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Sample records for stable adaptive control

  1. Adaptive PID Controller Using RLS for SISO Stable and Unstable Systems

    Directory of Open Access Journals (Sweden)

    Rania A. Fahmy

    2014-01-01

    Full Text Available The proportional-integral-derivative (PID is still the most common controller and stabilizer used in industry due to its simplicity and ease of implementation. In most of the real applications, the controlled system has parameters which slowly vary or are uncertain. Thus, PID gains must be adapted to cope with such changes. In this paper, adaptive PID (APID controller is proposed using the recursive least square (RLS algorithm. RLS algorithm is used to update the PID gains in real time (as system operates to force the actual system to behave like a desired reference model. Computer simulations are given to demonstrate the effectiveness of the proposed APID controller on SISO stable and unstable systems considering the presence of changes in the systems parameters.

  2. Stable neural-network-based adaptive control for sampled-data nonlinear systems.

    Science.gov (United States)

    Sun, F; Sun, Z; Woo, P Y

    1998-01-01

    For a class of multiinput-multioutput (MIMO) sampled-data nonlinear systems with unknown dynamic nonlinearities, a stable neural-network (NN)-based adaptive control approach which is an integration of an NN approach and the adaptive implementation of the variable structure control with a sector, is developed. The sampled-data nonlinear system is assumed to be controllable and its state vector is available for measurement. The variable structure control with a sector serves two purposes. One is to force the system state to be within the state region in which the NN's are used when the system goes out of neural control; and the other is to provide an additional control until the system tracking error metric is controlled inside the sector within the network approximation region. The proof of a complete stability and a tracking error convergence is given and the setting of the sector and the NN parameters is discussed. It is demonstrated that the asymptotic error of the system can be made dependent only on inherent network approximation errors and the frequency range of unmodeled dynamics. Simulation studies of a two-link manipulator show the effectiveness of the proposed control approach.

  3. Dynamic recurrent neural networks for stable adaptive control of wing rock motion

    Science.gov (United States)

    Kooi, Steven Boon-Lam

    Wing rock is a self-sustaining limit cycle oscillation (LCO) which occurs as the result of nonlinear coupling between the dynamic response of the aircraft and the unsteady aerodynamic forces. In this thesis, dynamic recurrent RBF (Radial Basis Function) network control methodology is proposed to control the wing rock motion. The concept based on the properties of the Presiach hysteresis model is used in the design of dynamic neural networks. The structure and memory mechanism in the Preisach model is analogous to the parallel connectivity and memory formation in the RBF neural networks. The proposed dynamic recurrent neural network has a feature for adding or pruning the neurons in the hidden layer according to the growth criteria based on the properties of ensemble average memory formation of the Preisach model. The recurrent feature of the RBF network deals with the dynamic nonlinearities and endowed temporal memories of the hysteresis model. The control of wing rock is a tracking problem, the trajectory starts from non-zero initial conditions and it tends to zero as time goes to infinity. In the proposed neural control structure, the recurrent dynamic RBF network performs identification process in order to approximate the unknown non-linearities of the physical system based on the input-output data obtained from the wing rock phenomenon. The design of the RBF networks together with the network controllers are carried out in discrete time domain. The recurrent RBF networks employ two separate adaptation schemes where the RBF's centre and width are adjusted by the Extended Kalman Filter in order to give a minimum networks size, while the outer networks layer weights are updated using the algorithm derived from Lyapunov stability analysis for the stable closed loop control. The issue of the robustness of the recurrent RBF networks is also addressed. The effectiveness of the proposed dynamic recurrent neural control methodology is demonstrated through simulations to

  4. 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.)

  5. Adaptive nonlinear flight control

    Science.gov (United States)

