials. Industry could profusely benefit from the following calls to action:- 1) Adopt 'IA-SIT S3D Mode' in panel specs (via VESA) to help panel makers monetize S3D; 2) Adopt 'IA-SIT Eyewear Universal Optical Stack' and algorithm (via CEA) to help PC peripheral makers develop stylish glasses; 3) Adopt 'IA-SIT Real Time Profile' for sub-100uS latency control (via BT Sig) to extend BT into S3D; and 4) Adopt 'IA-SIT Architecture' for Monitors and TVs to monetize via PC attach.
Thermotropic and Thermochromic Polymer Based Materials for Adaptive Solar Control
Directory of Open Access Journals (Sweden)
Olaf Mühling
2010-12-01
Full Text Available The aim of this review is to present the actual status of development in adaptive solar control by use of thermotropic and organic thermochromic materials. Such materials are suitable for application in smart windows. In detail polymer blends, hydrogels, resins, and thermoplastic films with a reversible temperature-dependent switching behavior are described. A comparative evaluation of the concepts for these energy efficient materials is given as well. Furthermore, the change of strategy from ordinary shadow systems to intrinsic solar energy reflection materials based on phase transition components and a first remark about their realization is reported. Own current results concerning extruded films and high thermally stable casting resins with thermotropic properties make a significant contribution to this field.
Directory of Open Access Journals (Sweden)
Mingyue Cui
2016-09-01
Full Text Available A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown wheels’ slipping. The longitudinal and lateral slipping are considered and processed as three time-varying parameters. The adaptive unscented Kalman filter is then designed to estimate the slipping parameters online, an adaptive adjustment of the noise covariances in the estimation process is implemented using a technique of covariance matching in the adaptive unscented Kalman filter context. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov stability theory. Control gains are determined online by applying pole placement method. Simulation and real experiment results show the effectiveness and robustness of the proposed control method.
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.
Adaptive neural network motion control for aircraft under uncertainty conditions
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.
Adaptive nonlinear control for a research reactor
International Nuclear Information System (INIS)
Benitez R, J.S.
1994-01-01
Linearization by feedback of states is based on the idea of transform the nonlinear dynamic equation of a system in a linear form. This linear behavior can be achieve well in a complete way (input state) or in partial way (input output). This can be applied to systems of single or multiple inputs, and can be used to solve problems of stabilization and tracking of references trajectories. Comparing this method with conventional ones, linearization by feedback of states is exact in certain region of the space of state, instead of linear approximations of the equations in a certain point of the operation. In the presence of parametric uncertainties in the model of the system, the introduction of adaptive schemes provide a type toughness to the control system by nonlinear feedback, which gives as result the eventual cancellation of the nonlinear terms in the dynamic relationship between the output and the input of the auxiliary control. In the same way, it has been presented the design of a nonlinearizing control for the non lineal model of a TRIGA Mark III type reactor, with the aim of tracking a predetermined power profile. The asymptotic tracking of such profile is, at the present moment, in the stage of verification by computerized simulation the relative easiness in the design of auxiliary variable of control, as well as the decoupling action of the output variable, make very attractive the utilization of the method herein presented. (Author)
Adaptive powertrain control for plugin hybrid electric vehicles
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.
Biofeedback systems and adaptive control hemodialysis treatment
Directory of Open Access Journals (Sweden)
Azar Ahmad
2008-01-01
Full Text Available On-line monitoring devices to control functions such as volume, body temperature, and ultrafiltration, were considered more toys than real tools for routine clinical application. However, bio-feedback blood volume controlled hemodialysis (HD is now possible in routine dialysis, allowing the delivery of a more physiologically acceptable treatment. This system has proved to reduce the incidence of intra-HD hypotension episodes significantly. Ionic dialysance and the patient′s plasma conductivity can be calculated easily from on-line measurements at two different steps of dialysate conductivity. A bio-feedback system has been devised to calculate the patient′s plasma conductivity and modulate the conductivity of the dialysate continuously in order to achieve a desired end-dialysis patient plasma conductivity corresponding to a desired end-dialysis plasma sodium concentration. Another bio-feedback system can control the body tempe-rature by measuring it at the arterial and venous lines of the extra-corporeal circuit, and then modulating the dialysate temperature in order to stabilize the patients′ temperature at constant values that result in improved intra-HD cardiovascular stability. The module can also be used to quantify vascular access recirculation. Finally, the simultaneous computer control of ultrafiltration has proven the most effective means for automatic blood pressure stabilization during hemo-dialysis treatment. The application of fuzzy logic in the blood-pressure-guided biofeedback con-trol of ultrafiltration during hemodialysis is able to minimize HD-induced hypotension. In con-clusion, online monitoring and adaptive control of the patient during the dialysis session using the bio-feedback systems is expected to render the process of renal replacement therapy more physiological and less eventful.
Direct adaptive control of manipulators in Cartesian space
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.
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.
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.
Revisionist integral deferred correction with adaptive step-size control
Christlieb, Andrew; Macdonald, Colin; Ong, Benjamin; Spiteri, Raymond
2015-01-01
© 2015 Mathematical Sciences Publishers. Adaptive step-size control is a critical feature for the robust and efficient numerical solution of initial-value problems in ordinary differential equations. In this paper, we show that adaptive step
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.
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.
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....
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.
Adaptive Controller Design for Continuous Stirred Tank Reactor
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...
International Nuclear Information System (INIS)
Tai, Nguyen Trong; Ahn, Kyoung Kwan
2011-01-01
In this paper, a novel adaptive sliding mode control with a proportional–integral–derivative (PID) tuning method is proposed to control a shape memory alloy (SMA) actuator. The goal of the controller is to achieve system robustness against the SMA hysteresis phenomenon, system uncertainties and external disturbances. In the controller, the PID controller is employed to approximate the sliding mode equivalent control along the direction that makes the sliding mode asymptotically stable. Due to the system nonlinearity, the PID control gain parameters are systematically computed online according to the adaptive law. To improve the transient performance, the initial PID gain parameters are optimized by the particle swarm optimization (PSO) method. Simulation and experimental results demonstrate that the controller performs well for the desired trajectory tracking, and the hysteresis phenomenon is compensated for completely. The control results are also compared with the optimized PID controller
Active structural control with stable fuzzy PID techniques
Yu, Wen
2016-01-01
This book presents a detailed discussion of intelligent techniques to measure the displacement of buildings when they are subjected to vibration. It shows how these techniques are used to control active devices that can reduce vibration 60–80% more effectively than widely used passive anti-seismic systems. After introducing various structural control devices and building-modeling and active structural control methods, the authors propose offset cancellation and high-pass filtering techniques to solve some common problems of building-displacement measurement using accelerometers. The most popular control algorithms in industrial settings, PD/PID controllers, are then analyzed and then combined with fuzzy compensation. The stability of this combination is proven with standard weight-training algorithms. These conditions provide explicit methods for selecting PD/PID controllers. Finally, fuzzy-logic and sliding-mode control are applied to the control of wind-induced vibration. The methods described are support...
Modular and Adaptive Control of Sound Processing
van Nort, Douglas
parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.
Feedback control of Zero Moment Point for stable bipedal walking
Looij, van de R.M.A.; Nijmeijer, H.; Kostic, D.
2014-01-01
In order to prevent the humanoid robot TUlip from falling a start has been made with a Zero Moment Point (ZMP) based controller. The chosen controller, which is called the Linear Inverted Pendulum Tracker (LIPT) controller, is based upon a lag between the real and reference ZMP and is used in
Robust chaos synchronization using input-to-state stable control
Indian Academy of Sciences (India)
... be obtained by solving a convex optimization problem represented by the. LMI. Simulation studies are presented to demonstrate the effectiveness of the proposed ... one is the linear state feedback controller and the other is the nonlinear feedback controller. By the proposed control scheme, the closed-loop error system is ...
A stable-manifold-based method for chaos control and synchronization
International Nuclear Information System (INIS)
Chen Shihua; Zhang Qunjiao; Xie Jin; Wang Changping
2004-01-01
A stable-manifold-based method is proposed for chaos control and synchronization. The novelty of this new and effective method lies in that, once the suitable stable manifold according to the desired dynamic properties is constructed, the goal of control is only to force the system state to lie on the selected stable manifold because once the stable manifold is reached, the chaotic system will be guided towards the desired target. The effectiveness of the approach and idea is tested by stabilizing the Newton-Leipnik chaotic system which possesses more than one strange attractor and by synchronizing the unified chaotic system which unifies both the Lorenz system and the Chen system
Neural network based adaptive control for nonlinear dynamic regimes
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.
Design of a stable fuzzy controller for an articulated vehicle.
Tanaka, K; Kosaki, T
1997-01-01
This paper presents a backward movement control of an articulated vehicle via a model-based fuzzy control technique. A nonlinear dynamic model of the articulated vehicle is represented by a Takagi-Sugeno fuzzy model. The concept of parallel distributed compensation is employed to design a fuzzy controller from the Takagi-Sugeno fuzzy model of the articulated vehicle. Stability of the designed fuzzy control system is guaranteed via Lyapunov approach. The stability conditions are characterized in terms of linear matrix inequalities since the stability analysis is reduced to a problem of finding a common Lyapunov function for a set of Lyapunov inequalities. Simulation results and experimental results show that the designed fuzzy controller effectively achieves the backward movement control of the articulated vehicle.
Reducing adapter synthesis to controller synthesis
Gierds, C.; Mooij, A.J.; Wolf, K.
2012-01-01
Service-oriented computing aims to create complex systems by composing less-complex systems, called services. Since services can be developed independently, the integration of services requires an adaptation mechanism for bridging any incompatibilities. Behavioral adapters aim to adjust the
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.
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.
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...
Applications of adaptive filters in active noise control
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.
Adaptive Intelligent Ventilation Noise Control, Phase II
National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
Adaptive Intelligent Ventilation Noise Control, Phase I
National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
Enhanced vaccine control of epidemics in adaptive networks
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.
Fuzzy adaptive speed control of a permanent magnet synchronous motor
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.
From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.
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.
Monitoring the Performance of a Neuro-Adaptive Controller
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.
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
Adaptive Backstepping Flight Control for Modern Fighter Aircraft
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,
Nonlinear adaptive inverse control via the unified model neural network
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.
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.
Cooperative adaptive cruise control, design and experiments
Naus, G.J.L.; Vugts, R.P.A.; Ploeg, J.; Molengraft, van de M.J.G.; Steinbuch, M.
2010-01-01
The design of a CACC system and corresponding experiments are presented. The design targets string stable system behavior, which is assessed using a frequency-domain-based approach. Following this approach, it is shown that the available wireless information enables small inter-vehicle distances,
Continuous use of an adaptive lung ventilation controller in critically ...
African Journals Online (AJOL)
1995-05-05
May 5, 1995 ... Adaptive lung ventilation (ALV) refers to closed-loop mechanical ventilation designed to work ... optimise the controller performance, the volume controller .... PawEE), vital capacity IYC), an index of airway resistance relative to ...
Connection adaption for control of networked mobile chaotic agents.
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.
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)
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...
A new approach to adaptive control of manipulators
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.
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
International Nuclear Information System (INIS)
Zhang Yun-Peng; Duan Hai-Bin; Zhang Xiang-Yin
2011-01-01
A novel distributed control scheme to generate stable flocking motion for a group of agents is proposed. In this control scheme, a molecular potential field model is applied as the potential field function because of its smoothness and unique shape. The approach of distributed receding horizon control is adopted to drive each agent to find its optimal control input to lower its potential at every step. Experimental results show that this proposed control scheme can ensure that all agents eventually converge to a stable flocking formation with a common velocity and the collisions can also be avoided at the same time. (general)
Adaptive fuzzy PID control for a quadrotor stabilisation
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.
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...
Projection Operator: A Step Towards Certification of Adaptive Controllers
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.
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.
Directory of Open Access Journals (Sweden)
Xiuchun Li
2013-01-01
Full Text Available When the parameters of both drive and response systems are all unknown, an adaptive sliding mode controller, strongly robust to exotic perturbations, is designed for realizing generalized function projective synchronization. Sliding mode surface is given and the controlled system is asymptotically stable on this surface with the passage of time. Based on the adaptation laws and Lyapunov stability theory, an adaptive sliding controller is designed to ensure the occurrence of the sliding motion. Finally, numerical simulations are presented to verify the effectiveness and robustness of the proposed method even when both drive and response systems are perturbed with external disturbances.
International Nuclear Information System (INIS)
Bazyka, D.A.; Chumak, A.A.; Bebeshko, V.G.; Beliaeva, N.V.
1997-01-01
Early changes of immune parameters in children evacuated from 30-km zone were characterized by E-rossette forming cells decrease and E-receptor non-stability in theophylline assay, surface Ig changes. Immunological follow-up of children inhabitants of territories contaminated with radionuclides after Chernobyl accident revealed TCR/CD3, CD4 and MHC CD3+, CD4+, CD57+ subsets, RIL-2, TrT expression and calcium channel activity. PMNC percentage with cortical thymocyte phenotype (CD1+, CD4+8+) was elevated during the first years after the accident and seemed to be of a compensatory origin. Combination of heterogenic activation and suppression subset reactions and changes in fine subset (Th1/Th2) organization were suggested. Adaptive and compensatory reactions were supposed and delayed hypersensitivity reactions increase as well. (author)
Fully probabilistic control design in an adaptive critic framework
Czech Academy of Sciences Publication Activity Database
Herzallah, R.; Kárný, Miroslav
2011-01-01
Roč. 24, č. 10 (2011), s. 1128-1135 ISSN 0893-6080 R&D Projects: GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : Stochastic control design * Fully probabilistic design * Adaptive control * Adaptive critic Subject RIV: BC - Control Systems Theory Impact factor: 2.182, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/karny-0364820.pdf
Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous Vehicles
2007-11-01
Tolerant Overactuated Autonomous Vehicles Casavola, A.; Garone, E. (2007) Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous ...Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous Vehicles 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Tolerant Overactuated Autonomous Vehicles 3.2 - 2 RTO-MP-AVT-145 UNCLASSIFIED/UNLIMITED Control allocation problem (CAP) - Given a virtual input v(t
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)
Revisionist integral deferred correction with adaptive step-size control
Christlieb, Andrew
2015-03-27
© 2015 Mathematical Sciences Publishers. Adaptive step-size control is a critical feature for the robust and efficient numerical solution of initial-value problems in ordinary differential equations. In this paper, we show that adaptive step-size control can be incorporated within a family of parallel time integrators known as revisionist integral deferred correction (RIDC) methods. The RIDC framework allows for various strategies to implement stepsize control, and we report results from exploring a few of them.
Applications of Adaptive Learning Controller to Synthetic Aperture Radar.
1985-02-01
TERMS (Continue on retuerse if necessary and identify by block num ber) FIELD YGROUP SUB. GR. Adaptive control, aritificial intelligence , synthetic aetr1...application of Artificial Intelligence methods to Synthetic Aperture Radars (SARs) is investigated. It was shown that the neuron-like Adaptive Learning...wavelength Al SE!RI M RADAR DIVISION REFERENCES 1. Barto, A.G. and R.S. Sutton, Goal Seeking Components for Adaptive Intelligence : An Initial Assessment
Adaptive optimization and control using neural networks
Energy Technology Data Exchange (ETDEWEB)
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
1993-10-22
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
An integration time adaptive control method for atmospheric composition detection of occultation
Ding, Lin; Hou, Shuai; Yu, Fei; Liu, Cheng; Li, Chao; Zhe, Lin
2018-01-01
When sun is used as the light source for atmospheric composition detection, it is necessary to image sun for accurate identification and stable tracking. In the course of 180 second of the occultation, the magnitude of sun light intensity through the atmosphere changes greatly. It is nearly 1100 times illumination change between the maximum atmospheric and the minimum atmospheric. And the process of light change is so severe that 2.9 times per second of light change can be reached. Therefore, it is difficult to control the integration time of sun image camera. In this paper, a novel adaptive integration time control method for occultation is presented. In this method, with the distribution of gray value in the image as the reference variable, and the concepts of speed integral PID control, the integration time adaptive control problem of high frequency imaging. The large dynamic range integration time automatic control in the occultation can be achieved.
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
Adaptive hybrid optimal quantum control for imprecisely characterized systems.
Egger, D J; Wilhelm, F K
2014-06-20
Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful.
Adaptive integral robust control and application to electromechanical servo systems.
Deng, Wenxiang; Yao, Jianyong
2017-03-01
This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
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)
Adaptive Automation Based on Air Traffic Controller Decision-Making
IJtsma (Student TU Delft), Martijn; Borst, C.; Mercado Velasco, G.A.; Mulder, M.; van Paassen, M.M.; Tsang, P.S.; Vidulich, M.A.
2017-01-01
Through smart scheduling and triggering of automation support, adaptive automation has the potential to balance air traffic controller workload. The challenge in the design of adaptive automation systems is to decide how and when the automation should provide support. This paper describes the design
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
Adaptive Tracking and Obstacle Avoidance Control for Mobile Robots with Unknown Sliding
Directory of Open Access Journals (Sweden)
Mingyue Cui
2012-11-01
Full Text Available An adaptive control approach is proposed for trajectory tracking and obstacle avoidance for mobile robots with consideration given to unknown sliding. A kinematic model of mobile robots is established in this paper, in which both longitudinal and lateral sliding are considered and processed as three time-varying parameters. A sliding model observer is introduced to estimate the sliding parameters online. A stable tracking control law for this nonholonomic system is proposed to compensate the unknown sliding effect. From Lyapunov-stability analysis, it is proved, regardless of unknown sliding, that tracking errors of the controlled closed-loop system are asymptotically stable, the tracking errors converge to zero outside the obstacle detection region and obstacle avoidance is guaranteed inside the obstacle detection region. The efficiency and robustness of the proposed control system are verified by simulation results.
Basic Research on Adaptive Model Algorithmic Control
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
Lange, G.; Haynert, K.; Dinter, T.; Scheu, S.; Kröncke, I.
2018-01-01
Frequent environmental changes and abiotic gradients of the Wadden Sea require appropriate adaptations of the local organisms and make it suitable for investigations on functional structure of macrozoobenthic communities from marine to terrestrial boundaries. To investigate community patterns and food use of the macrozoobenthos, a transect of 11 stations was sampled for species number, abundance and stable isotope values (δ13C and δ15N) of macrozoobenthos and for stable isotope values of potential food resources. The transect was located in the back-barrier system of the island of Spiekeroog (southern North Sea, Germany). Our results show that surface and subsurface deposit feeders, such as Peringia ulvae and different oligochaete species, dominated the community, which was poor in species, while species present at the transect stations reached high abundance. The only exception was the upper salt marsh with low abundances but higher species richness because of the presence of specialized semi-terrestrial and terrestrial taxa. The macrozoobenthos relied predominantly on marine resources irrespective of the locality in the intertidal zone, although δ13C values of the consumers decreased from - 14.1 ± 1.6‰ (tidal flats) to - 21.5 ± 2.4‰ (salt marsh). However, the ubiquitous polychaete Hediste diversicolor showed a δ15N enrichment of 2.8‰ (an increase of about one trophic level) from bare sediments to the first vegetated transect station, presumably due to switching from suspension or deposit feeding to predation on smaller invertebrates. Hence, we conclude that changes in feeding mode represent an important mechanism of adaptation to different Wadden Sea habitats.
Adaptive control in series load PWM induction heating inverters
Szelitzky, Tibor; Henrietta Dulf, Eva
2013-12-01
Permanent variations of the electric properties of the load in induction heating equipment make difficult to control the plant. To overcome these disadvantages, the authors propose a new approach based on adaptive control methods. For real plants it is enough to present desired performances or start-up variables for the controller, from which the algorithms tune the controllers by itself. To present the advantages of the proposed controllers, comparisons are made to a PI controller tuned through Ziegler-Nichols method.