    Rysdyk, Rolf Theoduor

    1998-08-01

    Research under supervision of Dr. Calise and Dr. Prasad at the Georgia Institute of Technology, School of Aerospace Engineering. has demonstrated the applicability of an adaptive controller architecture. The architecture successfully combines model inversion control with adaptive neural network (NN) compensation to cancel the inversion error. The tiltrotor aircraft provides a specifically interesting control design challenge. The tiltrotor aircraft is capable of converting from stable responsive fixed wing flight to unstable sluggish hover in helicopter configuration. It is desirable to provide the pilot with consistency in handling qualities through a conversion from fixed wing flight to hover. The linear model inversion architecture was adapted by providing frequency separation in the command filter and the error-dynamics, while not exiting the actuator modes. This design of the architecture provides for a model following setup with guaranteed performance. This in turn allowed for convenient implementation of guaranteed handling qualities. A rigorous proof of boundedness is presented making use of compact sets and the LaSalle-Yoshizawa theorem. The analysis allows for the addition of the e-modification which guarantees boundedness of the NN weights in the absence of persistent excitation. The controller is demonstrated on the Generic Tiltrotor Simulator of Bell-Textron and NASA Ames R.C. The model inversion implementation is robustified with respect to unmodeled input dynamics, by adding dynamic nonlinear damping. A proof of boundedness of signals in the system is included. The effectiveness of the robustification is also demonstrated on the XV-15 tiltrotor. The SHL Perceptron NN provides a more powerful application, based on the universal approximation property of this type of NN. The SHL NN based architecture is also robustified with the dynamic nonlinear damping. A proof of boundedness extends the SHL NN augmentation with robustness to unmodeled actuator

  6. Commande floue adaptative directe stable étendue appliquée à la ...

    African Journals Online (AJOL)

    Administrateur

    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 ...

  7. Fuzzy controller adaptation

    Science.gov (United States)

    Myravyova, E. A.; Sharipov, M. I.; Radakina, D. S.

    2017-10-01

    During writing this work, the fuzzy controller with a double base of rules was studied, which was applied for the synthesis of the automated control system. A method for fuzzy controller adaptation has been developed. The adaptation allows the fuzzy controller to automatically compensate for parametric interferences that occur at the control object. Specifically, the fuzzy controller controlled the outlet steam temperature in the boiler unit BKZ-75-39 GMA. The software code was written in the programming support environment Unity Pro XL designed for fuzzy controller adaptation.

  8. Stable and self-adaptive performance of mechanically pumped CO2 two-phase loops for AMS-02 tracker thermal control in vacuum

    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.

  9. Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets

    Science.gov (United States)

    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.

  10. 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.

  11. Adaptive sequential controller

    Science.gov (United States)

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

    1994-01-01

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

  12. 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...... is controlled using wall mounted ventilation flaps. In the paper an algorithm for air flow control is presented meeting the needs for temperature and humidity while taking the air flow pattern in consideration. To obtain simple and realisable controllers a model based control design method is applied....... In the design dynamic models for temperature and humidity are very important elements and effort is put into deriving and testing the models. It turns out that non-linearities are dominating in both models making feedback linearization the natural design method. The air controller as well as the temperature...

  13. 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.

  14. Face adaptation: Changing stable representations of familiar faces within minutes?

    Directory of Open Access Journals (Sweden)

    Claus-Christian Carbon

    2005-01-01

    Full Text Available Three experiments are reported showing that the perception and the assessment of veridicality of familiar faces are highly adaptive to new visual information. Subjects were asked to discriminate between real photographs and altered versions of celebrities. Exposing participants to extremely deviated versions changed the usually stable representations of the famous faces within a very short time. In Experiment 1, exposure to an extreme face version resulted in identity decisions shifted towards the exposed one. Experiment 2 revealed that the effects are not short lasting. In Experiment 3, we showed that the effect also generalizes to different pictures of the same famous person. Together the experiments seem to indicate that the brain permanently adapts to new perceptual information and integrates new data within already elaborated representations in a fast way.

  15. Graceful degradation of cooperative adaptive cruise control

    NARCIS (Netherlands)

    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

  16. Efficient adaptive fuzzy control scheme

    NARCIS (Netherlands)

    Papp, Z.; Driessen, B.J.F.

    1995-01-01

    The paper presents an adaptive nonlinear (state-) feedback control structure, where the nonlinearities are implemented as smooth fuzzy mappings defined as rule sets. The fine tuning and adaption of the controller is realized by an indirect adaptive scheme, which modifies the parameters of the fuzzy

  17. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C

    2009-01-01

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

  18. A robust adaptive robot controller

    NARCIS (Netherlands)

    Berghuis, Harry; Berghuis, Harry; Ortega, Romeo; Nijmeijer, Henk

    1993-01-01

    A globally convergent adaptive control scheme for robot motion control with the following features is proposed. First, the adaptation law possesses enhanced robustness with respect to noisy velocity measurements. Second, the controller does not require the inclusion of high gain loops that may

  19. Adaptive control for chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Hua Changchun E-mail: cch@ysu.edu.cn; Guan Xinping

    2004-10-01

    Control problem of chaotic system is investigated via adaptive method. A fairly simple adaptive controller is constructed, which can control chaotic systems to unstable fixed points. The precise mathematical models of chaotic systems need not be known and only the fixed points and the dimensions of chaotic systems are required to be known. Simulations on controlling different chaotic systems are investigated and the results show the validity and feasibility of the proposed controller.