Novel hybrid adaptive controller for manipulation in complex perturbation environments.
Directory of Open Access Journals (Sweden)
Alex M C Smith
Full Text Available In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.
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...
Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation
National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...
Adaptive control and synchronization of a fractional-order chaotic ...
Indian Academy of Sciences (India)
Fractional order; adaptive scheme; control; synchronization. ... College of Physics and Electronics, Hunan Institute of Science and Technology, ... of Information and Communication Engineering, Hunan Institute of Science and Technology, ...
Analysis of Postural Control Adaptation During Galvanic and Vibratory Stimulation
National Research Council Canada - National Science Library
Fransson, P
2001-01-01
The objective for this study was to investigate whether the postural control adaptation during galvanic stimulation of the vestibular nerve were similar to that found during vibration stimulation to the calf muscles...
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.
Lifetime Maximizing Adaptive Power Control in Wireless Sensor Networks
National Research Council Canada - National Science Library
Sun, Fangting; Shayman, Mark
2006-01-01
...: adaptive power control. They focus on the sensor networks that consist of a sink and a set of homogeneous wireless sensor nodes, which are randomly deployed according to a uniform distribution...
High Efficiency Lighting with Integrated Adaptive Control (HELIAC), Phase II
National Aeronautics and Space Administration — The proposed project is the continued development of the High Efficiency Lighting with Integrated Adaptive Control (HELIAC) system. Solar radiation is not a viable...
High Efficiency Lighting with Integrated Adaptive Control (HELIAC), Phase I
National Aeronautics and Space Administration — The innovation of the proposed project is the development of High Efficiency Lighting with Integrated Adaptive Control (HELIAC) systems to drive plant growth. Solar...
Integrated Damage-Adaptive Control System (IDACS), Phase I
National Aeronautics and Space Administration — SSCI, in collaboration with Boeing Phantom Works, proposes to develop and test an efficient Integrated Damage Adaptive Control System (IDACS). The proposed system is...
Real-Time Application Performance Steering and Adaptive Control
National Research Council Canada - National Science Library
Reed, Daniel
2002-01-01
.... The objective of the Real-time Application Performance Steering and Adaptive Control project is to replace ad hoc, post-mortem performance optimization with an extensible, portable, and distributed...
Vehicle-to-infrastructure program cooperative adaptive cruise control.
2015-03-01
This report documents the work completed by the Crash Avoidance Metrics Partners LLC (CAMP) Vehicle to Infrastructure (V2I) Consortium during the project titled Cooperative Adaptive Cruise Control (CACC). Participating companies in the V2I Cons...
Control and adaptation in telecommunication systems mathematical foundations
Popovskij, Vladimir; Titarenko, Larysa
2011-01-01
This book is devoted to mathematical foundations providing synthesis and analysis of control and adaptation algorithms targeting modern telecommunication systems (TCS). The most popular technologies and network management methods are discussed.
Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping
2018-02-01
In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.
Scenario design : adaptive architecture for command and control experiment eight
Clark, Frankie J.
2002-01-01
Approved for public release; distribution is unlimited. The Adaptive Architectures for Command and Control (A2C2) project is an ongoing research effort sponsored by the Office of Naval Research to explore adaptation in joint command and control. The objective of the project's eighth experiment is to study the adjustments that organizations make when they are confronted with a scenario for which their organizational is ill-suited. To accomplish this, teams will each be in one of two fundame...
Scalable Harmonization of Complex Networks With Local Adaptive Controllers
Czech Academy of Sciences Publication Activity Database
Kárný, Miroslav; Herzallah, R.
2017-01-01
Roč. 47, č. 3 (2017), s. 394-404 ISSN 2168-2216 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Adaptive control * Adaptive estimation * Bayes methods * Complex networks * Decentralized control * Fee dback * Fee dforward systems * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 2.350, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0457337.pdf
Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty
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.
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.
Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center
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.
Simple adaptive control for quadcopters with saturated actuators
Borisov, Oleg I.; Bobtsov, Alexey A.; Pyrkin, Anton A.; Gromov, Vladislav S.
2017-01-01
The stabilization problem for quadcopters with saturated actuators is considered. A simple adaptive output control approach is proposed. The control law "consecutive compensator" is augmented with the auxiliary integral loop and anti-windup scheme. Efficiency of the obtained regulator was confirmed by simulation of the quadcopter control problem.
Adaptive lighting controllers using smart sensors
Papantoniou, Sotiris; Kolokotsa, Denia; Kalaitzakis, Kostas; Cesarini, Davide Nardi; Cubi, Eduard; Cristalli, Cristina
2016-07-01
The aim of this paper is to present an advanced controller for artificial lights evaluated in several rooms in two European Hospitals located in Chania, Greece and Ancona, Italy. Fuzzy techniques have been used for the architecture of the controller. The energy efficiency of the controllers has been calculated by running the controller coupled with validated models of the RADIANCE back-wards ray tracing software. The input of the controller is the difference between the current illuminance value and the desired one, while the output is the change of the light level that should be applied in the artificial lights. Simulation results indicate significant energy saving potentials. Energy saving potential is calculated from the comparison of the current use of the artificial lights by the users and the proposed one. All simulation work has been conducted using Matlab and RADIANCE environment.
Adaptive pitch control for load mitigation of wind turbines
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.
Biancani, Leann M.; Flight, Patrick A.; Nacci, Diane E.; Rand, David M.; Crawford, Douglas L.; Oleksiak, Marjorie F.
2018-01-01
Populations of the non-migratory estuarine fish Fundulus heteroclitus inhabiting the heavily polluted New Bedford Harbour (NBH) estuary have shown inherited tolerance to local pollutants introduced to their habitats in the past 100 years. Here we examine two questions: (i) Is there pollution-driven selection on the mitochondrial genome across a fine geographical scale? and (ii) What is the pattern of migration among sites spanning a strong pollution gradient? Whole mitochondrial genomes were analysed for 133 F. heteroclitus from seven nearby collection sites: four sites along the NBH pollution cline (approx. 5 km distance), which had pollution-adapted fish, as well as one site adjacent to the pollution cline and two relatively unpolluted sites about 30 km away, which had pollution-sensitive fish. Additionally, we used microsatellite analyses to quantify genetic variation over three F. heteroclitus generations in both pollution-adapted and sensitive individuals collected from two sites at two different time points (1999/2000 and 2007/2008). Our results show no evidence for a selective sweep of mtDNA in the polluted sites. Moreover, mtDNA analyses revealed that both pollution-adapted and sensitive populations harbour similar levels of genetic diversity. We observed a high level of non-synonymous mutations in the most polluted site. This is probably associated with a reduction in Ne and concomitant weakening of purifying selection, a demographic expansion following a pollution-related bottleneck or increased mutation rates. Our demographic analyses suggest that isolation by distance influences the distribution of mtDNA genetic variation between the pollution cline and the clean populations at broad spatial scales. At finer scales, population structure is patchy, and neither spatial distance, pollution concentration or pollution tolerance is a good predictor of mtDNA variation. Lastly, microsatellite analyses revealed stable population structure over the last
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.
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.
Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System.
Wang, Ning; Er, Meng Joo; Sun, Jing-Chao; Liu, Yan-Cheng
2016-07-01
In this paper, a novel adaptive robust online constructive fuzzy control (AR-OCFC) scheme, employing an online constructive fuzzy approximator (OCFA), to deal with tracking surface vehicles with uncertainties and unknown disturbances is proposed. Significant contributions of this paper are as follows: 1) unlike previous self-organizing fuzzy neural networks, the OCFA employs decoupled distance measure to dynamically allocate discriminable and sparse fuzzy sets in each dimension and is able to parsimoniously self-construct high interpretable T-S fuzzy rules; 2) an OCFA-based dominant adaptive controller (DAC) is designed by employing the improved projection-based adaptive laws derived from the Lyapunov synthesis which can guarantee reasonable fuzzy partitions; 3) closed-loop system stability and robustness are ensured by stable cancelation and decoupled adaptive compensation, respectively, thereby contributing to an auxiliary robust controller (ARC); and 4) global asymptotic closed-loop system can be guaranteed by AR-OCFC consisting of DAC and ARC and all signals are bounded. Simulation studies and comprehensive comparisons with state-of-the-arts fixed- and dynamic-structure adaptive control schemes demonstrate superior performance of the AR-OCFC in terms of tracking and approximation accuracy.
Adaptive Controller for Drive System PMSG in Wind Turbine
Gnanambal; G.Balaji; M.Abinaya
2014-01-01
This paper proposes adaptive Maximum Power Point Tracking (MPPT) controller for Permanent Magnet Synchronous Generator (PMSG) wind turbine and direct power control for grid side inverter for transformer less integration of wind energy. PMSG wind turbine with two back to back voltage source converters are considered more efficient, used to make real and reactive power control. The optimal control strategy has introduced for integrated control of PMSG Maximum Power Extraction, DC li...
National Research Council Canada - National Science Library
Lukesh, Gordon
2004-01-01
.... Pointing estimates are available after 25 shots. As a prime example of the utility and feasibility, estimates of boresight will be available to adaptively control pointing with a goal of boresight reduction via feedback...
Research on the adaptive optical control technology based on DSP
Zhang, Xiaolu; Xue, Qiao; Zeng, Fa; Zhao, Junpu; Zheng, Kuixing; Su, Jingqin; Dai, Wanjun
2018-02-01
Adaptive optics is a real-time compensation technique using high speed support system for wavefront errors caused by atmospheric turbulence. However, the randomness and instantaneity of atmospheric changing introduce great difficulties to the design of adaptive optical systems. A large number of complex real-time operations lead to large delay, which is an insurmountable problem. To solve this problem, hardware operation and parallel processing strategy are proposed, and a high-speed adaptive optical control system based on DSP is developed. The hardware counter is used to check the system. The results show that the system can complete a closed loop control in 7.1ms, and improve the controlling bandwidth of the adaptive optical system. Using this system, the wavefront measurement and closed loop experiment are carried out, and obtain the good results.
Adaptive Feedfoward Feedback Control Framework, Phase I
National Aeronautics and Space Administration — A novel approach is proposed for the suppression of the aircraft's structural vibration to increase the resilience of the flight control law in the presence of the...
Towards an adaptive model for greenhouse control
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,
Design of an adaptable nonlinear controller
International Nuclear Information System (INIS)
Benitez R, J.S.
1994-01-01
The study of the behavior of a nuclear reactor is of great importance as it allows to know a priori the conditions at which a reactor is submitted. In the sareactor are the design and simulation of control algorithms based on the theories of modern control with the objective of improving improving the performance criterions as well as to guarantee the the stability of the retrofitting system. (author)
Substantiation of Structure of Adaptive Control Systems for Motor Units
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.
Decentralized adaptive control of manipulators - Theory, simulation, and experimentation
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.
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.
Hybrid adaptive ascent flight control for a flexible launch vehicle
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
Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network
Directory of Open Access Journals (Sweden)
Kazuhiko Hiramoto
2018-01-01
Full Text Available We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance. In order to design a semiactive control system with high control performance against earthquakes with different time and/or frequency properties, multiple semiactive control laws with high performance for each of multiple earthquake disturbances are scheduled with an adaptive manner. Each semiactive control law to be scheduled is designed based on the output emulation approach that has been proposed by the authors. As the adaptive gain scheduling mechanism, we introduce an artificial neural network (ANN. Input signals of the ANN are the measured earthquake disturbance itself, for example, the acceleration, velocity, and displacement. The output of the ANN is the parameter for the scheduling of multiple semiactive control laws each of which has been optimized for a single disturbance. Parameters such as weight and bias in the ANN are optimized by the genetic algorithm (GA. The proposed design method is applied to semiactive control design of a base-isolated building with a semiactive damper. With simulation study, the proposed adaptive gain scheduling method realizes control performance exceeding single semiactive control optimizing the average of the control performance subject to various earthquake disturbances.
Hussein, Sami; Kruger, Jörg
2011-01-01
Robot assisted training has proven beneficial as an extension of conventional therapy to improve rehabilitation outcome. Further facilitation of this positive impact is expected from the application of cooperative control algorithms to increase the patient's contribution to the training effort according to his level of ability. This paper presents an approach for cooperative training for end-effector based gait rehabilitation devices. Thereby it provides the basis to firstly establish sophisticated cooperative control methods in this class of devices. It uses a haptic control framework to synthesize and render complex, task specific training environments, which are composed of polygonal primitives. Training assistance is integrated as part of the environment into the haptic control framework. A compliant window is moved along a nominal training trajectory compliantly guiding and supporting the foot motion. The level of assistance is adjusted via the stiffness of the moving window. Further an iterative learning algorithm is used to automatically adjust this assistance level. Stable haptic rendering of the dynamic training environments and adaptive movement assistance have been evaluated in two example training scenarios: treadmill walking and stair climbing. Data from preliminary trials with one healthy subject is provided in this paper. © 2011 IEEE
Stable Hovering Flight for a Small Unmanned Helicopter Using Fuzzy Control
Directory of Open Access Journals (Sweden)
Arbab Nighat Khizer
2014-01-01
Full Text Available Stable hover flight control for small unmanned helicopter under light air turbulent environment is presented. Intelligent fuzzy logic is chosen because it is a nonlinear control technique based on expert knowledge and is capable of handling sensor created noise and contradictory inputs commonly encountered in flight control. The fuzzy nonlinear control utilizes these distinct qualities for attitude, height, and position control. These multiple controls are developed using two-loop control structure by first designing an inner-loop controller for attitude angles and height and then by establishing outer-loop controller for helicopter position. The nonlinear small unmanned helicopter model used comes from X-Plane simulator. A simulation platform consisting of MATLAB/Simulink and X-Plane© flight simulator was introduced to implement the proposed controls. The main objective of this research is to design computationally intelligent control laws for hovering and to test and analyze this autopilot for small unmanned helicopter model on X-Plane under ideal and mild turbulent condition. Proposed fuzzy flight controls are validated using an X-Plane helicopter model before being embedded on actual helicopter. To show the effectiveness of the proposed fuzzy control method and its ability to cope with the external uncertainties, results are compared with a classical PD controller. Simulated results show that two-loop fuzzy controllers have a good ability to establish stable hovering for a class of unmanned rotorcraft in the presence of light turbulent environment.
ADAPTIVE CONTROL SYSTEM OF INDUSTRIAL REACTORS
Directory of Open Access Journals (Sweden)
Vyacheslav K. Mayevski
2014-01-01
Full Text Available This paper describes a mathematical model of an industrial chemical reactor for production of synthetic rubber. During reactor operation the model parameters vary considerably. To create a control algorithm performed transformation of mathematical model of the reactor in order to obtain a dependency that can be used to determine the model parameters are changing during reactor operation.
Adaptive gaze control for object detection
De Croon, G.C.H.E.; Postma, E.O.; Van den Herik, H.J.
2011-01-01
We propose a novel gaze-control model for detecting objects in images. The model, named act-detect, uses the information from local image samples in order to shift its gaze towards object locations. The model constitutes two main contributions. The first contribution is that the model’s setup makes
Directory of Open Access Journals (Sweden)
Jian Liu
Full Text Available In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic systems (CVCSs in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
Liu, Jian; Liu, Kexin; Liu, Shutang
2017-01-01
In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
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.
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
Direct adaptive control of a PUMA 560 industrial robot
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.
GÖKCE, Kürşad; UYAROĞLU, Yılmaz
2013-01-01
This paper proposes a feedforward neural network-based control scheme to control the chaotic trajectories of a discrete-Hénon map in order to stay within an acceptable distance from the stable fixed point. An adaptive learning back propagation algorithm with online training is employed to improve the effectiveness of the proposed method. The simulation study carried in the discrete-Hénon system verifies the validity of the proposed control system.
Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
Directory of Open Access Journals (Sweden)
Alejandro Carrasco Elizalde
2008-01-01
Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.
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.
On Using Exponential Parameter Estimators with an Adaptive Controller
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.
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.
Adaptive Incentive Controls for Stackelberg Games with Unknown Cost Functionals.
1984-01-01
APR EZT:: F I AN 73S e OsL:-: UNCLASSI?:-- Q4~.’~- .A.., 6, *~*i i~~*~~*.- U ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH UNKNOWN COST...AD-A161 885 ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH i/1 UNKNOWN COST FUNCTIONALSCU) ILLINOIS UNIV AT URBANA DECISION AND CONTROL LAB T...ORGANIZATION 6b. OFFICE SYMBOL 7.. NAME OF MONITORING ORGANIZATION CoriaeLcenef~pda~ Joint Services Electronics Program Laboratory, Univ. of Illinois N/A
Adaptive control of chaotic continuous-time systems with delay
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.
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.
Adaptive active vibration isolation – A control perspective
Directory of Open Access Journals (Sweden)
Landau Ioan Doré
2015-01-01
The paper will review a number of recent developments for adaptive feedback compensation of multiple unknown and time-varying narrow band disturbances and for adaptive feedforward compensation of broad band disturbances in the presence of the inherent internal positive feedback caused by the coupling between the compensator system and the measurement of the image of the disturbance. Some experimental results obtained on a relevant active vibration control system will illustrate the performance of the various algorithms presented.
Automated Merging in a Cooperative Adaptive Cruise Control (CACC) System
Klein Wolterink, W.; Heijenk, Geert; Karagiannis, Georgios
2011-01-01
Cooperative Adaptive Cruise Control (CACC) is a form of cruise control in which a vehicle maintains a constant headway to its preceding vehicle using radar and vehicle-to-vehicle (V2V) communication. Within the Connect & Drive1 project we have implemented and tested a prototype of such a system,
Automated Merging in a Cooperative Adaptive Cruise Control (CACC) System
Klein Wolterink, W.; Karagiannis, Georgios; Brogle, Marc; Masip Bruin, Xavier; Braun, Torsten; Heijenk, Gerhard J.
Cooperative Adaptive Cruise Control (CACC) is a form of cruise control in which a vehicle maintains a constant headway to its preceding vehicle using radar and vehicle-to-vehicle (V2V) communication. Within the Connect & Drive1 project we have implemented and tested a prototype of such a system,
Adaptive Control of Wind Turbines for Maximum Power Point Tracking
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei
2018-01-01
induction generator (SCIG) is used to illustrate the generator control system for a variable‐speed WECS. The chapter also presents case studies have been carried out to verify the developed adaptive controller for WECSs. WECSs are non‐linear systems with parameter uncertainties and which are subject...... to disturbances, in the form of non‐linear and unmodeled aerodynamics....
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 ...
Adaptive decoupled power control method for inverter connected DG
DEFF Research Database (Denmark)
Sun, Xiaofeng; Tian, Yanjun; Chen, Zhe
2014-01-01
an adaptive droop control method based on online evaluation of power decouple matrix for inverter connected distributed generations in distribution system. Traditional decoupled power control is simply based on line impedance parameter, but the load characteristics also cause the power coupling, and alter...
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...
Optimal adaptive control for a class of stochastic systems
Bagchi, Arunabha; Chen, Han-Fu
1995-01-01
We study linear-quadratic adaptive tracking problems for a special class of stochastic systems expressed in the state-space form. This is a long-standing problem in the control of aircraft flying through atmospheric turbulence. Using an ELS-based algorithm and introducing dither in the control law
Frequency Adaptability of Harmonics Controllers for Grid-Interfaced Converters
DEFF Research Database (Denmark)
Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede
2017-01-01
sensitivity of the most popular harmonic controllers for grid-interfaced converters. The frequency adaptability of these harmonic controllers is evaluated in the presence of a variable grid frequency within a specified reasonable range, e.g., +-1% of the nominal grid frequency (50 Hz). Solutions...