  20. 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)....

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

    Data.gov (United States)

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

  2. Adaptive unmanned aerial vechile control

    OpenAIRE

    Bernotaitis, Vilimantas

    2016-01-01

    This thesis analyzes unmanned aerial vehicles and its adaptivity - their structures, operational principles and components. Also analyzing algorithms of adaptive neural networks and their usage in unmanned aerial vehicles. The main objective of this thesis is to analyze structures, control systems of unmanned aerial vehicles and their abilities to adapt to changing environment. This thesis contains analysis of already used solutions and their drawbacks. As research made in this thesis shown t...

  3. 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.

  4. Evaluation of a Neural Adaptive Flight Controller

    Science.gov (United States)

    Totah, Joseph J.

    1997-01-01

    The objective of this paper is to present results from the evaluation of a direct adaptive tracking controller. The control architecture employs both pre-trained and an on-line neural networks to represent the non-linear aircraft dynamics in the model inversion portion of the controller. The aircraft model used for this evaluation is representative of the F-15 Advanced Control Technology for Integrated Vehicles (ACTIVE) aircraft. The controller was evaluated for three cases: (1) nominal conditions; (2) loss of control power; and (3) loss of control power in the presence of atmospheric turbulence. The results were compared with the existing F-15 ACTIVE conventional mode controller in all cases. The results indicate extremely desirable airframe stabilization characteristics for case (1) that do not degrade significantly for case (2) or (3) as does the conventional mode controller. It was concluded that this controller exhibits both stable and robust adaptive characteristics when subjected to mild and extreme loss of control power conditions. Integration of this neural adaptive flight controller into the full non-linear six degree-of-freedom F-15 ACTIVE simulation is recommended for evaluation in a real-time high fidelity piloted simulation environment.

  5. Controlling smart grid adaptivity

    NARCIS (Netherlands)

    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

  6. Hybrid Adaptive Flight Control with Model Inversion Adaptation

    Science.gov (United States)

    Nguyen, Nhan

    2011-01-01

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

  7. 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...... role. If it can be emphasis on control design. The models have beenvalidated by experimental data obtained from an existing wind turbine. The e ective wind speed experienced by the rotor of a wind turbine, which is often required by some control methods, is estimated by using a wind turbine as a wind...

  8. Dynamics and control of twisting bi-stable structures

    Science.gov (United States)

    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

  9. Active Fault Tolerant Control of Livestock Stable Ventilation System

    DEFF Research Database (Denmark)

    Gholami, Mehdi

    2011-01-01

    degraded performance even in the faulty case. In this thesis, we have designed such controllers for climate control systems for livestock buildings in three steps: Deriving a model for the climate control system of a pig-stable. Designing a active fault diagnosis (AFD) algorithm for different kinds...... of the hybrid model are estimated by a recursive estimation algorithm, the Extended Kalman Filter (EKF), using experimental data which was provided by an equipped laboratory. Two methods for active fault diagnosis are proposed. The AFD methods excite the system by injecting a so-called excitation input. In both...... methods, the input is designed off-line based on a sensitivity analysis in order to improve the precision of estimation of parameters associated with faults. Two different algorithm, the EKF and a new adaptive filter, are used to estimate the parameters of the system. The fault is detected and isolated...

  10. Stable swarming using adaptive long-range interactions

    Science.gov (United States)

    Gorbonos, Dan; Gov, Nir S.

    2017-04-01

    Sensory mechanisms in biology, from cells to humans, have the property of adaptivity, whereby the response produced by the sensor is adapted to the overall amplitude of the signal, reducing the sensitivity in the presence of strong stimulus, while increasing it when it is weak. This property is inherently energy consuming and a manifestation of the nonequilibrium nature of living organisms. We explore here how adaptivity affects the effective forces that organisms feel due to others in the context of a uniform swarm, in both two and three dimensions. The interactions between the individuals are taken to be attractive and long-range and of power-law form. We find that the effects of adaptivity inside the swarm are dramatic, where the effective forces decrease (or remain constant) with increasing swarm density. Linear stability analysis demonstrates how this property prevents collapse (Jeans instability), when the forces are adaptive. Adaptivity therefore endows swarms with a natural mechanism for self-stabilization.