The Basal Ganglia and Adaptive Motor Control
Graybiel, Ann M.; Aosaki, Toshihiko; Flaherty, Alice W.; Kimura, Minoru
1994-09-01
The basal ganglia are neural structures within the motor and cognitive control circuits in the mammalian forebrain and are interconnected with the neocortex by multiple loops. Dysfunction in these parallel loops caused by damage to the striatum results in major defects in voluntary movement, exemplified in Parkinson's disease and Huntington's disease. These parallel loops have a distributed modular architecture resembling local expert architectures of computational learning models. During sensorimotor learning, such distributed networks may be coordinated by widely spaced striatal interneurons that acquire response properties on the basis of experienced reward.
Algebraic and adaptive learning in neural control systems
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.
Adaptive landing gear concept—feedback control validation
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.
Shared Care in Monitoring Stable Glaucoma Patients: A Randomized Controlled Trial
Holtzer-Goor, Kim M.; van Vliet, Ellen J.; van Sprundel, Esther; Plochg, Thomas; Koopmanschap, Marc A.; Klazinga, Niek S.; Lemij, Hans G.
2016-01-01
Comparing the quality of care provided by a hospital-based shared care glaucoma follow-up unit with care as usual. This randomized controlled trial included stable glaucoma patients and patients at risk for developing glaucoma. Patients in the Usual Care group (n=410) were seen by glaucoma
Insufficient control of heart rate in stable coronary artery disease patients in Latvia
Directory of Open Access Journals (Sweden)
Inga Balode
2014-01-01
Conclusions: Despite the wide use of beta-blockers, HR is insufficiently controlled in the analyzed sample of stable CAD patients in Latvia. Target HR ≤60 bpm is achieved only in 25% of the patients while more than one third have increased HR ≥70 bpm.
VLSI PARTITIONING ALGORITHM WITH ADAPTIVE CONTROL PARAMETER
Directory of Open Access Journals (Sweden)
P. N. Filippenko
2013-03-01
Full Text Available The article deals with the problem of very large-scale integration circuit partitioning. A graph is selected as a mathematical model describing integrated circuit. Modification of ant colony optimization algorithm is presented, which is used to solve graph partitioning problem. Ant colony optimization algorithm is an optimization method based on the principles of self-organization and other useful features of the ants’ behavior. The proposed search system is based on ant colony optimization algorithm with the improved method of the initial distribution and dynamic adjustment of the control search parameters. The experimental results and performance comparison show that the proposed method of very large-scale integration circuit partitioning provides the better search performance over other well known algorithms.
Development of fault tolerant adaptive control laws for aerospace systems
Perez Rocha, Andres E.
The main topic of this dissertation is the design, development and implementation of intelligent adaptive control techniques designed to maintain healthy performance of aerospace systems subjected to malfunctions, external parameter changes and/or unmodeled dynamics. The dissertation is focused on the development of novel adaptive control configurations that rely on non-linear functions that appear in the immune system of living organisms as main source of adaptation. One of the main goals of this dissertation is to demonstrate that these novel adaptive control architectures are able to improve overall performance and protect the system while reducing control effort and maintaining adequate operation outside bounds of nominal design. This research effort explores several phases, ranging from theoretical stability analysis, simulation and hardware implementation on different types of aerospace systems including spacecraft, aircraft and quadrotor vehicles. The results presented in this dissertation are focused on two main adaptivity approaches, the first one is intended for aerospace systems that do not attain large angles and use exact feedback linearization of Euler angle kinematics. A proof of stability is presented by means of the circle Criterion and Lyapunov's direct method. The second approach is intended for aerospace systems that can attain large attitude angles (e.g. space systems in gravity-less environments), the adaptation is incorporated on a baseline architecture that uses partial feedback linearization of quaternions kinematics. In this case, the closed loop stability was analyzed using Lyapunov's direct method and Barbalat's Lemma. It is expected that some results presented in this dissertation can contribute towards the validation and certification of direct adaptive controllers.
Directory of Open Access Journals (Sweden)
A. BENNASSAR
2016-01-01
Full Text Available Many industrial applications require high performance speed sensorless operation and demand new control methods in order to obtain fast dynamic response and insensitive to external disturbances. The current research aims to present the performance of the sensorless direct torque control (DTC of an induction motor (IM using adaptive Luenberger observer (ALO with fuzzy logic controller (FLC for adaptation mechanism. The rotor speed is regulated by proportional integral (PI anti-windup controller. The proposed strategy is directed to reduce the ripple on the torque and the flux. Numerical simulation results show the good performance and effectiveness of the proposed sensorless control for different references of the speed even both low and high speeds.
Directory of Open Access Journals (Sweden)
Yee-Pien Yang
2006-10-01
Full Text Available Periodic disturbance occurs in various applications on the control of the rotational mechanical systems. For optical disk drives, the spirally shaped tracks are usually not perfectly circular and the assembly of the disk and spindle motor is unavoidably eccentric. The resulting periodic disturbance is, therefore, synchronous with the disk rotation, and becomes particularly noticeable for the track following and focusing servo system. This paper applies a novel adaptive controller, namely Frequency Adaptive Control Technique (FACT, for rejecting the periodic runout and wobble effects in the optical disk drive with dual actuators. The control objective is to attenuate adaptively the specific frequency contents of periodic disturbances without amplifying its rest harmonics. FACT is implemented in a plug-in manner and provides a suitable framework for periodic disturbance rejection in the cases where the fundamental frequencies of the disturbance are alterable. It is shown that the convergence property of parameters in the proposed adaptive algorithm is exponentially stable. It is applicable to both the spindle modes of constant linear velocity (CLV and constant angular velocity (CAV for various operation speeds. The experiments showed that the proposed FACT has successful improvement on the tracking and focusing performance of the CD-ROM, and is extended to various compact disk drives.
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
A discrete-time adaptive control scheme for robot manipulators
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.
An adaptable Boolean net trainable to control a computing robot
International Nuclear Information System (INIS)
Lauria, F. E.; Prevete, R.; Milo, M.; Visco, S.
1999-01-01
We discuss a method to implement in a Boolean neural network a Hebbian rule so to obtain an adaptable universal control system. We start by presenting both the Boolean neural net and the Hebbian rule we have considered. Then we discuss, first, the problems arising when the latter is naively implemented in a Boolean neural net, second, the method consenting us to overcome them and the ensuing adaptable Boolean neural net paradigm. Next, we present the adaptable Boolean neural net as an intelligent control system, actually controlling a writing robot, and discuss how to train it in the execution of the elementary arithmetic operations on operands represented by numerals with an arbitrary number of digits
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
Adaptive Backstepping Control of Lightweight Tower Wind Turbine
DEFF Research Database (Denmark)
Galeazzi, Roberto; Borup, Kasper Trolle; Niemann, Hans Henrik
2015-01-01
the angular deflection of the tower with respect to the vertical axis in response to variations in wind speed. The controller is shown to guarantee asymptotic tracking of the reference trajectory. The performance of the control system is evaluated through deterministic and stochastic simulations including......This paper investigates the feasibility of operating a wind turbine with lightweight tower in the full load region exploiting an adaptive nonlinear controller that allows the turbine to dynamically lean against the wind while maintaining nominal power output. The use of lightweight structures...... for towers and foundations would greatly reduce the construction cost of the wind turbine, however extra features ought be included in the control system architecture to avoid tower collapse. An adaptive backstepping collective pitch controller is proposed for tower point tracking control, i.e. to modify...
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.
Robust Optimal Adaptive Trajectory Tracking Control of Quadrotor Helicopter
Directory of Open Access Journals (Sweden)
M. Navabi
Full Text Available Abstract This paper focuses on robust optimal adaptive control strategy to deal with tracking problem of a quadrotor unmanned aerial vehicle (UAV in presence of parametric uncertainties, actuator amplitude constraints, and unknown time-varying external disturbances. First, Lyapunov-based indirect adaptive controller optimized by particle swarm optimization (PSO is developed for multi-input multi-output (MIMO nonlinear quadrotor to prevent input constraints violation, and then disturbance observer-based control (DOBC technique is aggregated with the control system to attenuate the effects of disturbance generated by an exogenous system. The performance of synthesis control method is evaluated by a new performance index function in time-domain, and the stability analysis is carried out using Lyapunov theory. Finally, illustrative numerical simulations are conducted to demonstrate the effectiveness of the presented approach in altitude and attitude tracking under several conditions, including large time-varying uncertainty, exogenous disturbance, and control input constraints.
Multi-Model Adaptive Fuzzy Controller for a CSTR Process
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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.
Adaptive mechanism-based congestion control for networked systems
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.
L1 Adaptive Control for a Vertical Rotor Orientation System
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Sijia Liu
2016-08-01
Full Text Available Bottom-fixed vertical rotating devices are widely used in industrial and civilian fields. The free upside of the rotor will cause vibration and lead to noise and damage during operation. Meanwhile, parameter uncertainties, nonlinearities and external disturbances will further deteriorate the performance of the rotor. Therefore, in this paper, we present a rotor orientation control system based on an active magnetic bearing with L 1 adaptive control to restrain the influence of the nonlinearity and uncertainty and reduce the vibration amplitude of the vertical rotor. The boundedness and stability of the adaptive system are analyzed via a theoretical derivation. The impact of the adaptive gain is discussed through simulation. An experimental rig based on dSPACE is designed to test the validity of the rotor orientation system. The experimental results show that the relative vibration amplitude of the rotor using the L 1 adaptive controller will be reduced to ∼50% of that in the initial state, which is a 10% greater reduction than can be achieved with the nonadaptive controller. The control approach in this paper is of some significance to solve the orientation control problem in a low-speed vertical rotor with uncertainties and nonlinearities.
Bayesian selective response-adaptive design using the historical control.
Kim, Mi-Ok; Harun, Nusrat; Liu, Chunyan; Khoury, Jane C; Broderick, Joseph P
2018-06-13
High quality historical control data, if incorporated, may reduce sample size, trial cost, and duration. A too optimistic use of the data, however, may result in bias under prior-data conflict. Motivated by well-publicized two-arm comparative trials in stroke, we propose a Bayesian design that both adaptively incorporates historical control data and selectively adapt the treatment allocation ratios within an ongoing trial responsively to the relative treatment effects. The proposed design differs from existing designs that borrow from historical controls. As opposed to reducing the number of subjects assigned to the control arm blindly, this design does so adaptively to the relative treatment effects only if evaluation of cumulated current trial data combined with the historical control suggests the superiority of the intervention arm. We used the effective historical sample size approach to quantify borrowed information on the control arm and modified the treatment allocation rules of the doubly adaptive biased coin design to incorporate the quantity. The modified allocation rules were then implemented under the Bayesian framework with commensurate priors addressing prior-data conflict. Trials were also more frequently concluded earlier in line with the underlying truth, reducing trial cost, and duration and yielded parameter estimates with smaller standard errors. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons, Ltd.
Adaptive control system having hedge unit and related apparatus and methods
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.
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....
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.
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
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.
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.
International Nuclear Information System (INIS)
Mehrasa, Majid; Pouresmaeil, Edris; Mehrjerdi, Hasan; Jørgensen, Bo Nørregaard; Catalão, João P.S.
2015-01-01
Highlights: • A control technique for enhancing the stable operation of distributed generation units is proposed. • Passivity-based control technique is considered to analyze the dynamic and steady-state behaviors. • The compensation of instantaneous variations in the reference current components is considered. • Simulation results confirm the performance of the control scheme within the microgrid. - Abstract: This paper describes a control technique for enhancing the stable operation of distributed generation (DG) units based on renewable energy sources, during islanding and grid-connected modes. The Passivity-based control technique is considered to analyze the dynamic and steady-state behaviors of DG units during integration and power sharing with loads and/or power grid, which is an appropriate tool to analyze and define a stable operating condition for DG units in microgrid technology. The compensation of instantaneous variations in the reference current components of DG units in ac-side, and dc-link voltage variations in dc-side of interfaced converters, are considered properly in the control loop of DG units, which is the main contribution and novelty of this control technique over other control strategies. By using the proposed control technique, DG units can provide the continuous injection of active power from DG sources to the local loads and/or utility grid. Moreover, by setting appropriate reference current components in the control loop of DG units, reactive power and harmonic current components of loads can be supplied during the islanding and grid-connected modes with a fast dynamic response. Simulation results confirm the performance of the control scheme within the microgrid during dynamic and steady-state operating conditions
Second-order sliding mode controller with model reference adaptation for automatic train operation
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.
Design of a self-adaptive fuzzy PID controller for piezoelectric ceramics micro-displacement system
Zhang, Shuang; Zhong, Yuning; Xu, Zhongbao
2008-12-01
In order to improve control precision of the piezoelectric ceramics (PZT) micro-displacement system, a self-adaptive fuzzy Proportional Integration Differential (PID) controller is designed based on the traditional digital PID controller combining with fuzzy control. The arithmetic gives a fuzzy control rule table with the fuzzy control rule and fuzzy reasoning, through this table, the PID parameters can be adjusted online in real time control. Furthermore, the automatic selective control is achieved according to the change of the error. The controller combines the good dynamic capability of the fuzzy control and the high stable precision of the PID control, adopts the method of using fuzzy control and PID control in different segments of time. In the initial and middle stage of the transition process of system, that is, when the error is larger than the value, fuzzy control is used to adjust control variable. It makes full use of the fast response of the fuzzy control. And when the error is smaller than the value, the system is about to be in the steady state, PID control is adopted to eliminate static error. The problems of PZT existing in the field of precise positioning are overcome. The results of the experiments prove that the project is correct and practicable.
Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks
Jorgensen, Charles C.
1997-01-01
A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.
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.
Adaptive Feature Based Control of Compact Disk Players
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Stoustrup, Jakob; Vidal, Enrique Sanchez
2005-01-01
Many have experienced the problem that their Compact Disc players have difficulties playing Compact Discs with surface faults like scratches and fingerprints. The cause of this is due to the two servo control loops used to keep the Optical Pick-up Unit focused and radially on the information track...... of the Compact Disc. The problem is to design servo controllers which are well suited for handling surface faults which disturb the position measurement and still react sufficiently against normal disturbances like mechanical shocks. In previous work of the same authors a feature based control scheme for CD......-players playing CDs with surface fault is derived and described. This feature based control scheme uses precomputed base to remove the surface fault influence from the position measurements. In this paper an adaptive version of the feature based control scheme is proposed and described. This adaptive scheme can...
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.
Directory of Open Access Journals (Sweden)
Robert W Snow
2008-07-01
Full Text Available The international financing of malaria control has increased significantly in the last ten years in parallel with calls to halve the malaria burden by the year 2015. The allocation of funds to countries should reflect the size of the populations at risk of infection, disease, and death. To examine this relationship, we compare an audit of international commitments with an objective assessment of national need: the population at risk of stable Plasmodium falciparum malaria transmission in 2007.The national distributions of populations at risk of stable P. falciparum transmission were projected to the year 2007 for each of 87 P. falciparum-endemic countries. Systematic online- and literature-based searches were conducted to audit the international funding commitments made for malaria control by major donors between 2002 and 2007. These figures were used to generate annual malaria funding allocation (in US dollars per capita population at risk of stable P. falciparum in 2007. Almost US$1 billion are distributed each year to the 1.4 billion people exposed to stable P. falciparum malaria risk. This is less than US$1 per person at risk per year. Forty percent of this total comes from the Global Fund to Fight AIDS, Tuberculosis and Malaria. Substantial regional and national variations in disbursements exist. While the distribution of funds is found to be broadly appropriate, specific high population density countries receive disproportionately less support to scale up malaria control. Additionally, an inadequacy of current financial commitments by the international community was found: under-funding could be from 50% to 450%, depending on which global assessment of the cost required to scale up malaria control is adopted.Without further increases in funding and appropriate targeting of global malaria control investment it is unlikely that international goals to halve disease burdens by 2015 will be achieved. Moreover, the additional financing
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.
Model-free adaptive control of advanced power plants
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.
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.
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
DEFF Research Database (Denmark)
Alphinas, Robert A.; Hansen, Hans Henrik; Tambo, Torben
2017-01-01
Non-adaptive proportional controllers suffer from the ability to handle a system disturbance leading to a large steady-state error and undesired transient behavior. On the other hand, they are easy to implement and tune. This article examines whether an adaptive controller based on the MIT...
Continuous control of asymmetric forebody vortices in a bi-stable state
Wang, Qi-te; Cheng, Ke-ming; Gu, Yun-song; Li, Zhuo-qi
2018-02-01
Aiming at the problem of continuous control of asymmetric forebody vortices at a high angle of attack in a bi-stable regime, a dual synthetic jet actuator embedded in an ogive forebody was designed. Alternating unsteady disturbance with varying degree asymmetrical flow fields near the nozzles is generated by adjusting the duty cycle of the drive signal of the actuator, specifically embodying the asymmetric time-averaged pattern of jet velocity, vorticity, and turbulent kinetic energy. Experimental results show that within the range of relatively high angles of attack, including the angle-of-attack region in a bi-stable state, the lateral force of the ogive forebody is continuously controlled by adjusting the duty cycle of the drive signal; the position of the forebody vortices in space, the vorticity magnitude, the total pressure coefficient near the vortex core, and the vortex breakdown location are continuously changed with the duty cycle increased observed from the time-averaged flow field. Instantaneous flow field results indicate that although the forebody vortices are in an unsteady oscillation state, a continuous change in the forebody vortices' oscillation balance position as the duty cycle increases leads to a continuous change in the model's surface pressure distribution and time-averaged lateral force. Different from the traditional control principle, in this study, other different degree asymmetrical states of the forebody vortices except the bi-stable state are obtained using the dual synthetic jet control technology.
An adaptive robust controller for time delay maglev transportation systems
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.
Adaptive Wavelet Coding Applied in a Wireless Control System.
Gama, Felipe O S; Silveira, Luiz F Q; Salazar, Andrés O
2017-12-13
Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER) versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.
Adaptive Wavelet Coding Applied in a Wireless Control System
Directory of Open Access Journals (Sweden)
Felipe O. S. Gama
2017-12-01
Full Text Available Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.
Fei, Juntao; Lu, Cheng
2018-04-01
In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.
A 3D Fractional-Order Chaotic System with Only One Stable Equilibrium and Controlling Chaos
Directory of Open Access Journals (Sweden)
Shiyun Shen
2017-01-01
Full Text Available One 3D fractional-order chaotic system with only one locally asymptotically stable equilibrium is reported. To verify the chaoticity, the maximum Lyapunov exponent (MAXLE with respect to the fractional-order and chaotic attractors are obtained by numerical calculation for this system. Furthermore, by linear scalar controller consisting of a single state variable, one control scheme for stabilization of the 3D fractional-order chaotic system is suggested. The numerical simulations show the feasibility of the control scheme.
A Stable Formation Control Using Approximation of Translational and Angular Accelerations
Directory of Open Access Journals (Sweden)
Viet-Hong Tran
2011-03-01
Full Text Available In this paper, a stable leader-following formation control for multiple non-holonomic mobile robot systems using only limited on-board sensor information is proposed. The control can be used for the conventional single leader – single follower (SLSF or for novel two leaders – single follower (TLSF schemes. The control algorithm utilizes estimations of the leaders' translational and angular accelerations in a simple form to reduce the measurement of indirect information. Simulation results show that the TLSF scheme can suppress the oscillation and damping in formation of large robot teams.
Anticipation and the adaptive control of safety margins in driving
van der Hulst, M.; Meijman, T.F.; Rothengatter, J.A.
Driving is a task that requires the timely detection of critical events and relevant changes in traffic circumstances. Adaptation of speed and safety margins allows drivers to control the time available to react to potential hazards. One of the basic safety margins in driving is the time headway
Interference mitigation through adaptive power control in wireless sensor networks
Chincoli, M.; Bacchiani, C.; Syed, Aly; Exarchakos, G.; Liotta, A.
2016-01-01
Adaptive transmission power control schemes have been introduced in wireless sensor networks to adjust energy consumption under different network conditions. This is a crucial goal, given the constraints under which sensor communications operate. Power reduction may however have counter-productive
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
Driving characteristics and adaptive cruise control : A naturalistic driving study
Schakel, W.J.; Gorter, C.M.; de Winter, J.C.F.; van Arem, B.
2017-01-01
With the increasing number of vehicles equipped with Adaptive Cruise Control (ACC), it becomes important to assess its impact on traffic flow efficiency, in particular with respect to capacity and queue discharge rate. Simulation studies and surveys suggest that ACC has both positive and negative
Developed adaptive neuro-fuzzy algorithm to control air conditioning ...
African Journals Online (AJOL)
user
The paper developed artificial intelligence technique adaptive neuro-fuzzy ... system is highly appreciated and essential in most of our daily life. ... It can construct an input-output mapping based on human knowledge and specific input-output data ... fuzzy controllers to produce desirable internal temperature and air quality, ...
Liquid-crystal intraocular adaptive lens with wireless control
Simonov, A.N.; Vdovine, G.V.; Loktev, M.
2007-01-01
We present a prototype of an adaptive intraocular lens based on a modal liquid-crystal spatial phase modulator with wireless control. The modal corrector consists of a nematic liquid-crystal layer sandwiched between two glass substrates with transparent low- and high-ohmic electrodes, respectively.
Adaptive Media Access Control for Energy Harvesting - Wireless Sensor Networks
DEFF Research Database (Denmark)
Fafoutis, Xenofon; Dragoni, Nicola
2012-01-01
ODMAC (On-Demand Media Access Control) is a recently proposed MAC protocol designed to support individual duty cycles for Energy Harvesting — Wireless Sensor Networks (EH-WSNs). Individual duty cycles are vital for EH-WSNs, because they allow nodes to adapt their energy consumption to the ever-ch...
Adaptive feed forward in the LANL RF control system
International Nuclear Information System (INIS)
Ziomek, C.D.
1992-01-01
This paper describes an adaptive feed forward 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 feed forward 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 feed forward 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 feed forward system are presented. (Author) 3 figs., 2 refs
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.
LFC based adaptive PID controller using ANN and ANFIS techniques
Directory of Open Access Journals (Sweden)
Mohamed I. Mosaad
2014-12-01
Full Text Available This paper presents an adaptive PID Load Frequency Control (LFC for power systems using Neuro-Fuzzy Inference Systems (ANFIS and Artificial Neural Networks (ANN oriented by Genetic Algorithm (GA. PID controller parameters are tuned off-line by using GA to minimize integral error square over a wide-range of load variations. The values of PID controller parameters obtained from GA are used to train both ANFIS and ANN. Therefore, the two proposed techniques could, online, tune the PID controller parameters for optimal response at any other load point within the operating range. Testing of the developed techniques shows that the adaptive PID-LFC could preserve optimal performance over the whole loading range. Results signify superiority of ANFIS over ANN in terms of performance measures.
Directory of Open Access Journals (Sweden)
Fuhong Min
2016-08-01
Full Text Available The bifurcation and Lyapunov exponent for a single-machine-infinite bus system with excitation model are carried out by varying the mechanical power, generator damping factor and the exciter gain, from which periodic motions, chaos and the divergence of system are observed respectively. From given parameters and different initial conditions, the coexisting motions are developed in power system. The dynamic behaviors in power system may switch freely between the coexisting motions, which will bring huge security menace to protection operation. Especially, the angle divergences due to the break of stable chaotic oscillation are found which causes the instability of power system. Finally, a new adaptive backstepping sliding mode controller is designed which aims to eliminate the angle divergences and make the power system run in stable orbits. Numerical simulations are illustrated to verify the effectivity of the proposed method.
Energy Technology Data Exchange (ETDEWEB)
Min, Fuhong, E-mail: minfuhong@njnu.edu.cn; Wang, Yaoda; Peng, Guangya; Wang, Enrong [School of Electrical and Automation Engineering, Nanjing Normal University, Jiangsu, 210042 (China)
2016-08-15
The bifurcation and Lyapunov exponent for a single-machine-infinite bus system with excitation model are carried out by varying the mechanical power, generator damping factor and the exciter gain, from which periodic motions, chaos and the divergence of system are observed respectively. From given parameters and different initial conditions, the coexisting motions are developed in power system. The dynamic behaviors in power system may switch freely between the coexisting motions, which will bring huge security menace to protection operation. Especially, the angle divergences due to the break of stable chaotic oscillation are found which causes the instability of power system. Finally, a new adaptive backstepping sliding mode controller is designed which aims to eliminate the angle divergences and make the power system run in stable orbits. Numerical simulations are illustrated to verify the effectivity of the proposed method.
Doko, Marthen Luther
2017-05-01
When developing a wide class of on-line parameter estimation scheme for estimating the unknown parameter vector that appears in certain general linear and bilinear parametric model will be parametrizations of LTI processes or plants as well as of some special classes of nonlinear processes or plants. The resuls is used to design one of the important tools in control, i.e., adaptive observer and for stable LTI processes or plants. In this paper it will consider the design of schemes that simultaneously estimate the plant state variables and parameters by processing the plant I/O measurements on-line and such schemes is refered to as adaptive observers. The design of an adaptive observer is based on the combination of a state observer that could be used to estimate the state variables of aparticular plant state-space representation with an on-line estimation scheme. The choice of the plant state-space representation is crucial for the design and stability analysis of the adaptive observer. The paper will discuss a class of observer called Adaptive Luenberger Observer and its application. Begin with observable canonical form one can find observability matrix of n linear independent rows. By using this fact or their linear combination chosen as a basis, various canonical forms known also as Luenberger canonical form can be obtained. Also,this formation will leads to various algorithm for computing including computation of observable canonical form, observable Hessenberg form and reduced-order state observer design.
Adaptive semi-active control of buildings under seismic solicitations
International Nuclear Information System (INIS)
Roberti, V.; Jezequel, L.
1993-01-01
This paper describes an adaptive semi-active control method whereby nonlinear distributed systems are identified by their dynamical response. Approximate procedures are proposed which take into account the nonlinear behavior of the dynamic system considered. It is shown that only slight knowledge of nonlinearities is needed to apply feedback and feedforward control laws. The method is implemented to a simple example of a building with three degrees of freedom and the numerical results are analyzed
Adaptive Control of the Chaotic System via Singular System Approach
Directory of Open Access Journals (Sweden)
Yudong Li
2014-01-01
Full Text Available This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.
Adaptive PID control based on orthogonal endocrine neural networks.
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.
Microgrid Stability Controller Based on Adaptive Robust Total SMC
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...
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.
Localization of an Underwater Control Network Based on Quasi-Stable Adjustment
Chen, Xinhua; Zhang, Hongmei; Feng, Jie
2018-01-01
There exists a common problem in the localization of underwater control networks that the precision of the absolute coordinates of known points obtained by marine absolute measurement is poor, and it seriously affects the precision of the whole network in traditional constraint adjustment. Therefore, considering that the precision of underwater baselines is good, we use it to carry out quasi-stable adjustment to amend known points before constraint adjustment so that the points fit the network shape better. In addition, we add unconstrained adjustment for quality control of underwater baselines, the observations of quasi-stable adjustment and constrained adjustment, to eliminate the unqualified baselines and improve the results’ accuracy of the two adjustments. Finally, the modified method is applied to a practical LBL (Long Baseline) experiment and obtains a mean point location precision of 0.08 m, which improves by 38% compared with the traditional method. PMID:29570627
Adaptive piezoelectric sensoriactuators for active structural acoustic control
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
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
Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance
Directory of Open Access Journals (Sweden)
Zhonghua Wu
2017-01-01
Full Text Available This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP technique, prescribed performance control, and a kind of smooth switching strategy into back-stepping design, a new composite switching adaptive neural prescribed performance control scheme is proposed and a new type of adaptive laws is constructed for the altitude subsystem. Compared with previous neural control scheme for flight vehicle, the remarkable feature is that the proposed controller not only achieves the prescribed performance including transient and steady property but also addresses the constraint on NN. Two comparative simulations are presented to verify the effectiveness of the proposed controller.
Photonic lantern adaptive spatial mode control in LMA fiber amplifiers.
Montoya, Juan; Aleshire, Chris; Hwang, Christopher; Fontaine, Nicolas K; Velázquez-Benítez, Amado; Martz, Dale H; Fan, T Y; Ripin, Dan
2016-02-22
We demonstrate adaptive-spatial mode control (ASMC) in few-moded double-clad large mode area (LMA) fiber amplifiers by using an all-fiber-based photonic lantern. Three single-mode fiber inputs are used to adaptively inject the appropriate superposition of input modes in a multimode gain fiber to achieve the desired mode at the output. By actively adjusting the relative phase of the single-mode inputs, near-unity coherent combination resulting in a single fundamental mode at the output is achieved.
Stable Control of Firing Rate Mean and Variance by Dual Homeostatic Mechanisms.
Cannon, Jonathan; Miller, Paul
2017-12-01
Homeostatic processes that provide negative feedback to regulate neuronal firing rates are essential for normal brain function. Indeed, multiple parameters of individual neurons, including the scale of afferent synapse strengths and the densities of specific ion channels, have been observed to change on homeostatic time scales to oppose the effects of chronic changes in synaptic input. This raises the question of whether these processes are controlled by a single slow feedback variable or multiple slow variables. A single homeostatic process providing negative feedback to a neuron's firing rate naturally maintains a stable homeostatic equilibrium with a characteristic mean firing rate; but the conditions under which multiple slow feedbacks produce a stable homeostatic equilibrium have not yet been explored. Here we study a highly general model of homeostatic firing rate control in which two slow variables provide negative feedback to drive a firing rate toward two different target rates. Using dynamical systems techniques, we show that such a control system can be used to stably maintain a neuron's characteristic firing rate mean and variance in the face of perturbations, and we derive conditions under which this happens. We also derive expressions that clarify the relationship between the homeostatic firing rate targets and the resulting stable firing rate mean and variance. We provide specific examples of neuronal systems that can be effectively regulated by dual homeostasis. One of these examples is a recurrent excitatory network, which a dual feedback system can robustly tune to serve as an integrator.
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)
Implementation of Adaptive Digital Controllers on Programmable Logic Devices
Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Monenegro, Justino (Technical Monitor)
2002-01-01
Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used proportional-integral-derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM-based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a DSP (Digital Signal Processor) or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSP) devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. An alternative is required for compact implementation of such functionality to withstand the harsh environment
Adaptive control in multi-threaded iterated integration
International Nuclear Information System (INIS)
Doncker, Elise de; Yuasa, Fukuko
2013-01-01
In recent years we have developed a technique for the direct computation of Feynman loop-integrals, which are notorious for the occurrence of integrand singularities. Especially for handling singularities in the interior of the domain, we approximate the iterated integral using an adaptive algorithm in the coordinate directions. We present a novel multi-core parallelization scheme for adaptive multivariate integration, by assigning threads to the rule evaluations in the outer dimensions of the iterated integral. The method ensures a large parallel granularity as each function evaluation by itself comprises an integral over the lower dimensions, while the application of the threads is governed by the adaptive control in the outer level. We give computational results for a test set of 3- to 6-dimensional integrals, where several problems exhibit a loop integral behavior.
Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control
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
Embedded intelligent adaptive PI controller for an electromechanical system.
El-Nagar, Ahmad M
2016-09-01
In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Adaptive suboptimal second-order sliding mode control for microgrids
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.
Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems
Xia, Feng; Ma, Longhua; Peng, Chen; Sun, Youxian; Dong, Jinxiang
2008-01-01
There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN. PMID:27879934
Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems
Directory of Open Access Journals (Sweden)
Jinxiang Dong
2008-07-01
Full Text Available There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting crosslayer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An eventdriven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.
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...
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.
Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems
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
Adaptive model predictive process control using neural networks
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.
Directory of Open Access Journals (Sweden)
Michel Nicolas
2017-12-01
Full Text Available The purpose of this study was to identify the potentially distinct defense profiles of athletes in order to provide insight into the complex associations that can exist between defenses and other important variables tied to performance in sports (e.g., coping, perceived stress and control and to further our understanding of the complexity of the adaptation process in sports. Two hundred and ninety-six (N = 296 athletes participated in a naturalistic study that involved a highly stressful situation: a sports competition. Participants were assessed before and after the competition. Hierarchical cluster analysis and a series of MANOVAs with post hoc comparisons indicated two stable defense profiles (high and low defense profiles of athletes both before and during sport competition. These profiles differed with regards to coping, stress and control. Athletes with high defense profiles reported higher levels of coping strategies, perceived stress and control than athletes with low defense profiles. This study confirmed that defenses are involved in the psychological adaptation process and that research and intervention should not be based only on coping, but rather must include defense mechanisms in order to improve our understanding of psychological adaptation in competitive sports.
Nicolas, Michel; Martinent, Guillaume; Drapeau, Martin; Chahraoui, Khadija; Vacher, Philippe; de Roten, Yves
2017-01-01
The purpose of this study was to identify the potentially distinct defense profiles of athletes in order to provide insight into the complex associations that can exist between defenses and other important variables tied to performance in sports (e.g., coping, perceived stress and control) and to further our understanding of the complexity of the adaptation process in sports. Two hundred and ninety-six ( N = 296) athletes participated in a naturalistic study that involved a highly stressful situation: a sports competition. Participants were assessed before and after the competition. Hierarchical cluster analysis and a series of MANOVAs with post hoc comparisons indicated two stable defense profiles (high and low defense profiles) of athletes both before and during sport competition. These profiles differed with regards to coping, stress and control. Athletes with high defense profiles reported higher levels of coping strategies, perceived stress and control than athletes with low defense profiles. This study confirmed that defenses are involved in the psychological adaptation process and that research and intervention should not be based only on coping, but rather must include defense mechanisms in order to improve our understanding of psychological adaptation in competitive sports.
The ALICE-HMPID Detector Control System: Its evolution towards an expert and adaptive system
De Cataldo, G.; Franco, A.; Pastore, C.; Sgura, I.; Volpe, G.
2011-05-01
The High Momentum Particle IDentification (HMPID) detector is a proximity focusing Ring Imaging Cherenkov (RICH) for charged hadron identification. The HMPID is based on liquid C 6F 14 as the radiator medium and on a 10 m 2 CsI coated, pad segmented photocathode of MWPCs for UV Cherenkov photon detection. To ensure full remote control, the HMPID is equipped with a detector control system (DCS) responding to industrial standards for robustness and reliability. It has been implemented using PVSS as Slow Control And Data Acquisition (SCADA) environment, Programmable Logic Controller as control devices and Finite State Machines for modular and automatic command execution. In the perspective of reducing human presence at the experiment site, this paper focuses on DCS evolution towards an expert and adaptive control system, providing, respectively, automatic error recovery and stable detector performance. HAL9000, the first prototype of the HMPID expert system, is then presented. Finally an analysis of the possible application of the adaptive features is provided.
The ALICE-HMPID Detector Control System: Its evolution towards an expert and adaptive system
International Nuclear Information System (INIS)
De Cataldo, G.; Franco, A.; Pastore, C.; Sgura, I.; Volpe, G.
2011-01-01
The High Momentum Particle IDentification (HMPID) detector is a proximity focusing Ring Imaging Cherenkov (RICH) for charged hadron identification. The HMPID is based on liquid C 6 F 14 as the radiator medium and on a 10 m 2 CsI coated, pad segmented photocathode of MWPCs for UV Cherenkov photon detection. To ensure full remote control, the HMPID is equipped with a detector control system (DCS) responding to industrial standards for robustness and reliability. It has been implemented using PVSS as Slow Control And Data Acquisition (SCADA) environment, Programmable Logic Controller as control devices and Finite State Machines for modular and automatic command execution. In the perspective of reducing human presence at the experiment site, this paper focuses on DCS evolution towards an expert and adaptive control system, providing, respectively, automatic error recovery and stable detector performance. HAL9000, the first prototype of the HMPID expert system, is then presented. Finally an analysis of the possible application of the adaptive features is provided.
Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity
Frost, S. A.; Balas, M. J.
2010-01-01
We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. Autonomous assembly of large, complex flexible structures in space is a target application for Evolving Systems. A critical requirement for autonomous assembling structures is that they remain stable during and after assembly. The fundamental topic of inheritance of stability, dissipativity, and passivity in Evolving Systems is the primary focus of this research. In this paper, we develop an adaptive key component controller to restore stability in Nonlinear Evolving Systems that would otherwise fail to inherit the stability traits of their components. We provide sufficient conditions for the use of this novel control method and demonstrate its use on an illustrative example.
Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System
Directory of Open Access Journals (Sweden)
Shan Zuo
2014-01-01
Full Text Available In searching for methods to increase the power capacity of wind power generation system, superconducting synchronous generator (SCSG has appeared to be an attractive candidate to develop large-scale wind turbine due to its high energy density and unprecedented advantages in weight and size. In this paper, a high-temperature superconducting technology based large-scale wind turbine is considered and its physical structure and characteristics are analyzed. A simple yet effective single neuron-adaptive PID control scheme with Delta learning mechanism is proposed for the speed control of SCSG based wind power system, in which the RBF neural network (NN is employed to estimate the uncertain but continuous functions. Compared with the conventional PID control method, the simulation results of the proposed approach show a better performance in tracking the wind speed and maintaining a stable tip-speed ratio, therefore, achieving the maximum wind energy utilization.
Adaptive pitch control for variable speed wind turbines
Johnson, Kathryn E [Boulder, CO; Fingersh, Lee Jay [Westminster, CO
2012-05-08
An adaptive method for adjusting blade pitch angle, and controllers implementing such a method, for achieving higher power coefficients. Average power coefficients are determined for first and second periods of operation for the wind turbine. When the average power coefficient for the second time period is larger than for the first, a pitch increment, which may be generated based on the power coefficients, is added (or the sign is retained) to the nominal pitch angle value for the wind turbine. When the average power coefficient for the second time period is less than for the first, the pitch increment is subtracted (or the sign is changed). A control signal is generated based on the adapted pitch angle value and sent to blade pitch actuators that act to change the pitch angle of the wind turbine to the new or modified pitch angle setting, and this process is iteratively performed.
Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance
Wu, Zhonghua; Lu, Jingchao; Shi, Jingping; Liu, Yang; Zhou, Qing
2017-01-01
This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs) be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP) tech...
Theoretical model for ultracold molecule formation via adaptive feedback control
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 ...
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
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.
Laser diodes for sensing applications: adaptive cruise control and more
Heerlein, Joerg; Morgott, Stefan; Ferstl, Christian
2005-02-01
Adaptive Cruise Controls (ACC) and pre-crash sensors require an intelligent eye which can recognize traffic situations and deliver a 3-dimensional view. Both microwave RADAR and "Light RADAR" (LIDAR) systems are well suited as sensors. In order to utilize the advantages of LIDARs -- such as lower cost, simpler assembly and high reliability -- the key component, the laser diode, is of primary importance. Here, we present laser diodes which meet the requirements of the automotive industry.
Agrawal, Shikha; Silakari, Sanjay; Agrawal, Jitendra
2015-11-01
A novel parameter automation strategy for Particle Swarm Optimization called APSO (Adaptive PSO) is proposed. The algorithm is designed to efficiently control the local search and convergence to the global optimum solution. Parameters c1 controls the impact of the cognitive component on the particle trajectory and c2 controls the impact of the social component. Instead of fixing the value of c1 and c2 , this paper updates the value of these acceleration coefficients by considering time variation of evaluation function along with varying inertia weight factor in PSO. Here the maximum and minimum value of evaluation function is use to gradually decrease and increase the value of c1 and c2 respectively. Molecular energy minimization is one of the most challenging unsolved problems and it can be formulated as a global optimization problem. The aim of the present paper is to investigate the effect of newly developed APSO on the highly complex molecular potential energy function and to check the efficiency of the proposed algorithm to find the global minimum of the function under consideration. The proposed algorithm APSO is therefore applied in two cases: Firstly, for the minimization of a potential energy of small molecules with up to 100 degrees of freedom and finally for finding the global minimum energy conformation of 1,2,3-trichloro-1-flouro-propane molecule based on a realistic potential energy function. The computational results of all the cases show that the proposed method performs significantly better than the other algorithms. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Control algorithms and applications of the wavefront sensorless adaptive optics
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.