  11. Adaptive governance : Towards a stable, accountable and responsive government

    NARCIS (Netherlands)

    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

  12. 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

  13. Adaptive Controller Design for Faulty UAVs via Quantum Information Technology

    Directory of Open Access Journals (Sweden)

    Fuyang Chen

    2012-12-01

    Full Text Available In this paper, an adaptive controller is designed for a UAV flight control system against faults and parametric uncertainties based on quantum information technology and the Popov hyperstability theory. First, considering the bounded control input, the state feedback controller is designed to make the system stable. The model of adaptive control is introduced to eliminate the impact by the uncertainties of system parameters via quantum information technology. Then, according to the model reference adaptive principle, an adaptive control law based on the Popov hyperstability theory is designed. This law enable better robustness of the flight control system and tracking control performances. The closed-loop system's stability is guaranteed by the Popov hyperstability theory. The simulation results demonstrate that a better dynamic performance of the UAV flight control system with faults and parametric uncertainties can be maintained with the proposed method.

  14. Direct Adaptive Control Of An Industrial Robot

    Science.gov (United States)

    Seraji, Homayoun; Lee, Thomas; Delpech, Michel

    1992-01-01

    Decentralized direct adaptive control scheme for six-jointed industrial robot eliminates part of overall computational burden imposed by centralized controller and degrades performance of robot by reducing sampling rate. Control and controller-adaptation laws based on observed performance of manipulator: no need to model dynamics of robot. Adaptive controllers cope with uncertainties and variations in robot and payload.

  15. Commande floue adaptative directe stable étendue appliquée à la ...

    African Journals Online (AJOL)

    Les résultats obtenus montrent que la commande floue adaptative directe stable étendue a prouvé une grande efficacité et une bonne robustesse en présence des variations paramétriques et de perturbations. Mots clé: Machine asynchrone- Systèmes flous- Commande par logique floue- Commande adaptative- lois ...

  16. Adaptive stochastic disturbance accommodating control

    Science.gov (United States)

    George, Jemin; Singla, Puneet; Crassidis, John L.

    2011-02-01

    This article presents a Kalman filter based adaptive disturbance accommodating stochastic control scheme for linear uncertain systems to minimise the adverse effects of both model uncertainties and external disturbances. Instead of dealing with system uncertainties and external disturbances separately, the disturbance accommodating control scheme lumps the overall effects of these errors in a to-be-determined model-error vector and then utilises a Kalman filter in the feedback loop for simultaneously estimating the system states and the model-error vector from noisy measurements. Since the model-error dynamics is unknown, the process noise covariance associated with the model-error dynamics is used to empirically tune the Kalman filter to yield accurate estimates. A rigorous stochastic stability analysis reveals a lower bound requirement on the assumed system process noise covariance to ensure the stability of the controlled system when the nominal control action on the true plant is unstable. An adaptive law is synthesised for the selection of stabilising system process noise covariance. Simulation results are presented where the proposed control scheme is implemented on a two degree-of-freedom helicopter.

  17. Adaptive Controller Effects on Pilot Behavior

    Science.gov (United States)

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

    2014-01-01

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

  18. 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 new...... system. This paper presents a novel method of introducing new control components in a smooth manner, providing stability guarantees during the transition phase, and which retains the original control structure....

  19. 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...

  20. Disturbance Accommodating Adaptive Control with Application to Wind Turbines

    Science.gov (United States)

    Frost, Susan

    2012-01-01

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

  1. Stable Neural Control of Uncertain Multivariable Systems

    National Research Council Canada - National Science Library

    Mears, Mark

    2001-01-01

    ... that the trajectories remain bonded. Lyapunov analysis is used to derive equations for the sliding mode control, neural network training, and to show uniform ultimate boundedness of the closed loop systems...