Retrospective Cost Adaptive Control with Concurrent Closed-Loop Identification
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.
Miao, Zhidong; Liu, Dake; Gong, Chen
2017-08-01
For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power.
Miao, Zhidong; Liu, Dake
2017-01-01
For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power. PMID:28763011
Neural controller for adaptive movements with unforeseen payloads.
Kuperstein, M; Wang, J
1990-01-01
A theory and computer simulation of a neural controller that learns to move and position a link carrying an unforeseen payload accurately are presented. The neural controller learns adaptive dynamic control from its own experience. It does not use information about link mass, link length, or direction of gravity, and it uses only indirect uncalibrated information about payload and actuator limits. Its average positioning accuracy across a large range of payloads after learning is 3% of the positioning range. This neural controller can be used as a basis for coordinating any number of sensory inputs with limbs of any number of joints. The feedforward nature of control allows parallel implementation in real time across multiple joints.
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.
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.
Driver's behavioral adaptation to adaptive cruise control (ACC): the case of speed and time headway.
Bianchi Piccinini, Giulio Francesco; Rodrigues, Carlos Manuel; Leitão, Miguel; Simões, Anabela
2014-06-01
The Adaptive Cruise Control is an Advanced Driver Assistance System (ADAS) that allows maintaining given headway and speed, according to settings pre-defined by the users. Despite the potential benefits associated to the utilization of ACC, previous studies warned against negative behavioral adaptations that might occur while driving with the system activated. Unfortunately, up to now, there are no unanimous results about the effects induced by the usage of ACC on speed and time headway to the vehicle in front. Also, few studies were performed including actual users of ACC among the subjects. This research aimed to investigate the effect of the experience gained with ACC on speed and time headway for a group of users of the system. In addition, it explored the impact of ACC usage on speed and time headway for ACC users and regular drivers. A matched sample driving simulator study was planned as a two-way (2×2) repeated measures mixed design, with the experience with ACC as between-subjects factor and the driving condition (with ACC and manually) as within-subjects factor. The results show that the usage of ACC brought a small but not significant reduction of speed and, especially, the maintenance of safer time headways, being the latter result greater for ACC users, probably as a consequence of their experience in using the system. The usage of ACC did not cause any negative behavioral adaptations to the system regarding speed and time headway. Based on this research work, the Adaptive Cruise Control showed the potential to improve road safety for what concerns the speed and the time headway maintained by the drivers. The speed of the surrounding traffic and the minimum time headway settable through the ACC seem to have an important effect on the road safety improvement achievable with the system. Copyright © 2014 Elsevier Ltd. All rights reserved.
Quasi-adaptive fuzzy heating control of solar buildings
Energy Technology Data Exchange (ETDEWEB)
Gouda, M.M. [Faculty of Industrial Education, Cairo (Egypt); Danaher, S. [University of Northumbria, Newcastle upon Tyne, (United Kingdom). School of Engineering; Underwood, C.P. [University of Northumbria, Newcastle upon Tyne (United Kingdom). School of Built Environment and Sustainable Cities Research Institute
2006-12-15
Significant progress has been made on maximising passive solar heat gains to building spaces in winter. Control of the space heating in these applications is complicated due to the lagging influence of the useful solar heat gain coupled with the wide range of construction materials and heating system choices. Additionally, and in common with most building control applications, there is a need to develop control solutions that permit simple and transparent set-up and commissioning procedures. This paper addresses the development and testing of a quasi-adaptive fuzzy logic control method that addresses these issues. The controller is developed in two steps. A feed-forward neural network is used to predict the internal air temperature, in which a singular value decomposition (SVD) algorithm is used to remove the highly correlated data from the inputs of the neural network to reduce the network structure. The fuzzy controller is then designed to have two inputs: the first input being the error between the set-point temperature and the internal air temperature and the second the predicted future internal air temperature. The controller was implemented in real-time using a test cell with controlled ventilation and a modulating electric heating system. Results, compared with validated simulations of conventionally controlled heating, confirm that the proposed controller achieves superior tracking and reduced overheating when compared with the conventional method of control. (author)
Flatness-based adaptive fuzzy control of chaotic finance dynamics
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.
Lei, Meizhen; Wang, Liqiang
2018-01-01
The halbach-type linear oscillatory motor (HT-LOM) is multi-variable, highly coupled, nonlinear and uncertain, and difficult to get a satisfied result by conventional PID control. An incremental adaptive fuzzy controller (IAFC) for stroke tracking was presented, which combined the merits of PID control, the fuzzy inference mechanism and the adaptive algorithm. The integral-operation is added to the conventional fuzzy control algorithm. The fuzzy scale factor can be online tuned according to the load force and stroke command. The simulation results indicate that the proposed control scheme can achieve satisfied stroke tracking performance and is robust with respect to parameter variations and external disturbance.
On flexible CAD of adaptive control and identification algorithms
DEFF Research Database (Denmark)
Christensen, Anders; Ravn, Ole
1988-01-01
a total redesign of the system within each sample. The necessary design parameters are evaluated and a decision vector is defined, from which the identification algorithm can be generated by the program. Using the decision vector, a decision-node tree structure is built up, where the nodes define......SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows...
Robust synchronization of chaotic systems via adaptive sliding mode control
International Nuclear Information System (INIS)
Yan, J.-J.; Hung, M.-L.; Chiang, T.-Y.; Yang, Y.-S.
2006-01-01
This Letter investigates the synchronization problem for a general class of chaotic systems. Using the sliding mode control technique, an adaptive control law is established to guarantee synchronization of the master and slave systems even when unknown parameters and external disturbances are present. In contrast to the previous works, the structure of slave system is simple and need not be identical to the master system. Furthermore, a novel proportional-integral (PI) switching surface is proposed to simplify the task of assigning the performance of the closed-loop error system in sliding mode. An illustrative example of Chua's circuit is given to demonstrate the effectiveness of the proposed synchronization scheme
Adaptive Fractional Fuzzy Sliding Mode Control for Multivariable Nonlinear Systems
Directory of Open Access Journals (Sweden)
Junhai Luo
2014-01-01
Full Text Available This paper presents a robust adaptive fuzzy sliding mode control method for a class of uncertain nonlinear systems. The fractional order calculus is employed in the parameter updating stage. The underlying stability analysis as well as parameter update law design is carried out by Lyapunov based technique. In the simulation, two examples including a comparison with the traditional integer order counterpart are given to show the effectiveness of the proposed method. The main contribution of this paper consists in the control performance is better for the fractional order updating law than that of traditional integer order.
Adaptive Reference Control for Pressure Management in Water Networks
DEFF Research Database (Denmark)
Kallesøe, Carsten; Jensen, Tom Nørgaard; Wisniewski, Rafal
2015-01-01
Water scarcity is an increasing problem worldwide and at the same time a huge amount of water is lost through leakages in the distribution network. It is well known that improved pressure control can lower the leakage problems. In this work water networks with a single pressure actuator and several....... Subsequently, these relations are exploited in an adaptive reference control scheme for the actuator pressure that ensures constant pressure at the critical points. Numerical experiments underpin the results. © Copyright IEEE - All rights reserved....
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.
Generalized projective synchronization of chaotic systems via adaptive learning control
International Nuclear Information System (INIS)
Yun-Ping, Sun; Jun-Min, Li; Hui-Lin, Wang; Jiang-An, Wang
2010-01-01
In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)
Graph theoretical stable allocation as a tool for reproduction of control by human operators
van Nooijen, Ronald; Ertsen, Maurits; Kolechkina, Alla
2016-04-01
During the design of central control algorithms for existing water resource systems under manual control it is important to consider the interaction with parts of the system that remain under manual control and to compare the proposed new system with the existing manual methods. In graph theory the "stable allocation" problem has good solution algorithms and allows for formulation of flow distribution problems in terms of priorities. As a test case for the use of this approach we used the algorithm to derive water allocation rules for the Gezira Scheme, an irrigation system located between the Blue and White Niles south of Khartoum. In 1925, Gezira started with 300,000 acres; currently it covers close to two million acres.
Adaptive fuzzy-neural-network control for maglev transportation system.
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.
International Nuclear Information System (INIS)
Farivar, Faezeh; Aliyari Shoorehdeli, Mahdi; Nekoui, Mohammad Ali; Teshnehlab, Mohammad
2012-01-01
Highlights: ► A systematic procedure for GPS of unknown heavy chaotic gyroscope systems. ► Proposed methods are based on Lyapunov stability theory. ► Without calculating Lyapunov exponents and Eigen values of the Jacobian matrix. ► Capable to extend for a variety of chaotic systems. ► Useful for practical applications in the future. - Abstract: This paper proposes the chaos control and the generalized projective synchronization methods for heavy symmetric gyroscope systems via Gaussian radial basis adaptive variable structure control. Because of the nonlinear terms of the gyroscope system, the system exhibits chaotic motions. Occasionally, the extreme sensitivity to initial states in a system operating in chaotic mode can be very destructive to the system because of unpredictable behavior. In order to improve the performance of a dynamic system or avoid the chaotic phenomena, it is necessary to control a chaotic system with a periodic motion beneficial for working with a particular condition. As chaotic signals are usually broadband and noise like, synchronized chaotic systems can be used as cipher generators for secure communication. This paper presents chaos synchronization of two identical chaotic motions of symmetric gyroscopes. In this paper, the switching surfaces are adopted to ensure the stability of the error dynamics in variable structure control. Using the neural variable structure control technique, control laws are established which guarantees the chaos control and the generalized projective synchronization of unknown gyroscope systems. In the neural variable structure control, Gaussian radial basis functions are utilized to on-line estimate the system dynamic functions. Also, the adaptation laws of the on-line estimator are derived in the sense of Lyapunov function. Thus, the unknown gyro systems can be guaranteed to be asymptotically stable. Also, the proposed method can achieve the control objectives. Numerical simulations are presented to
Adaptive control theory of concentration in the uranium enrichment plant
International Nuclear Information System (INIS)
Sugitsue, Noritake; Miyagawa, Hiroshi; Yokoyama, Kaoru; Nakakura, Hiroyuki
1999-01-01
This paper presents the new adaptive control of concentration in the uranium enrichment plant. The purpose of this control system is average concentration control in production tram. As a result the accuracy and practical use of this control system have already been confirmed by the operation of the uranium enrichment demonstration plant. Three elements of technology are required to this method. The first is the measurement of the concentration using product flow quantity change. This technology shall be called 'Qp difference to Xp transform method'. The second is the relationship between temperature change and flow quantity using G.M.D.H. (Groupe Method of Data Handling) and the third is the estimation of temperature change using AR (Auto-regressive) model. (author)
Non-linear and adaptive control of a refrigeration system
DEFF Research Database (Denmark)
Rasmussen, Henrik; Larsen, Lars F. S.
2011-01-01
are capable of adapting to variety of systems. This paper proposes a novel method for superheat and capacity control of refrigeration systems; namely by controlling the superheat by the compressor speed and capacity by the refrigerant flow. A new low order nonlinear model of the evaporator is developed......In a refrigeration process heat is absorbed in an evaporator by evaporating a flow of liquid refrigerant at low pressure and temperature. Controlling the evaporator inlet valve and the compressor in such a way that a high degree of liquid filling in the evaporator is obtained at all compressor...... capacities ensures a high energy efficiency. The level of liquid filling is indirectly measured by the superheat. Introduction of variable speed compressors and electronic expansion valves enables the use of more sophisticated control algorithms, giving a higher degree of performance and just as important...
Distributed adaptive droop control for DC distribution systems
DEFF Research Database (Denmark)
Nasirian, Vahidreza; Davoudi, Ali; Lewis, Frank
2016-01-01
Summary form only given: A distributed-adaptive droop mechanism is proposed for secondary/primary control of dc microgrids. The conventional secondary control that adjusts the voltage set point for the local droop mechanism is replaced by a voltage regulator. A current regulator is also added...... to fine-tune the droop coefficient for different loading conditions. The voltage regulator uses an observer that processes neighbors' data to estimate the average voltage across the microgrid. This estimation is further used to generate a voltage correction term to adjust the local voltage set point...... with the proposed controller engaged. A low-voltage dc microgrid prototype is used to verify the controller performance, link-failure resiliency, and the plug-and-play capability....
Microgrid Stability Controller Based on Adaptive Robust Total SMC
DEFF Research Database (Denmark)
Su, Xiaoling; Han, Minxiao; Guerrero, Josep M.
2015-01-01
This paper presents a microgrid stability controller (MSC) in order to provide existing 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....... The MSC provides fast dynamic response and robustness to the microgrid. When the system is operating in grid-connected mode, it is able to improve the controllability of the exchanged power between the microgrid and the utility grid, while smoothing DG’s output power. When the microgrid is operating...... 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-mode control (ARTSMC) system for the MSC. It is proved that the ARTSMC system is insensitive to parametric uncertainties and external disturbances...
Probabilistic DHP adaptive critic for nonlinear stochastic control systems.
Herzallah, Randa
2013-06-01
Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Káarnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained. Copyright © 2013 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Wernicke, J.-Th. [Wind Force Engineering and Consulting GmbH, Bremerhaven (Germany)
2004-07-01
The technology of Time Division Multiplexing (TDM) is compared with conventional strain gauge technologies in practical operation in a wind power system. Load cycles in the rotor blade were measured during plant life, and the data were used in plant control. The system is a tool in technical project management and financial management of a wind park. (orig.)
Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems
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.
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.
Adaptive precompensators for flexible-link manipulator control
Tzes, Anthony P.; Yurkovich, Stephen
1989-01-01
The application of input precompensators to flexible manipulators is considered. Frequency domain compensators color the input around the flexible mode locations, resulting in a bandstop or notch filter in cascade with the system. Time domain compensators apply a sequence of impulses at prespecified times related to the modal frequencies. The resulting control corresponds to a feedforward term that convolves in real-time the desired reference input with a sequence of impulses and produces a vibration-free output. An adaptive precompensator can be implemented by combining a frequency domain identification scheme which is used to estimate online the modal frequencies and subsequently update the bandstop interval or the spacing between the impulses. The combined adaptive input preshaping scheme provides the most rapid slew that results in a vibration-free output. Experimental results are presented to verify the results.
Adaptive dynamic programming with applications in optimal control
Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang
2017-01-01
This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...
Mullakkal Babu, F.A.; Wang, M.; van Arem, B.; Happee, R.; Rosetti, R.; Wolf, D.
2016-01-01
Current Full Range Adaptive Cruise Control (FRACC) systems switch between separate adaptive cruise control and collision avoidance systems. This can lead to jerky responses and discomfort during the transition between the two control modes. We propose a Full Range Adaptive Cruise Control (FRACC)
Adaptive control for solar energy based DC microgrid system development
Zhang, Qinhao
During the upgrading of current electric power grid, it is expected to develop smarter, more robust and more reliable power systems integrated with distributed generations. To realize these objectives, traditional control techniques are no longer effective in either stabilizing systems or delivering optimal and robust performances. Therefore, development of advanced control methods has received increasing attention in power engineering. This work addresses two specific problems in the control of solar panel based microgrid systems. First, a new control scheme is proposed for the microgrid systems to achieve optimal energy conversion ratio in the solar panels. The control system can optimize the efficiency of the maximum power point tracking (MPPT) algorithm by implementing two layers of adaptive control. Such a hierarchical control architecture has greatly improved the system performance, which is validated through both mathematical analysis and computer simulation. Second, in the development of the microgrid transmission system, the issues related to the tele-communication delay and constant power load (CPL)'s negative incremental impedance are investigated. A reference model based method is proposed for pole and zero placements that address the challenges of the time delay and CPL in closed-loop control. The effectiveness of the proposed modeling and control design methods are demonstrated in a simulation testbed. Practical aspects of the proposed methods for general microgrid systems are also discussed.
Masalaite, Agne; Garbaras, Andrius; Garbariene, Inga; Ceburnis, Darius; Martuzevicius, Dainius; Puida, Egidijus; Kvietkus, Kestutis; Remeikis, Vidmantas
2014-05-01
Biomass burning is the largest source of primary fine fraction carbonaceous particles and the second largest source of trace gases in the global atmosphere with a strong effect not only on the regional scale but also in areas distant from the source . Many studies have often assumed no significant carbon isotope fractionation occurring between black carbon and the original vegetation during combustion. However, other studies suggested that stable carbon isotope ratios of char or BC may not reliably reflect carbon isotopic signatures of the source vegetation. Overall, the apparently conflicting results throughout the literature regarding the observed fractionation suggest that combustion conditions may be responsible for the observed effects. The purpose of the present study was to gather more quantitative information on carbonaceous aerosols produced in controlled biomass burning, thereby having a potential impact on interpreting ambient atmospheric observations. Seven different biomass fuel types were burned under controlled conditions to determine the effect of the biomass type on the emitted particulate matter mass and stable carbon isotope composition of bulk and size segregated particles. Size segregated aerosol particles were collected using the total suspended particle (TSP) sampler and a micro-orifice uniform deposit impactor (MOUDI). The results demonstrated that particle emissions were dominated by the submicron particles in all biomass types. However, significant differences in emissions of submicron particles and their dominant sizes were found between different biomass fuels. The largest negative fractionation was obtained for the wood pellet fuel type while the largest positive isotopic fractionation was observed during the buckwheat shells combustion. The carbon isotope composition of MOUDI samples compared very well with isotope composition of TSP samples indicating consistency of the results. The measurements of the stable carbon isotope ratio in
Chen, Fenli; Zhang, Mingjun; Wang, Shengjie; Qiu, Xue; Du, Mingxia
2017-12-31
Stable hydrogen and oxygen isotopes in precipitation are very sensitive to environmental changes, and can record evolution of water cycle. The Lanzhou city in northwestern China is jointly influenced by the monsoon and westerlies, which is considered as a vital platform to investigate the moisture regime for this region. Since 2011, an observation network of stable isotopes in precipitation was established across the city, and four stations were included in the network. In 2013, six more sampling stations were added, and the enhanced network might provide more meaningful information on spatial incoherence and synoptic process. This study focused on the variations of stable isotopes (δ 18 O and δD) in precipitation and the environmental controls based on the 1432 samples in this enhanced network from April 2011 to October 2014. The results showed that the precipitation isotopes had great spatial diversity, and the neighboring stations may present large difference in δD and δ 18 O. Based on the observation at ten sampling sites, an isoscape in precipitation was calculated, and the method is useful to produce isoscape for small domains. The temperature effect and amount effect was reconsidered based on the dataset. Taking meteorological parameters (temperature, precipitation amount, relative humidity, water vapor pressure and dew point temperature) as variables in a multi-linear regression, the result of coefficients for these meteorological parameters were calculated. Some cases were also involved in this study, and the isotopic characteristics during one event or continuous days were used to understand the environmental controls on precipitation isotopes. Copyright © 2017 Elsevier B.V. All rights reserved.
Efficient speed control of induction motor using RBF based model reference adaptive control method
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...
The system of nonlinear adaptive control for wind turbine with DFIG
Directory of Open Access Journals (Sweden)
Mikhail Medvedev
2014-12-01
Full Text Available This paper presents a problem solution of the stable voltage generating in the changing terms of environment for the double-fed induction generator (DFIG. For this, in nonlinear multivariable systems, such as mathematical model of DFIG, the method of observer’s synthesis for external, parametric and structural disturbances was used. This allows, on the basis of disturbances approximation, to carry out an evaluation under conditions of uncertainty, leading to disturbances adaptation with a priori unknown structure. The work presents a synthesis method of control system, allowing to solve indicated problem. Stand-alone wind turbine used as a power plant with DFIG. The control system uses the original nonlinear mathematical model of the DFIG in rotating “dq” coordinates, taking into account non-linear changes in the parameters. To confirm the effectiveness of the problem solution, mathematical computer model was developed. The paper also presents the results of full-scale simulation.