  2. An adaptive fuzzy logic controller for robot-manipulator

    Directory of Open Access Journals (Sweden)

    Ho Dac Loc

    2004-06-01

    Full Text Available In this paper, an adaptive fuzzy controller is designed for the robot-manipulator. The synthesized controller ensures that 1 the close-loop system is globally stable and 2 the tracking error converges to zero asymptotically and a cost function is minimized. The fuzzy controller is synthesized from a collection of IF-THEN rules. The parameters of the membership functions characterizing the linguistic terms change according to some adaptive law for the purpose of controlling a plant to track a reference trajectory. The proposed control scheme is demonstrated in a typical nonlinear plant two link manipulator. The computer simulation of control is done by the language MATLAB. The results of simulation show that the adaptive controller well operates and provides good qualities of the control system. The presented results are analyzed.

  3. Almost optimal adaptive LQ control: SISO case

    NARCIS (Netherlands)

    Polderman, Jan W.; Daams, Jasper

    2002-01-01

    In this paper an almost optimal indirect adaptive controller for input/output dynamical systems is proposed. The control part of the adaptive control scheme is based on a modified LQ control law: by adding a time-varying gain to the certainty equivalent control law the conflict between

  4. Statistical Physics for Adaptive Distributed Control

    Science.gov (United States)

    Wolpert, David H.

    2005-01-01

    A viewgraph presentation on statistical physics for distributed adaptive control is shown. The topics include: 1) The Golden Rule; 2) Advantages; 3) Roadmap; 4) What is Distributed Control? 5) Review of Information Theory; 6) Iterative Distributed Control; 7) Minimizing L(q) Via Gradient Descent; and 8) Adaptive Distributed Control.

  5. Flight Test Approach to Adaptive Control Research

    Science.gov (United States)

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

    2011-01-01

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

  6. Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

    Science.gov (United States)

    Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

    1992-01-01

    A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

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

    Science.gov (United States)

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

    2018-01-01

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

  8. Embedded Controller Design for Pig Stable Ventilation Systems

    DEFF Research Database (Denmark)

    Jessen, Jan Jacob

    present an early result for performing system identification for zone based climate dynamics, based on an idea of guaranteed internal flow directions. Paper 6 presents a verified stable distributed temperature controller for pig stables divided into zones. Paper 7 is an expanded journal version of paper 6......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...... from the Mathworks' range of products and automatic code generation. It is furthermore shown how to build new climate control systems based on cheap and readily available hardware and software. An early result for performing system identification for zone based climate dynamics is also presented...

  9. Optimal model distributions in supervisory adaptive control

    NARCIS (Netherlands)

    Ghosh, D.; Baldi, S.

    2017-01-01

    Several classes of multi-model adaptive control schemes have been proposed in literature: instead of one single parameter-varying controller, in this adaptive methodology multiple fixed-parameter controllers for different operating regimes (i.e. different models) are utilised. Despite advances in

  10. A robust adaptive controller for robot manipulators

    NARCIS (Netherlands)

    Berghuis, Harry; Berghuis, Harry; Ortega, Romeo; Nijmeijer, Henk

    1992-01-01

    The authors propose a globally convergent adaptive control scheme for robot motion control with the following features: first, the adaptation law processes enhanced robustness with respect to noisy velocity measurements; secondly, the controller does not require the inclusion of high-gain loops that

  11. Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting

    Science.gov (United States)

    Trujillo, Anna; Gregory, Irene

    2013-01-01

    Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.

  12. 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.

  13. Robust Adaptive Control of Multivariable Nonlinear Systems

    Science.gov (United States)

    2011-03-28

    On the commercial side, the implementation of L1 adaptive controller on NASA’s subscale generic transport model (GTM) aircraft demonstrated...I. Gregory, L. Valavani, Experimental Validation of 1L Adaptive Control: Rohrs ’ Counterexample in Flight, Submitted to AIAA Journal of Guidance

  14. Adaptive Method Using Controlled Grid Deformation

    Directory of Open Access Journals (Sweden)

    Florin FRUNZULICA

    2011-09-01

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

  15. Research in Neural Network Based Adaptive Control

    National Research Council Canada - National Science Library

    Calise, Anthony

    2000-01-01

    .... We regard this as a major step towards flight certification of adaptive controllers. The approach is more general in that it permits a broad class of input nonlinearities, including such effects as discrete and bang/bang control...

  16. Adaptive Control Methods for Soft Robots

    Data.gov (United States)

    National Aeronautics and Space Administration — I propose to develop methods for soft and inflatable robots that will allow the control system to adapt and change control parameters based on changing conditions...

  17. Quantum Transduction with Adaptive Control.

    Science.gov (United States)

    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.