Adaptive Neural Tracking Control for Discrete-Time Switched Nonlinear Systems with Dead Zone Inputs
Directory of Open Access Journals (Sweden)
Jidong Wang
2017-01-01
Full Text Available In this paper, the adaptive neural controllers of subsystems are proposed for a class of discrete-time switched nonlinear systems with dead zone inputs under arbitrary switching signals. Due to the complicated framework of the discrete-time switched nonlinear systems and the existence of the dead zone, it brings about difficulties for controlling such a class of systems. In addition, the radial basis function neural networks are employed to approximate the unknown terms of each subsystem. Switched update laws are designed while the parameter estimation is invariable until its corresponding subsystem is active. Then, the closed-loop system is stable and all the signals are bounded. Finally, to illustrate the effectiveness of the proposed method, an example is employed.
Adaptive super twisting vibration control of a flexible spacecraft with state rate estimation
Malekzadeh, Maryam; Karimpour, Hossein
2018-05-01
The robust attitude and vibration control of a flexible spacecraft trying to perform accurate maneuvers in spite of various sources of uncertainty is addressed here. Difficulties for achieving precise and stable pointing arise from noisy onboard sensors, parameters indeterminacy, outer disturbances as well as un-modeled or hidden dynamics interactions. Based on high-order sliding-mode methods, the non-minimum phase nature of the problem is dealt with through output redefinition. An adaptive super-twisting algorithm (ASTA) is incorporated with its observer counterpart on the system under consideration to get reliable attitude and vibration control in the presence of sensor noise and momentum coupling. The closed-loop efficiency is verified through simulations under various indeterminate situations and got compared to other methods.
Yang, Xiong; Liu, Derong; Wang, Ding
2014-03-01
In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.
Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification
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.
A servo-controlled canine model of stable severe ischemic left ventricular failure.
Wagner, Richard L; Hood, William B; Howland, Peter A
2009-12-01
Reversible left ventricular failure was produced in conscious dogs by compromise of the coronary circulation. In animals with prior left anterior descending coronary artery occlusion, mean left atrial pressure (LAP) was incorporated into an automatic feedback control system used to inflate a balloon cuff on the circumflex (Cfx) coronary artery. The system could produce stable increases in LAP to 15-20 mm Hg. The dominating system transfer function was the ratio of LAP to balloon volume (BV), which was characterized by a fixed delay (5 s), with LAP/BV = (8e(-jomegatau ))/(0.02 + jomega). The system was stabilized by a phase lead network to reduce oscillations of LAP. A total of seven experiments were conducted in three dogs, and testing of inotropic agents was possible in three experiments under stable conditions with the pump off after an hour or more of operation. Problems encountered were 0.003-0.008 Hz oscillations in LAP in three experiments, which could usually be controlled by reducing the system gain. Late stage ventricular fibrillation occurred in all three animals, but defibrillation was easily accomplished after deflating the Cfx balloon. This system produces reversible left ventricular failure solely due to ischemia, thus closely simulating clinical heart failure due to coronary insufficiency.
Robustness study of the pseudo open-loop controller for multiconjugate adaptive optics.
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.
Fault diagnosis and fault-tolerant control based on adaptive control approach
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. .
Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko
2014-01-01
The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations
Directory of Open Access Journals (Sweden)
Georg eLayher
2014-12-01
Full Text Available The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, but both belong to the category of felines. In other words, tigers and leopards are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in the computational neurosciences. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of (sub- category representations. We demonstrate the temporal evolution of such learning and show how the approach successully establishes category and subcategory
Adaptive Controller for Drive System PMSG in Wind Turbine
Directory of Open Access Journals (Sweden)
Gnanambal
2014-07-01
Full Text Available This paper proposes adaptive Maximum Power Point Tracking (MPPT controller for Permanent Magnet Synchronous Generator (PMSG wind turbine and direct power control for grid side inverter for transformer less integration of wind energy. PMSG wind turbine with two back to back voltage source converters are considered more efficient, used to make real and reactive power control. The optimal control strategy has introduced for integrated control of PMSG Maximum Power Extraction, DC link voltage control and grid voltage support controls. Simulation model using MATLAB Simulink has developed to investigate the performance of proposed control techniques for PMSG wind turbine steady and variable wind conditions. This paper shows that the direct driven grid connected PMSG system has excellent performances and confirms the feasibility of the proposed techniques. While the wind turbine market continues to be dominated by conventional gear-driven wind turbine systems, the direct drive is attracting attention. PM machines are more attractive and superior with higher efficiency and energy yield, higher reliability, and power-to-weight ratio compared with electricity-excited machines.
Nonlinear vibration with control for flexible and adaptive structures
Wagg, David
2015-01-01
This book provides a comprehensive discussion of nonlinear multi-modal structural vibration problems, and shows how vibration suppression can be applied to such systems by considering a sample set of relevant control techniques. It covers the basic principles of nonlinear vibrations that occur in flexible and/or adaptive structures, with an emphasis on engineering analysis and relevant control techniques. Understanding nonlinear vibrations is becoming increasingly important in a range of engineering applications, particularly in the design of flexible structures such as aircraft, satellites, bridges, and sports stadia. There is an increasing trend towards lighter structures, with increased slenderness, often made of new composite materials and requiring some form of deployment and/or active vibration control. There are also applications in the areas of robotics, mechatronics, micro electrical mechanical systems, non-destructive testing and related disciplines such as structural health monitoring. Two broader ...
Adaptive chaos control and synchronization in only locally Lipschitz systems
International Nuclear Information System (INIS)
Lin Wei
2008-01-01
In the existing results on chaos control and synchronization based on the adaptive controlling technique (ACT), a uniform Lipschitz condition on a given dynamical system is always assumed in advance. However, without this uniform Lipschitz condition, the ACT might be failed in both theoretical analysis and in numerical experiment. This Letter shows how to utilize the ACT to get a rigorous control for the system which is not uniformly Lipschitz but only locally Lipschitz, and even for the system which has unbounded trajectories. In fact, the ACT is proved to possess some limitation, which is actually induced by the nonlinear degree of the original system. Consequently, a piecewise ACT is proposed so as to improve the performance of the existing techniques
Distributed Adaptive Droop Control for DC Distribution Systems
DEFF Research Database (Denmark)
Nasirian, Vahidreza; Davoudi, Ali; Lewis, Frank
2014-01-01
A distributed-adaptive droop mechanism is proposed for secondary/primary control of dc Microgrids. The conventional secondary control, that adjusts the voltage set point for the local droop mechanism, is replaced by a voltage regulator. A current regulator is then added to fine-tune the droop...... coefficient for different loading conditions. The voltage regulator uses an observer that processes neighbors’ data to estimate the average voltage across the Microgrid. This estimation is further used to generate a voltage correction term to adjust the local voltage set point. The current regulator compares...... engaged. A low-voltage dc Microgrid prototype is used to verify the controller performance, link-failure resiliency, and the plug-andplay capabilities....
Active Inference, homeostatic regulation and adaptive behavioural control.
Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl
2015-11-01
We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.
Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua
2016-11-14
In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.
ADEX optimized adaptive controllers and systems from research to industrial practice
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...
Adaptive Interval Type-2 Fuzzy Logic Control for PMSM Drives with a Modified Reference Frame
Chaoui, Hicham; Khayamy, Mehdy; Aljarboua, Abdullah Abdulaziz
2017-01-01
In this paper, an adaptive interval type-2 fuzzy logic control scheme is proposed for high-performance permanent magnet synchronous machine drives. This strategy combines the power of type-2 fuzzy logic systems with the adaptive control theory
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Rasgrf2 controls dopaminergic adaptations to alcohol in mice.
Easton, Alanna C; Rotter, Andrea; Lourdusamy, Anbarasu; Desrivières, Sylvane; Fernández-Medarde, Alberto; Biermann, Teresa; Fernandes, Cathy; Santos, Eugenio; Kornhuber, Johannes; Schumann, Gunter; Müller, Christian P
2014-10-01
Alcohol abuse leads to serious health problems with no effective treatment available. Recent evidence suggests a role for ras-specific guanine-nucleotide releasing factor 2 (RASGRF2) in alcoholism. Rasgrf2 is a calcium sensor and MAPK/ERK activating protein, which has been linked to neurotransmitter release and monoaminergic receptor adaptations. Rasgrf2 knock out (KO) mice do not develop a dopamine response in the nucleus accumbens after an alcohol challenge and show a reduced consumption of alcohol. The present study aims to further characterise the role of Rasgrf2 in dopaminergic activation beyond the nucleus accumbens following alcohol treatment. Using in vivo microdialysis we found that alcohol induces alterations in dopamine levels in the dorsal striatum between wildtype (WT) and Rasgrf2 KO mice. There was no difference in the expression of dopamine transporter (DAT), dopamine receptor regulating factor (DRRF), or dopamine D2 receptor (DRD2) mRNA in the brain between Rasgrf2 KO and WT mice. After sub-chronic alcohol treatment, DAT and DRRF, but not DRD2 mRNA expression differed between WT and Rasgrf2 KO mice. Brain adaptations were positively correlated with splenic expression levels. These data suggest that Rasgrf2 controls dopaminergic signalling and adaptations to alcohol also in other brain regions, beyond the nucleus accumbens. Copyright © 2014 Elsevier Inc. All rights reserved.
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.
Direct model reference adaptive control with application to flexible robots
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.
Adaptive control using neural networks and approximate models.
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.
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...
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...
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.
International Nuclear Information System (INIS)
Cheng Sheng-Yi; Liu Wen-Jin; Chen Shan-Qiu; Dong Li-Zhi; Yang Ping; Xu Bing
2015-01-01
Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n 2 ) ∼ O(n 3 ) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ∼ (O(n) 3/2 ), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. (paper)
Robust sawtooth period control based on adaptive online optimization
International Nuclear Information System (INIS)
Bolder, J.J.; Witvoet, G.; De Baar, M.R.; Steinbuch, M.; Van de Wouw, N.; Haring, M.A.M.; Westerhof, E.; Doelman, N.J.
2012-01-01
The systematic design of a robust adaptive control strategy for the sawtooth period using electron cyclotron current drive (ECCD) is presented. Recent developments in extremum seeking control (ESC) are employed to derive an optimized controller structure and offer practical tuning guidelines for its parameters. In this technique a cost function in terms of the desired sawtooth period is optimized online by changing the ECCD deposition location based on online estimations of the gradient of the cost function. The controller design does not require a detailed model of the sawtooth instability. Therefore, the proposed ESC is widely applicable to any sawtoothing plasma or plasma simulation and is inherently robust against uncertainties or plasma variations. Moreover, it can handle a broad class of disturbances. This is demonstrated by time-domain simulations, which show successful tracking of time-varying sawtooth period references throughout the whole operating space, even in the presence of variations in plasma parameters, disturbances and slow launcher mirror dynamics. Due to its simplicity and robustness the proposed ESC is a valuable sawtooth control candidate for any experimental tokamak plasma, and may even be applicable to other fusion-related control problems. (paper)
Efficient community-based control strategies in adaptive networks
International Nuclear Information System (INIS)
Yang Hui; Tang Ming; Zhang Haifeng
2012-01-01
Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible–infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible–infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans. (paper)
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.
Yang, Xiong; He, Haibo
2018-05-26
In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Rojas R, E.
2014-07-01
The design and implementation of an identification and control scheme of the TRIGA Mark III research nuclear reactor of the Instituto Nacional de Investigaciones Nucleares (ININ) of Mexico is presented in this thesis work. The identification of the reactor dynamics is carried out using fuzzy logic based systems, in which a learning process permits the adjustment of the membership function parameters by means of techniques based on neural networks and bio-inspired algorithms. The resulting identification system is a useful tool that allows the emulation of the reactor power behavior when different types of insertions of reactivity are applied into the core. The identification of the power can also be used for the tuning of the parameters of a control system. On the other hand, the regulation of the reactor power is carried out by means of an adaptive and stable fuzzy control scheme. The control law is derived using the input-output linearization technique, which permits the introduction of a desired power profile for the plant to follow asymptotically. This characteristic is suitable for managing the ascent of power from an initial level n{sub o} up to a predetermined final level n{sub f}. During the increase of power, a constraint related to the rate of change in power is considered by the control scheme, thus minimizing the occurrence of a safety reactor shutdown due to a low reactor period value. Furthermore, the theory of stability in the sense of Lyapunov is used to obtain a supervisory control law which maintains the power error within a tolerance region, thus guaranteeing the stability of the power of the closed loop system. (Author)
Adaptive Automatic Gauge Control of a Cold Strip Rolling Process
Directory of Open Access Journals (Sweden)
ROMAN, N.
2010-02-01
Full Text Available The paper tackles with thickness control structure of the cold rolled strips. This structure is based on the rolls position control of a reversible quarto rolling mill. The main feature of the system proposed in the paper consists in the compensation of the errors introduced by the deficient dynamics of the hydraulic servo-system used for the rolls positioning, by means of a dynamic compensator that approximates the inverse system of the servo-system. Because the servo-system is considered variant over time, an on-line identification of the servo-system and parameter adapting of the compensator are achieved. The results obtained by numerical simulation are presented together with the data taken from real process. These results illustrate the efficiency of the proposed solutions.
Resonant power converter comprising adaptive dead-time control
DEFF Research Database (Denmark)
2017-01-01
The invention relates in a first aspect to a resonant power converter comprising: a first power supply rail for receipt of a positive DC supply voltage and a second power supply rail for receipt of a negative DC supply voltage. The resonant power converter comprises a resonant network with an input...... terminal for receipt of a resonant input voltage from a driver circuit. The driver circuit is configured for alternatingly pulling the resonant input voltage towards the positive and negative DC supply voltages via first and second semiconductor switches, respectively, separated by intervening dead......-time periods in accordance with one or more driver control signals. A dead-time controller is configured to adaptively adjusting the dead-time periods based on the resonant input voltage....
Directory of Open Access Journals (Sweden)
Jane Davidson
Full Text Available Reference laboratories advise immediate separation and freezing of samples for the assay of proinsulin, which limit its practicability for smaller centres. Following the demonstration that insulin and C-peptide are stable in EDTA at room temperature for at least 24hours, we undertook simple stability studies to establish whether the same might apply to proinsulin.Venous blood samples were drawn from six adult women, some fasting, some not, aliquoted and assayed immediately and after storage at either 4°C or ambient temperature for periods from 2h to 24h.There was no significant variation or difference with storage time or storage condition in either individual or group analysis.Proinsulin appears to be stable at room temperature in EDTA for at least 24h. Immediate separation and storage on ice of samples for proinsulin assay is not necessary, which will simplify sample transport, particularly for multicentre trials.
Safety problems in vehicles with adaptive cruise control system
Directory of Open Access Journals (Sweden)
Yadav Arun K.
2017-06-01
Full Text Available In today’s world automotive industries are still putting efforts towards more autonomous vehicles (AVs. The main concern of introducing the autonomous technology is safety of driver. According to a survey 90% of accidents happen due to mistake of driver. The adaptive cruise control system (ACC is a system which combines cruise control with a collision avoidance system. The ACC system is based on laser and radar technologies. This system is capable of controlling the velocity of vehicle automatically to match the velocity of car, bus or truck in front of vehicle. If the lead vehicle gets slow down or accelerate, than ACC system automatically matches that velocity. The proposed paper is focusing on more accurate methods of detecting the preceding vehicle by using a radar and lidar sensors by considering the vehicle side slip and by controlling the distance between two vehicles. By using this approach i.e. logic for calculation of former vehicle distance and controlling the throttle valve of ACC equipped vehicle, an improvement in driving stability was achieved. The own contribution results with fuel efficient driving and with more safer and reliable driving system, but still some improvements are going on to make it more safe and reliable.
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
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.
Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows.
Directory of Open Access Journals (Sweden)
Carsten Kirkeby
Full Text Available Paratuberculosis is a chronic infection that in dairy cattle causes reduced milk yield, weight loss, and ultimately fatal diarrhea. Subclinical animals can excrete bacteria (Mycobacterium avium ssp. paratuberculosis, MAP in feces and infect other animals. Farmers identify the infectious animals through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic consequences of continuously adapting the sampling interval in response to the estimated true prevalence in the herd. The key results were that the true prevalence was greatly affected by the hygiene level and to some extent by the test-frequency. Furthermore, the choice of prevalence that will be tolerated in a control scenario had a major impact on the true prevalence in the normal hygiene setting, but less so when the hygiene was poor. The net revenue is not greatly affected by the test-strategy, because of the general variation in net revenues between farms. An exception to this is the low hygiene herd, where frequent testing results in lower revenue. When we look at the probability of eradication, then it is correlated with the testing frequency and the target prevalence during the control phase. The probability of eradication is low in the low hygiene herd, and a test-and-cull strategy should probably not be the primary strategy in this herd. Based on this study we suggest that, in order to control MAP, the standard Danish dairy farm should use an adaptive strategy where a short sampling interval of three months is used when the estimated true prevalence is above 1%, and otherwise use a long sampling interval of one year.
A robust adaptive load frequency control for micro-grids.
Khooban, Mohammad-Hassan; Niknam, Taher; Blaabjerg, Frede; Davari, Pooya; Dragicevic, Tomislav
2016-11-01
The goal of this study is to introduce a novel robust load frequency control (LFC) strategy for micro-grid(s) (MG(s)) in islanded mode operation. Admittedly, power generators in MG(s) cannot supply steady electric power output and sometimes cause unbalance between supply and demand. Battery energy storage system (BESS) is one of the effective solutions to these problems. Due to the high cost of the BESS, a new idea of Vehicle-to-Grid (V2G) is that a battery of Electric-Vehicle (EV) can be applied as a tantamount large-scale BESS in MG(s). As a result, a new robust control strategy for an islanded micro-grid (MG) is introduced that can consider electric vehicles׳ (EV(s)) effect. Moreover, in this paper, a new combination of the General Type II Fuzzy Logic Sets (GT2FLS) and the Modified Harmony Search Algorithm (MHSA) technique is applied for adaptive tuning of proportional-integral (PI) controller. Implementing General Type II Fuzzy Systems is computationally expensive. However, using a recently introduced α-plane representation, GT2FLS can be seen as a composition of several Interval Type II Fuzzy Logic Systems (IT2FLS) with a corresponding level of α for each. Real-data from an offshore wind farm in Sweden and solar radiation data in Aberdeen (United Kingdom) was used in order to examine the performance of the proposed novel controller. A comparison is made between the achieved results of Optimal Fuzzy-PI (OFPI) controller and those of Optimal Interval Type II Fuzzy-PI (IT2FPI) controller, which are of most recent advances in the area at hand. The Simulation results prove the successfulness and effectiveness of the proposed controller. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
A self-adaptive feedforward rf control system for linacs
International Nuclear Information System (INIS)
Zhang Renshan; Ben-Zvi, I.; Xie Jialin
1993-01-01
The design and performance of a self-adaptive feedforward rf control system are reported. The system was built for the linac of the Accelerator Test Facility (ATF) at Brookhaven National Laboratory. Variables of time along the linac macropulse, such as field or phase are discretized and represented as vectors. Upon turn-on or after a large change in the operating-point, the control system acquires the response of the system to test signal vectors and generates a linearized system response matrix. During operation an error vector is generated by comparing the linac variable vectors and a target vector. The error vector is multiplied by the inverse of the system's matrix to generate a correction vector is added to an operating point vector. This control system can be used to control a klystron to produce flat rf amplitude and phase pulses, to control a rf cavity to reduce the rf field fluctuation, and to compensate the energy spread among bunches in a rf linac. Beam loading effects can be corrected and a programmed ramp can be produced. The performance of the control system has been evaluated on the control of a klystron's output as well as an rf cavity. Both amplitude and phase have been regulated simultaneously. In initial tests, the rf output from a klystron has been regulated to an amplitude fluctuation of less than ±0.3% and phase variation of less than ±0.6deg. The rf field of the ATF's photo-cathode microwave gun cavity has been regulated to ±5% in amplitude and simultaneously to ±1deg in phase. Regulating just the rf field amplitude in the rf gun cavity, we have achieved amplitude fluctuation of less than ±2%. (orig.)
Microgrid Stability Controller Based on Adaptive Robust Total SMC
Directory of Open Access Journals (Sweden)
Xiaoling Su
2015-03-01
Full Text Available 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-mode control (ARTSMC system for the MSC. It is proved that the ARTSMC system is insensitive to parametric uncertainties and external disturbances. The MSC provides fast dynamic response and robustness to the microgrid. When the system is operating in grid-connected mode, it is able to improve the controllability of the exchanged power between the microgrid and the utility grid, while smoothing the DGs’ output power. When the microgrid is operating in islanded mode, it provides voltage and frequency support, while guaranteeing seamless transition between the two operation modes. Simulation and experimental results show the effectiveness of the proposed approach.
Adaptive controller for volumetric display of neuroimaging studies
Bleiberg, Ben; Senseney, Justin; Caban, Jesus
2014-03-01
Volumetric display of medical images is an increasingly relevant method for examining an imaging acquisition as the prevalence of thin-slice imaging increases in clinical studies. Current mouse and keyboard implementations for volumetric control provide neither the sensitivity nor specificity required to manipulate a volumetric display for efficient reading in a clinical setting. Solutions to efficient volumetric manipulation provide more sensitivity by removing the binary nature of actions controlled by keyboard clicks, but specificity is lost because a single action may change display in several directions. When specificity is then further addressed by re-implementing hardware binary functions through the introduction of mode control, the result is a cumbersome interface that fails to achieve the revolutionary benefit required for adoption of a new technology. We address the specificity versus sensitivity problem of volumetric interfaces by providing adaptive positional awareness to the volumetric control device by manipulating communication between hardware driver and existing software methods for volumetric display of medical images. This creates a tethered effect for volumetric display, providing a smooth interface that improves on existing hardware approaches to volumetric scene manipulation.
L(sub 1) Adaptive Flight Control System: Flight Evaluation and Technology Transition
Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Isaac; Gregory, Irene M.; Cao, Chengyu
2010-01-01
Certification of adaptive control technologies for both manned and unmanned aircraft represent a major challenge for current Verification and Validation techniques. A (missing) key step towards flight certification of adaptive flight control systems is the definition and development of analysis tools and methods to support Verification and Validation for nonlinear systems, similar to the procedures currently used for linear systems. In this paper, we describe and demonstrate the advantages of L(sub l) adaptive control architectures for closing some of the gaps in certification of adaptive flight control systems, which may facilitate the transition of adaptive control into military and commercial aerospace applications. As illustrative examples, we present the results of a piloted simulation evaluation on the NASA AirSTAR flight test vehicle, and results of an extensive flight test program conducted by the Naval Postgraduate School to demonstrate the advantages of L(sub l) adaptive control as a verifiable robust adaptive flight control system.
Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton
Kinnaird, Catherine R.; Ferris, Daniel P.
2013-01-01
Locomotor adaptation in humans is not well understood. To provide insight into the neural reorganization that occurs following a significant disruption to one's learned neuromuscular map relating a given motor command to its resulting muscular action, we tied the mechanical action of a robotic exoskeleton to the electromyography (EMG) profile of the soleus muscle during walking. The powered exoskeleton produced an ankle dorsiflexion torque proportional to soleus muscle recruitment thus limiting the soleus' plantar flexion torque capability. We hypothesized that neurologically intact subjects would alter muscle activation patterns in response to the antagonistic exoskeleton by decreasing soleus recruitment. Subjects practiced walking with the exoskeleton for two 30-min sessions. The initial response to the perturbation was to “fight” the resistive exoskeleton by increasing soleus activation. By the end of training, subjects had significantly reduced soleus recruitment resulting in a gait pattern with almost no ankle push-off. In addition, there was a trend for subjects to reduce gastrocnemius recruitment in proportion to the soleus even though only the soleus EMG was used to control the exoskeleton. The results from this study demonstrate the ability of the nervous system to recalibrate locomotor output in response to substantial changes in the mechanical output of the soleus muscle and associated sensory feedback. This study provides further evidence that the human locomotor system of intact individuals is highly flexible and able to adapt to achieve effective locomotion in response to a broad range of neuromuscular perturbations. PMID:23307949
Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton.
Gordon, Keith E; Kinnaird, Catherine R; Ferris, Daniel P
2013-04-01
Locomotor adaptation in humans is not well understood. To provide insight into the neural reorganization that occurs following a significant disruption to one's learned neuromuscular map relating a given motor command to its resulting muscular action, we tied the mechanical action of a robotic exoskeleton to the electromyography (EMG) profile of the soleus muscle during walking. The powered exoskeleton produced an ankle dorsiflexion torque proportional to soleus muscle recruitment thus limiting the soleus' plantar flexion torque capability. We hypothesized that neurologically intact subjects would alter muscle activation patterns in response to the antagonistic exoskeleton by decreasing soleus recruitment. Subjects practiced walking with the exoskeleton for two 30-min sessions. The initial response to the perturbation was to "fight" the resistive exoskeleton by increasing soleus activation. By the end of training, subjects had significantly reduced soleus recruitment resulting in a gait pattern with almost no ankle push-off. In addition, there was a trend for subjects to reduce gastrocnemius recruitment in proportion to the soleus even though only the soleus EMG was used to control the exoskeleton. The results from this study demonstrate the ability of the nervous system to recalibrate locomotor output in response to substantial changes in the mechanical output of the soleus muscle and associated sensory feedback. This study provides further evidence that the human locomotor system of intact individuals is highly flexible and able to adapt to achieve effective locomotion in response to a broad range of neuromuscular perturbations.
Zinniker, D.; Tipple, B.; Pagani, M.
2007-12-01
Unique and abundant secondary metabolites found in waxes and resins of the Callitroid, Cupressoid, and Taxodioid clades of the Cupressaceae family can be identified and quantified in complex mixtures of sedimentary organic compounds. This unusual feature makes it possible to study relatively simple (taxon-specific) isotope systems back in time across the broad array of environments in which these conifers are found. Work on these systems can potentially provide both robust paleoenvironmental proxies (i.e. for source water δD and growing season relative humidity) and quantitative probes into the ecophysiology of these plants in modern and ancient environments. Our research focuses on three genera representing environmental end-members of Cupressaceae - Juniperus, Thuja, and Chamaecyparis - (1) across geographic and environmental gradients in the field, and (2) in specific Holocene and late Pleistocene environmental records. The latter research focuses on peat cores from New England and Oregon and fossil packrat middens from the southwestern United States. Modern transects highlight the sensitivity of Cupressaceae to climatic variables. These include both variables during growth (relative humidity, soil moisture, etc.) and variables affecting seasonal and diurnal growth rates (temperature, winter precipitation, insolation, microhabitat, etc.). Work on ancient records has demonstrated the sensitivity of these unique taxon-specific archives to both subtle and dramatic climate shifts during the Pleistocene and Holocene. This work will result in an improved understanding of climatic and physiological controls on the stable isotopic composition of modern and ancient Cupressaceae - and by extension, other arborescent gymnosperms and C3 plants - providing a framework for understanding more complexly sourced organic inputs to sediments, coals, and petroleum prior to the advent of C4 plants. This research also has direct implications for stratigraphic stable isotope studies
Real-Time Adaptive Control of a Magnetic Levitation System with a Large Range of Load Disturbance.
Zhang, Zhizhou; Li, Xiaolong
2018-05-11
In an idle light-load or a full-load condition, the change of the load mass of a suspension system is very significant. If the control parameters of conventional control methods remain unchanged, the suspension performance of the control system deteriorates rapidly or even loses stability when the load mass changes in a large range. In this paper, a real-time adaptive control method for a magnetic levitation system with large range of mass changes is proposed. First, the suspension control system model of the maglev train is built up, and the stability of the closed-loop system is analyzed. Then, a fast inner current-loop is used to simplify the design of the suspension control system, and an adaptive control method is put forward to ensure that the system is still in a stable state when the load mass varies in a wide range. Simulations and experiments show that when the load mass of the maglev system varies greatly, the adaptive control method is effective to suspend the system stably with a given displacement.
An adaptive neuro-fuzzy controller for mold level control in continuous casting
International Nuclear Information System (INIS)
Zolghadri Jahromi, M.; Abolhassan Tash, F.
2001-01-01
Mold variations in continuous casting are believed to be the main cause of surface defects in the final product. Although a Pid controller is well capable of controlling the level under normal conditions, it cannot prevent large variations of mold level when a disturbance occurs in the form of nozzle unclogging. In this paper, dual controller architecture is presented, a Pid controller is used as the main controller of the plant and an adaptive neuro-fuzzy controller is used as an auxiliary controller to help the Pid during disturbed phases. The control is passed back to the Pid controller after the disturbance is being dealt with. Simulation results prove the effectiveness of this control strategy in reducing mold level variations during the unclogging period
Data adaptive control parameter estimation for scaling laws
Energy Technology Data Exchange (ETDEWEB)
Dinklage, Andreas [Max-Planck-Institut fuer Plasmaphysik, Teilinstitut Greifswald, Wendelsteinstrasse 1, D-17491 Greifswald (Germany); Dose, Volker [Max-Planck- Institut fuer Plasmaphysik, Boltzmannstrasse 2, D-85748 Garching (Germany)
2007-07-01
Bayesian experimental design quantifies the utility of data expressed by the information gain. Data adaptive exploration determines the expected utility of a single new measurement using existing data and a data descriptive model. In other words, the method can be used for experimental planning. As an example for a multivariate linear case, we apply this method for constituting scaling laws of fusion devices. In detail, the scaling of the stellarator W7-AS is examined for a subset of {iota}=1/3 data. The impact of the existing data on the scaling exponents is presented. Furthermore, in control parameter space regions of high utility are identified which improve the accuracy of the scaling law. This approach is not restricted to the presented example only, but can also be extended to non-linear models.
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
Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows
DEFF Research Database (Denmark)
Kirkeby, Carsten Thure; Græsbøll, Kaare; Nielsen, Søren Saxmose
2016-01-01
consequences of continuously adapting the sampling interval in response to the estimated true prevalence in the herd. The key results were that the true prevalence was greatly affected by the hygiene level and to some extent by the test-frequency. Furthermore, the choice of prevalence that will be tolerated...... through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic...... in a control scenario had a major impact on the true prevalence in the normal hygiene setting, but less so when the hygiene was poor. The net revenue is not greatly affected by the test-strategy, because of the general variation in net revenues between farms. An exception to this is the low hygiene herd, where...
Programming adaptive control to evolve increased metabolite production.
Chou, Howard H; Keasling, Jay D
2013-01-01
The complexity inherent in biological systems challenges efforts to rationally engineer novel phenotypes, especially those not amenable to high-throughput screens and selections. In nature, increased mutation rates generate diversity in a population that can lead to the evolution of new phenotypes. Here we construct an adaptive control system that increases the mutation rate in order to generate diversity in the population, and decreases the mutation rate as the concentration of a target metabolite increases. This system is called feedback-regulated evolution of phenotype (FREP), and is implemented with a sensor to gauge the concentration of a metabolite and an actuator to alter the mutation rate. To evolve certain novel traits that have no known natural sensors, we develop a framework to assemble synthetic transcription factors using metabolic enzymes and construct four different sensors that recognize isopentenyl diphosphate in bacteria and yeast. We verify FREP by evolving increased tyrosine and isoprenoid production.
Cerebellar transcranial direct current stimulation improves adaptive postural control.
Poortvliet, Peter; Hsieh, Billie; Cresswell, Andrew; Au, Jacky; Meinzer, Marcus
2018-01-01
Rehabilitation interventions contribute to recovery of impaired postural control, but it remains a priority to optimize their effectiveness. A promising strategy may involve transcranial direct current stimulation (tDCS) of brain areas involved in fine-tuning of motor adaptation. This study explored the effects of cerebellar tDCS (ctDCS) on postural recovery from disturbance by Achilles tendon vibration. Twenty-eight healthy volunteers participated in this sham-ctDCS controlled study. Standing blindfolded on a force platform, four trials were completed: 60 s quiet standing followed by 20 min active (anodal-tDCS, 1 mA, 20 min, N = 14) or sham-ctDCS (40 s, N = 14) tDCS; three quiet standing trials with 15 s of Achilles tendon vibration and 25 s of postural recovery. Postural steadiness was quantified as displacement, standard deviation and path derived from the center of pressure (COP). Baseline demographics and quiet standing postural steadiness, and backwards displacement during vibration were comparable between groups. However, active-tDCS significantly improved postural steadiness during vibration and reduced forward displacement and variability in COP derivatives during recovery. We demonstrate that ctDCS results in short-term improvement of postural adaptation in healthy individuals. Future studies need to investigate if multisession ctDCS combined with training or rehabilitation interventions can induce prolonged improvement of postural balance. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
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.
Considering Variable Road Geometry in Adaptive Vehicle Speed Control
Directory of Open Access Journals (Sweden)
Xinping Yan
2013-01-01
Full Text Available Adaptive vehicle speed control is critical for developing Advanced Driver Assistance Systems (ADAS. Vehicle speed control considering variable road geometry has become a hotspot in ADAS research. In this paper, first, an exploration of intrinsic relationship between vehicle operation and road geometry is made. Secondly, a collaborative vehicle coupling model, a road geometry model, and an AVSC, which can respond to variable road geometry in advance, are developed. Then, based on H∞ control method and the minimum energy principle, a performance index is specified by a cost function for the proposed AVSC, which can explicitly consider variable road geometry in its optimization process. The proposed AVSC is designed by the Hamilton-Jacobi Inequality (HJI. Finally, simulations are carried out by combining the vehicle model with the road geometry model, in an aim of minimizing the performance index of the AVSC. Analyses of the simulation results indicate that the proposed AVSC can automatically and effectively regulate speed according to variable road geometry. It is believed that the proposed AVSC can be used to improve the economy, comfort, and safety effects of current ADAS.
Improving Accuracy of Processing by Adaptive Control Techniques
Directory of Open Access Journals (Sweden)
N. N. Barbashov
2016-01-01
Full Text Available When machining the work-pieces a range of scatter of the work-piece dimensions to the tolerance limit is displaced in response to the errors. To improve an accuracy of machining and prevent products from defects it is necessary to diminish the machining error components, i.e. to improve the accuracy of machine tool, tool life, rigidity of the system, accuracy of adjustment. It is also necessary to provide on-machine adjustment after a certain time. However, increasing number of readjustments reduces the performance and high machine and tool requirements lead to a significant increase in the machining cost.To improve the accuracy and machining rate, various devices of active control (in-process gaging devices, as well as controlled machining through adaptive systems for a technological process control now become widely used. Thus, the accuracy improvement in this case is reached by compensation of a majority of technological errors. The sensors of active control can provide improving the accuracy of processing by one or two quality classes, and simultaneous operation of several machines.For efficient use of sensors of active control it is necessary to develop the accuracy control methods by means of introducing the appropriate adjustments to solve this problem. Methods based on the moving average, appear to be the most promising for accuracy control, since they contain information on the change in the last several measured values of the parameter under control.When using the proposed method in calculation, the first three members of the sequence of deviations remain unchanged, therefore 1 1 x x , 2 2 x x , 3 3 x x Then, for each i-th member of the sequence we calculate that way: , ' i i i x x k x , where instead of the i x values will be populated with the corresponding values ' i x calculated as an average of three previous members:3 ' 1 2 3 i i i i x x x x .As a criterion for the estimate of the control
Versteeg, Inge; Mens, Petra F.
2009-01-01
The objective of this study is to develop and evaluate a simple, cheap, and stable positive control for the quality control and quality assurance (QA) of rapid diagnostic tests (RDT) for the diagnosis of malaria. Plasmodium falciparum in vitro culture of known parasite concentrations was dried on a
Exposure Control Using Adaptive Multi-Stage Item Bundles.
Luecht, Richard M.
This paper presents a multistage adaptive testing test development paradigm that promises to handle content balancing and other test development needs, psychometric reliability concerns, and item exposure. The bundled multistage adaptive testing (BMAT) framework is a modification of the computer-adaptive sequential testing framework introduced by…
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.
Sheikhmoonesi, Fatemeh; Zarghami, Mehran; Mamashli, Shima; Yazdani Charati, Jamshid; Hamzehpour, Romina; Fattahi, Samineh; Azadbakht, Rahil; Kashi, Zahra; Ala, Shahram; Moshayedi, Mona; Alinia, Habibollah; Hendouei, Narjes
2016-01-01
In this study, the aim was to determine whether adding vitamin D to the standard therapeutic regimen of schizophrenic male patients with inadequate vitamin D status could improve some aspects of the symptom burden or not. This study was an open parallel label randomized clinical trial. Eighty patients with chronic stable schizophrenia with residual symptoms and Vitamin D deficiency were recruited randomly and then received either 600000 IU Vitamin D injection once along with their antipsychotic regimen or with their antipsychotic regimen only. Serum vitamin D was measured twice: first at the baseline and again on the fourth month. Positive and Negative Syndrome Scale (PANSS) was assessed at the baseline and on the fourth month. During the study, the vitamin D serum changes in vitamin group and control group were 22.1 ± 19.9(95%CI = 15.9-28.8) and 0.2 ± 1.7(95%CI = 0.2-0.8) (ng/mL) (pvitamin D and control group respectively (p=0.5). The changes of PANSS negative subscale score (N) were -0.1 ± 0.7 (95%CI = -0.3-0.05) and -0.1 ± 0.5 (95%CI = -0.2-0.04) in vitamin D and control group respectively (p = 0.7) and there was a negative but not significant correlation between serum vitamin D level changes and PANSS negative subscale score (r = -0.04, p = 0.7). We did not find a relationship between serum vitamin D level changes and the improvement of negative and positive symptoms in schizophrenic patients and more randomized clinical trials are required to confirm our findings.
Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing
2015-08-01
Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).
International Development Research Centre (IDRC) Digital Library (Canada)
building skills, knowledge or networks on adaptation, ... the African partners leading the AfricaAdapt network, together with the UK-based Institute of Development Studies; and ... UNCCD Secretariat, Regional Coordination Unit for Africa, Tunis, Tunisia .... 26 Rural–urban Cooperation on Water Management in the Context of.
DEFF Research Database (Denmark)
Conrad, Finn; Zhou, Jianjun; Gabacik, Andrzej
1998-01-01
Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control.......Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control....
Interval type-2 fuzzy gain-adaptive controller of a Doubly Fed ...
African Journals Online (AJOL)
... Interval Type-2 Fuzzy Gain Adaptive IP (IT2FGAIP) controller and a conventional IP controller ... and an adaptive IP controller is proposed for the speed control of DFIM in the presence of ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT
Renard, P; Van Breusegem, V; Nguyen, M T; Naveau, H; Nyns, E J
1991-10-20
An adaptive control algorithm has been implemented on a biomethanation process to maintain propionate concentration, a stable variable, at a given low value, by steering the dilution rate. It was thereby expected to ensure the stability of the process during the startup and during steady-state running with an acceptable performance. The methane pilot reactor was operated in the completely mixed, once-through mode and computer-controlled during 161 days. The results yielded the real-life validation of the adaptive control algorithm, and documented the stability and acceptable performance expected.
Decentralized adaptive control of interconnected nonlinear systems with unknown control directions.