  18. Adaptive Dynamic Programming for Control Algorithms and Stability

    CERN Document Server

    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-...

  19. An adaptive fuzzy logic controller for robot-manipulator

    Directory of Open Access Journals (Sweden)

    Tran Thu Ha

    2008-11-01

    Full Text Available In this paper, an adaptive fuzzy controller is designed for the robot-manipulator. The synthesized controller ensures that 1 the close-loop system is globally stable and 2 the tracking error converges to zero asymptotically and a cost function is minimized. The fuzzy controller is synthesized from a collection of IF-THEN rules. The parameters of the membership functions characterizing the linguistic terms change according to some adaptive law for the purpose of controlling a plant to track a reference trajectory. The proposed control scheme is demonstrated in a typical nonlinear plant two link manipulator. The computer simulation of control is done by the language MATLAB. The results of simulation show that the adaptipresented results are analyzed.

  20. Flight Approach to Adaptive Control Research

    Science.gov (United States)

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

    2011-01-01

    The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight 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.

  1. 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 ...

  2. 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 ...

  3. Adaptive Control of Chaos in Chua's Circuit

    Directory of Open Access Journals (Sweden)

    Weiping Guo

    2011-01-01

    Full Text Available A feedback control method and an adaptive feedback control method are proposed for Chua's circuit chaos system, which is a simple 3D autonomous system. The asymptotical stability is proven with Lyapunov theory for both of the proposed methods, and the system can be dragged to one of its three unstable equilibrium points respectively. Simulation results show that the proposed methods are valid, and control performance is improved through introducing adaptive technology.

  4. Adaptive Flight Control Research at NASA

    Science.gov (United States)

    Motter, Mark A.

    2008-01-01

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

  5. Adaptive feedback control for a class of chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Hua Changchun E-mail: cch@ysu.edu.cn; Guan Xinping E-mail: xpguan@ysu.edu.cn; Shi Peng

    2005-02-01

    In this paper, the problem of control for a class of chaotic systems is considered. The nonlinear functions of chaotic systems are not necessarily to satisfy the Lipsichtz conditions, but bounded by a polynomial with the gains unknown. Employing adaptive method, the corresponding controller which renders the closed-loop system asymptotically stable is constructed. The designed controller is robust with respect to certain class of disturbances in the chaotic systems. Simulations on unified chaotic systems and Arneodo chaotic system are performed and the results verify the validity of the proposed techniques.

  6. Adaptive fuzzy PID control of hydraulic servo control system for large axial flow compressor

    Science.gov (United States)

    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.

  7. Adaptive Feedfoward Feedback Control Framework Project

    Data.gov (United States)

    National Aeronautics and Space Administration — An Adaptive Feedforward and Feedback Control (AFFC) Framework is proposed to suppress the aircraft's structural vibrations and to increase the resilience of the...

  8. Multiple model adaptive control with mixing

    Science.gov (United States)

    Kuipers, Matthew

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

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

    Science.gov (United States)

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

    2018-01-01

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

  10. Stochastic Adaptive Control and Estimation Enhancement

    Science.gov (United States)

    1990-02-01

    multioutput ARMA system. The plant has constant but unknown parameters. The cautious controller with a one-step horizon and a new dual controller with a two...system is shown to be stable. Multiinput multioutput systems with unknown parameters are encoun- Remark 4.1: tered in many practical situations, and...dual (181 B. Witterunark, "An active suboptimal dual controller for systems with stochastic c irfsoluin applied t-a multiipvt multioutput model

  11. Maritime Adaptive Optics Beam Control

    Science.gov (United States)

    2010-09-01

    Griot Helium Neon Class II laser with output power of 0.5 mW, operating at a wavelength of 633 nm. The science camera is an IDS uEye-2210SE CCD camera...produced by Edmund Optics, Newport/New Focus, Thor Labs, and CVI Melles Griot . Two computer controllers are used for the full experimental system. The

  12. Decentralized adaptive control of robot manipulators with robust stabilization design

    Science.gov (United States)

    Yuan, Bau-San; Book, Wayne J.

    1988-01-01

    Due to geometric nonlinearities and complex dynamics, a decentralized technique for adaptive control for multilink robot arms is attractive. Lyapunov-function theory for stability analysis provides an approach to robust stabilization. Each joint of the arm is treated as a component subsystem. The adaptive controller is made locally stable with servo signals including proportional and integral gains. This results in the bound on the dynamical interactions with other subsystems. A nonlinear controller which stabilizes the system with uniform boundedness is used to improve the robustness properties of the overall system. As a result, the robot tracks the reference trajectories with convergence. This strategy makes computation simple and therefore facilitates real-time implementation.