Huang, Jiangshuai; Wang, Qing-Guo
2018-03-01
In this paper, we propose a decentralized adaptive control scheme for a class of interconnected strict-feedback nonlinear systems without a priori knowledge of subsystems' control directions. To address this problem, a novel Nussbaum-type function is proposed and a key theorem is drawn which involves quantifying the interconnections of multiple Nussbaum-type functions of the subsystems with different control directions in a single inequality. Global stability of the closed-loop system and asymptotic stabilization of subsystems' output are proved and a simulation example is given to illustrate the effectiveness of the proposed control scheme. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
MTPA control of mechanical sensorless IPMSM based on adaptive nonlinear control.
Najjar-Khodabakhsh, Abbas; Soltani, Jafar
2016-03-01
In this paper, an adaptive nonlinear control scheme has been proposed for implementing maximum torque per ampere (MTPA) control strategy corresponding to interior permanent magnet synchronous motor (IPMSM) drive. This control scheme is developed in the rotor d-q axis reference frame using adaptive input-output state feedback linearization (AIOFL) method. The drive system control stability is supported by Lyapunov theory. The motor inductances are online estimated by an estimation law obtained by AIOFL. The estimation errors of these parameters are proved to be asymptotically converged to zero. Based on minimizing the motor current amplitude, the MTPA control strategy is performed by using the nonlinear optimization technique while considering the online reference torque. The motor reference torque is generated by a conventional rotor speed PI controller. By performing MTPA control strategy, the generated online motor d-q reference currents were used in AIOFL controller to obtain the SV-PWM reference voltages and the online estimation of the motor d-q inductances. In addition, the stator resistance is online estimated using a conventional PI controller. Moreover, the rotor position is detected using the online estimation of the stator flux and online estimation of the motor q-axis inductance. Simulation and experimental results obtained prove the effectiveness and the capability of the proposed control method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Zhi-Lin Zeng
2014-01-01
Full Text Available This paper focuses on high precision leveling control of an underwater heavy load platform, which is viewed as an underwater parallel robot on the basis of its work pattern. The kinematic of platform with deformation is analyzed and the dynamics model of joint space is established. An adaptive backstepping controller according to Lyapunov's function is proposed for leveling control of platform based on joint space. Furthermore, the “lowest point fixed angle error” leveling scheme called “chase” is chosen for leveling control of platform. The digital simulation and practical experiment of single joint space actuator are carried out, and the results show high precision servo control of joint space. On the basis of this, the platform leveling control simulation relies on the hardware-in-loop system. The results indicate that the proposed controller can effectively restrain the influence from system parameter uncertainties and external disturbance to realize high precision leveling control of the underwater platform.
Adaptive robotic control driven by a versatile spiking cerebellar network.
Directory of Open Access Journals (Sweden)
Claudia Casellato
Full Text Available The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning, a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.
Adaptive robotic control driven by a versatile spiking cerebellar network.
Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio
2014-01-01
The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.
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
Adaptive Neuro-Fuzzy Based Gain Controller for Erbium-Doped Fiber Amplifiers
Directory of Open Access Journals (Sweden)
YUCEL, M.
2017-02-01
Full Text Available Erbium-doped fiber amplifiers (EDFA must have a flat gain profile which is a very important parameter such as wavelength division multiplexing (WDM and dense WDM (DWDM applications for long-haul optical communication systems and networks. For this reason, it is crucial to hold a stable signal power per optical channel. For the purpose of overcoming performance decline of optical networks and long-haul optical systems, the gain of the EDFA must be controlled for it to be fixed at a high speed. In this study, due to the signal power attenuation in long-haul fiber optic communication systems and non-equal signal amplification in each channel, an automatic gain controller (AGC is designed based on the adaptive neuro-fuzzy inference system (ANFIS for EDFAs. The intelligent gain controller is implemented and the performance of this new electronic control method is demonstrated. The proposed ANFIS-based AGC-EDFA uses the experimental dataset to produce the ANFIS-based sets and the rule base. Laser diode currents are predicted within the accuracy rating over 98 percent with the proposed ANFIS-based system. Upon comparing ANFIS-based AGC-EDFA and experimental results, they were found to be very close and compatible.
A Study on Mode Confusions in Adaptive Cruise Control Systems
Energy Technology Data Exchange (ETDEWEB)
Ahn, Dae Ryong; Yang, Ji Hyun; Lee, Sang Hun [Kookmin University, Seoul (Korea, Republic of)
2015-05-15
Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions.
A Study on Mode Confusions in Adaptive Cruise Control Systems
International Nuclear Information System (INIS)
Ahn, Dae Ryong; Yang, Ji Hyun; Lee, Sang Hun
2015-01-01
Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions
Information-educational environment with adaptive control of learning process
Modjaev, A. D.; Leonova, N. M.
2017-01-01
Recent years, a new scientific branch connected with the activities in social sphere management developing intensively and it is called "Social Cybernetics". In the framework of this scientific branch, theory and methods of management of social sphere are formed. Considerable attention is paid to the management, directly in real time. However, the decision of such management tasks is largely constrained by the lack of or insufficiently deep study of the relevant sections of the theory and methods of management. The article discusses the use of cybernetic principles in solving problems of control in social systems. Applying to educational activities a model of composite interrelated objects representing the behaviour of students at various stages of educational process is introduced. Statistical processing of experimental data obtained during the actual learning process is being done. If you increase the number of features used, additionally taking into account the degree and nature of variability of levels of current progress of students during various types of studies, new properties of students' grouping are discovered. L-clusters were identified, reflecting the behaviour of learners with similar characteristics during lectures. It was established that the characteristics of the clusters contain information about the dynamics of learners' behaviour, allowing them to be used in additional lessons. The ways of solving the problem of adaptive control based on the identified dynamic characteristics of the learners are planned.
International Nuclear Information System (INIS)
Brazier, J.L.; Guinamant, J.L.
1995-01-01
According to the progress which has been realised in the technology of separating and measuring isotopes, the stable isotopes are used as preferable 'labelling elements' for big number of applications. The isotopic composition of natural products shows significant variations as a result of different reasons like the climate, the seasons, or their geographic origins. So, it was proved that the same product has a different isotopic composition of alimentary and agriculture products. It is also important in detecting the pharmacological and medical chemicals. This review article deals with the technology, like chromatography and spectrophotometry, adapted to this aim, and some important applications. 17 refs. 6 figs
Tracking Control of Hysteretic Piezoelectric Actuator using Adaptive Rate-Dependent Controller.
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.
Alperin, M. J.; Blair, Neal E.; Albert, D. B.; Hoehler, T. M.; Martens, C. S.
1993-01-01
The carbon isotopic composition of methane produced in anoxic marine sediment is controlled by four factors: (1) the pathway of methane formation, (2) the isotopic composition of the methanogenic precursors, (3) the isotope fractionation factors for methane production, and (4) the isotope fractionation associated with methane oxidation. The importance of each factor was evaluated by monitoring stable carbon isotope ratios in methane produced by a sediment microcosm. Methane did not accumulate during the initial 42-day period when sediment contained sulfate, indicating little methane production from 'noncompetitive' substrates. Following sulfate depletion, methane accumulation proceeded in three distinct phases. First, CO2 reduction was the dominant methanogenic pathway and the isotopic composition of the methane produced ranged from -80 to -94 per thousand. The acetate concentration increased during this phase, suggesting that acetoclastic methanogenic bacteria were unable to keep pace with acetate production. Second, acetate fermentation became the dominant methanogenic pathway as bacteria responded to elevated acetate concentrations. The methane produced during this phase was progressively enriched in C-13, reaching a maximum delta(C-13) value of -42 per thousand. Third, the acetate pool experienced a precipitous decline from greater than 5 mM to less than 20 micro-M and methane production was again dominated by CO2 reduction. The delta(C-13) of methane produced during this final phase ranged from -46 to -58 per thousand. Methane oxidation concurrent with methane production was detected throughout the period of methane accumulation, at rates equivalent to 1 to 8 percent of the gross methane production rate. Thus methane oxidation was too slow to have significantly modified the isotopic signature of methane. A comparison of microcosm and field data suggests that similar microbial interactions may control seasonal variability in the isotopic composition of methane
L(sub 1) Adaptive Control Design for NASA AirSTAR Flight Test Vehicle
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.
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
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.
Intelligent control of non-linear dynamical system based on the adaptive neurocontroller
Engel, E.; Kovalev, I. V.; Kobezhicov, V.
2015-10-01
This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.
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)
Robust adaptive fuzzy neural tracking control for a class of unknown ...
Indian Academy of Sciences (India)
In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is ... The robust controller is used to guarantee the stability and to control the per- ..... From the above analysis we have the following theorem:.
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
Walking Flexibility after Hemispherectomy: Split-Belt Treadmill Adaptation and Feedback Control
Choi, Julia T.; Vining, Eileen P. G.; Reisman, Darcy S.; Bastian, Amy J.
2009-01-01
Walking flexibility depends on use of feedback or reactive control to respond to unexpected changes in the environment, and the ability to adapt feedforward or predictive control for sustained alterations. Recent work has demonstrated that cerebellar damage impairs feedforward adaptation, but not feedback control, during human split-belt treadmill…
Objective evaluation of human manual control adaptation boundaries using a cybernetic approach
Lu, T.
2018-01-01
Manual control tasks can be found everywhere in our daily activities, and the human ability to adapt in controlling many different vehicles such as cars and airplanes make it possible for us to travel farther, faster and higher. The human adaptation ability to changes in the controlled element
Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang
2010-09-01
This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.
Personal control over the cure of breast cancer : adaptiveness, underlying beliefs and correlates
Henselmans, Inge; Sanderman, Robbert; Helgeson, Vicki S; de Vries, J; Smink, Ans; Ranchor, Adelita V
OBJECTIVES: Although cognitive adaptation theory suggests that personal control acts as a stress buffer when facing adversity, maladaptive outcomes might occur when control is disconfirmed. The moderating effect of disappointing news on the adaptiveness of personal control over cure in women with
On the necessity of identifying the true parameter in adaptive LQ control
Polderman, Jan W.
1986-01-01
In adaptive control problems one may drop the requirement of identifying the true system in order to simplify the problem of control. It will be shown that in the adaptive LQ control problem this does not at all lead to an easier problem.
Adaptive automatic generation control with superconducting magnetic energy storage in power systems
International Nuclear Information System (INIS)
Tripathy, S.C.; Balasubramanian, R.; Nair, P.S.C.
1992-01-01
An improved automatic generation control (AGC) employing self-tuning adaptive control for both main AGC loop and superconducting magnetic energy storage (SMES) is presented in this paper. Computer simulations on a two-area interconnected power system show that the proposed adaptive control scheme is very effective in damping out oscillations caused by load disturbances and its performance is quite insensitive to controller gain parameter changes of SMES. A comprehensive comparative performance evaluation of control schemes using adaptive and non-adaptive controllers in the main AGC and in the SMES control loops is presented. The improvement in performance brought in by the adaptive scheme is particularly pronounced for load changes of random magnitude and duration. The proposed controller can be easily implemented using microprocessors
Adaptive, Distributed Control of Constrained Multi-Agent Systems
Bieniawski, Stefan; Wolpert, David H.
2004-01-01
Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.
Adaptive Feed-Forward Control of Low Frequency Interior Noise
Kletschkowski, Thomas
2012-01-01
This book presents a mechatronic approach to Active Noise Control (ANC). It describes the required elements of system theory, engineering acoustics, electroacoustics and adaptive signal processing in a comprehensive, consistent and systematic manner using a unified notation. Furthermore, it includes a design methodology for ANC-systems, explains its application and describes tools to be used for ANC-system design. From the research point of view, the book presents new approaches to sound source localization in weakly damped interiors. One is based on the inverse finite element method, the other is based on a sound intensity probe with an active free field. Furthermore, a prototype of an ANC-system able to reach the physical limits of local (feed-forward) ANC is described. This is one example for applied research in ANC-system design. Other examples are given for (i) local ANC in a semi-enclosed subspace of an aircraft cargo hold and (ii) for the combination of audio entertainment with ANC.
Control code for laboratory adaptive optics teaching system
Jin, Moonseob; Luder, Ryan; Sanchez, Lucas; Hart, Michael
2017-09-01
By sensing and compensating wavefront aberration, adaptive optics (AO) systems have proven themselves crucial in large astronomical telescopes, retinal imaging, and holographic coherent imaging. Commercial AO systems for laboratory use are now available in the market. One such is the ThorLabs AO kit built around a Boston Micromachines deformable mirror. However, there are limitations in applying these systems to research and pedagogical projects since the software is written with limited flexibility. In this paper, we describe a MATLAB-based software suite to interface with the ThorLabs AO kit by using the MATLAB Engine API and Visual Studio. The software is designed to offer complete access to the wavefront sensor data, through the various levels of processing, to the command signals to the deformable mirror and fast steering mirror. In this way, through a MATLAB GUI, an operator can experiment with every aspect of the AO system's functioning. This is particularly valuable for tests of new control algorithms as well as to support student engagement in an academic environment. We plan to make the code freely available to the community.
Directory of Open Access Journals (Sweden)
Saifullah Khalid
2016-09-01
Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.
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.
Lag Synchronization Between Two Coupled Networks via Open-Plus-Closed-Loop and Adaptive Controls
International Nuclear Information System (INIS)
Tong-Chun Hu; Yong-Qing Wu; Shi-Xing Li
2016-01-01
In this paper, we study lag synchronization between two coupled networks and apply two types of control schemes, including the open-plus-closed-loop (OPCL) and adaptive controls. We then design the corresponding control algorithms according to the OPCL and adaptive feedback schemes. With the designed controllers, we obtain two theorems on the lag synchronization based on Lyapunov stability theory and Barbalat's lemma. Finally we provide numerical examples to show the effectiveness of the obtained controllers and see that the adaptive control is stronger than the OPCL control when realizing the lag synchronization between two coupled networks with different coupling structures. (paper)
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.
National Research Council Canada - National Science Library
Diedrich, Frederick J; Hocevar, Susan P; Entin, Elliot E; Hutchins, Susan G; Kemple, William G; Kleinman, Davied L
2005-01-01
... on the behaviors of organizations as they strive to adapt. In this paper, we present a series of lessons learned based on a pilot experiment in which we explored the performance of two organizations...
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.
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
DEFF Research Database (Denmark)
Augustsson, Per; Barnkob, Rune; Wereley, Steven T.
2011-01-01
We present a platform for micro particle image velocimetry (μPIV), capable of carrying out full-channel, temperature-controlled, long-term-stable, and automated μPIV-measurement of microchannel acoustophoresis with uncertainties below 5% and a spatial resolution in the order of 20 μm. A method to...
Directory of Open Access Journals (Sweden)
Chuanjing Hou
2015-01-01
Full Text Available An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.
Hou, Chuanjing; Hu, Lisheng; Zhang, Yingwei
2015-01-01
An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.
Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control
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
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
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)
Indirect fuzzy adaptive control of a class of SISO nonlinear systems
International Nuclear Information System (INIS)
Laboid, S.; Boucherit, M.S.
2006-01-01
This paper presents an adaptive fuzzy control scheme for a class of continuous-time single-input single-output nonlinear systems with unknown dynamics and disturbance. Within this scheme, the fuzzy systems are employed to approximate the unknown system's dynamics. The proposed controller is composed of a well-defined adaptive fuzzy control term that uses the adaptive fuzzy approximation errors and disturbance. Based on a Lyapunov synthesis method, it is shown that the proposed adaptive control scheme guarantees the convergence of the tracking error to zero and the global boundedness of all signals in the closed-loop system. Moreover, the proposed controller allows initialization by zero of all adjusted parameters in the fuzzy approximators, and does not require the knowledge of the lower bound of the control gain and upper bounds of the approximation errors and disturbance. Simulation results performed on an inverted pendulum system are given to point out the good performance of the developed adaptive controller. (author)
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.
Adaptive fuzzy control of neutron power of the TRIGA Mark III reactor
International Nuclear Information System (INIS)
Rojas R, E.
2014-01-01
The design and implementation of an identification and control scheme of the TRIGA Mark III research nuclear reactor of the Instituto Nacional de Investigaciones Nucleares (ININ) of Mexico is presented in this thesis work. The identification of the reactor dynamics is carried out using fuzzy logic based systems, in which a learning process permits the adjustment of the membership function parameters by means of techniques based on neural networks and bio-inspired algorithms. The resulting identification system is a useful tool that allows the emulation of the reactor power behavior when different types of insertions of reactivity are applied into the core. The identification of the power can also be used for the tuning of the parameters of a control system. On the other hand, the regulation of the reactor power is carried out by means of an adaptive and stable fuzzy control scheme. The control law is derived using the input-output linearization technique, which permits the introduction of a desired power profile for the plant to follow asymptotically. This characteristic is suitable for managing the ascent of power from an initial level n o up to a predetermined final level n f . During the increase of power, a constraint related to the rate of change in power is considered by the control scheme, thus minimizing the occurrence of a safety reactor shutdown due to a low reactor period value. Furthermore, the theory of stability in the sense of Lyapunov is used to obtain a supervisory control law which maintains the power error within a tolerance region, thus guaranteeing the stability of the power of the closed loop system. (Author)
Real-time performance assessment and adaptive control for a water chiller unit in an HVAC system
Bai, Jianbo; Li, Yang; Chen, Jianhao
2018-02-01
The paper proposes an adaptive control method for a water chiller unit in a HVAC system. Based on the minimum variance evaluation, the adaptive control method was used to realize better control of the water chiller unit. To verify the performance of the adaptive control method, the proposed method was compared with an a conventional PID controller, the simulation results showed that adaptive control method had superior control performance to that of the conventional PID controller.
Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems
International Nuclear Information System (INIS)
Chang Weider; Yan Junjuh
2005-01-01
A robust adaptive PID controller design motivated from the sliding mode control is proposed for a class of uncertain chaotic systems in this paper. Three PID control gains, K p , K i , and K d , are adjustable parameters and will be updated online with an adequate adaptation mechanism to minimize a previously designed sliding condition. By introducing a supervisory controller, the stability of the closed-loop PID control system under with the plant uncertainty and external disturbance can be guaranteed. Finally, a well-known Duffing-Holmes chaotic system is used as an illustrative to show the effectiveness of the proposed robust adaptive PID controller
Multiple Model Adaptive Attitude Control of LEO Satellite with Angular Velocity Constraints
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.
Induction machine Direct Torque Control system based on fuzzy adaptive control
Li, Shi-ping; Yu, Yan; Jiao, Zhen-gang; Gu, Shu-sheng
2009-07-01
Direct Torque Control technology is a high-performance communication control method, it uses the space voltage vector method, and then to the inverter switch state control, to obtain high torque dynamic performance. But none of the switching states is able to generate the exact voltage vector to produce the desired changes in torque and flux in most of the switching instances. This causes a high ripple in torque. To solve this problem, a fuzzy implementation of Direct Torque Control of Induction machine is presented here. Error of stator flux, error of motor electromagnetic torque and position of angle of flux are taken as fuzzy variables. In order to further solve nonlinear problem of variation parameters in direct torque control system, the paper proposes a fuzzy parameter PID adaptive control method which is suitable for the direct torque control of an asynchronous motor. The generation of its fuzzy control is obtained by analyzing and optimizing PID control step response and combining expert's experience. For this reason, it carries out fuzzy work to PID regulator of motor speed to achieve to regulate PID parameters. Therefore the control system gets swifter response velocity, stronger robustness and higher precision of velocity control. The computer simulated results verify the validity of this novel method.
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.
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
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
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.
A Formal Framework for Adaptive Access Control Models.
Spaccapietra, S.; Rinderle, S.B.; Reichert, M.U.
For several reasons enterprises are frequently subject to organizational change. Respective adaptations may concern business processes, but also other components of an enterprise architecture. In particular, changes of organizational structures often become necessary. The information about