  13. Adaptive Control Strategies for Flexible Robotic Arm

    Science.gov (United States)

    Bialasiewicz, Jan T.

    1996-01-01

    The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.

  14. AI-based adaptive control and design of autopilot system for ...

    Indian Academy of Sciences (India)

    Artificial Intelligence (AI)-based controllers such as fuzzy logic PD, fuzzy logic PD + I, self-tuning fuzzy logic PID (STF-PID) controller and fuzzy logic-based sliding mode adaptive controller (FLSMAC) are designed for stable autopilot system and are compared with conventional PI controller. The target of throttle, speed and ...

  15. OUTPUT CONTROL WITH ADAPTIVE-PROPORTIONAL DIFFERENTIAL CONTROLLER

    Directory of Open Access Journals (Sweden)

    O. F. Opeiko

    2016-01-01

    Full Text Available The goal of this articl is to improve acсuracy and stability margine for system with proportional differential (PD-controllers and parameters unsertaity by means of adaptation. The adaptive controller must produce the accuraсy improving by encreasing the proportional gain of controller, when the error is non zero. Consequently, the error decrease, adaptation become less intensive, and the system maintain the stability. The is provided by the correctly constructed Lapunov function. The method of parametric synthesis for adaptive PD-controller is developed based on roots location on complex plane. The numerical example of synthesis is presented with simulation results, which demonstrate the correctness of developed method. The adaptive PD-controller allow accuracy improuving with stability retaining, i. e. the adaptivity is able to replace the integrator by proportional gain tuning. The adaptive PD-controller is especially helpful for systems, working with inputs variability, and when the exponential dynamic is of importance. In cases, when diturbances are restricted, the adaptive PD-controller provides the stability and accuracy, but slowly operation.

  16. 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.

  17. 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.

  18. Adaptive neural control of aeroelastic response

    Science.gov (United States)

    Lichtenwalner, Peter F.; Little, Gerald R.; Scott, Robert C.

    1996-05-01

    The Adaptive Neural Control of Aeroelastic Response (ANCAR) program is a joint research and development effort conducted by McDonnell Douglas Aerospace (MDA) and the National Aeronautics and Space Administration, Langley Research Center (NASA LaRC) under a Memorandum of Agreement (MOA). The purpose of the MOA is to cooperatively develop the smart structure technologies necessary for alleviating undesirable vibration and aeroelastic response associated with highly flexible structures. Adaptive control can reduce aeroelastic response associated with buffet and atmospheric turbulence, it can increase flutter margins, and it may be able to reduce response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Phase I of the ANCAR program involved development and demonstration of a neural network-based semi-adaptive flutter suppression system which used a neural network for scheduling control laws as a function of Mach number and dynamic pressure. This controller was tested along with a robust fixed-gain control law in NASA's Transonic Dynamics Tunnel (TDT) utilizing the Benchmark Active Controls Testing (BACT) wing. During Phase II, a fully adaptive on-line learning neural network control system has been developed for flutter suppression which will be tested in 1996. This paper presents the results of Phase I testing as well as the development progress of Phase II.

  19. Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.

    Science.gov (United States)

    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.

  20. Fuzzy adaptive PID control for six rotor eppo UAV

    Directory of Open Access Journals (Sweden)

    Yongwei LI

    2017-02-01

    Full Text Available Six rotor eppo drones's load change itself in the job process will reduce the aircraft flight control performance and make the resistance to environmental disturbance being poor. In order to improve the six rotor eppo unmanned aerial vehicle (UAV control performance, the UAV in the process of spraying pesticide is analyzed and the model is constructed, then the eppo UAV time-varying dynamics mathematical model is deduced, and a fuzzy adaptive PID control algorithm is proposed. Fuzzy adaptive PID algorithm has good adaptability and the parameter setting is simple, which improves the system dynamic response and steady state performance, realizing the stability of the six rotor eppo UAV flight. With measured parameters of each sensor input in to the fuzzy adaptive PID algorithm, the corresponding control quality is obtained, and the stable operation of aircraft is realized. Through using Matlab to simulate the flight system and combining the practical experiments, it shows that the dynamic performance and stability of the system is improved effetively.

  1. Neuro adaptive control for aerospace and distributed systems

    Science.gov (United States)

    Das, Abhijit

    dependent on the second largest eigenvalue of the laplacian matrix of the network graph. This research shows how to implement distributed nonlinear and adaptive controllers using pinning techniques for generalized directed communication graph models. The dynamics of the agent at each node are non-identical and unknown. A Lyapunov based technique is adopted to show the tracking performance when the tracker dynamics are also considered unknown. It is also shown using pinning adaptive control that the synchronization speed no longer depends on Fiedler eigenvalue of the graph laplacian matrix. The research also develops duality properties of linear controllers and observers for general cooperative di-graph systems. The choice of gains for controller and observer using riccati equations ensures stable synchronization on general di-graphs. Finally the research is extended to decentralized control of HVAC systems using pinning control methodology.

  2. Nonlinear adaptive neural controller for unstable aircraft

    OpenAIRE

    Suresh, S; Omkar, SN; Mani, V; Sundararajan, N

    2005-01-01

    A model reference indirect adaptive neural control scheme that uses both off-line and online learning strategies is proposed for an,unstable nonlinear aircraft controller design. The bounded-input-bounded-output stability requirement for the controller design is circumvented using an off-line, finite interval of time training scheme. The aircraft model is first identified using a neural network with linear filter (also known as time-delayed neural network) with the available input-output data...

  3. Flight control with adaptive critic neural network

    Science.gov (United States)

    Han, Dongchen

    2001-10-01

    In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.

  4. Adaptive control of solar energy collector systems

    CERN Document Server

    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

  5. Adaptive control of nonlinear underwater robotic systems

    Directory of Open Access Journals (Sweden)

    Thor I. Fossen

    1991-04-01

    Full Text Available The problem of controlling underwater mobile robots in 6 degrees of freedom (DOF is addressed. Uncertainties in the input matrix due to partly known nonlinear thruster characteristics are modeled as multiplicative input uncertainty. This paper proposes two methods to compensate for the model uncertainties: (1 an adaptive passivity-based control scheme and (2 deriving a hybrid (adaptive and sliding controller. The hybrid controller consists of a switching term which compensates for uncertainties in the input matrix and an on-line parameter estimation algorithm. Global stability is ensured by applying Barbalat's Lyapunovlike lemma. The hybrid controller is simulated for the horizontal motion of the Norwegian Experimental Remotely Operated Vehicle (NEROV.

  6. Adaptive Critic Nonlinear Robust Control: A Survey.

    Science.gov (United States)

    Wang, Ding; He, Haibo; Liu, Derong

    2017-10-01

    Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

  7. Evolving Systems and Adaptive Key Component Control

    Science.gov (United States)

    Frost, Susan A.; Balas, Mark J.

    2009-01-01

    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. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.

  8. 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

  9. Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control

    Science.gov (United States)

    Nguyen, Nhan T.; Boskovic, Jovan D.

    2008-01-01

    This paper presents a bounded linear stability analysis for a hybrid adaptive control that blends both direct and indirect adaptive control. Stability and convergence of nonlinear adaptive control are analyzed using an approximate linear equivalent system. A stability margin analysis shows that a large adaptive gain can lead to a reduced phase margin. This method can enable metrics-driven adaptive control whereby the adaptive gain is adjusted to meet stability margin requirements.

  10. Two scale high gain adaptive control

    NARCIS (Netherlands)

    Polderman, Jan W.; Mareels, I.M.Y.; Mareels, Iven

    2004-01-01

    Simple adaptive controllers based on high gain output feedback suffer a lack of robustness with respect to bounded disturbances. Existing modifications achieve boundedness of all solutions but introduce solutions that, even in the absence of disturbances, do not achieve regulation. In this paper a

  11. Simple adaptive control system design trades

    NARCIS (Netherlands)

    Mooij, E.

    2017-01-01

    In the design of a Model Reference Adaptive Control system, a reference model serves as the (well-known) basis through which system and user requirements can find their way into the design. By tuning the design parameters, the response of the actual vehicle should track the response of the

  12. Geometry control in adaptive truss structures

    Science.gov (United States)

    Ramesh, A. V.; Utku, S.

    1990-01-01

    Forward and inverse kinematics equations are derived for the large geometry maneuver of adaptive trusses. A new algorithm based on higher-order multistep methods is proposed as a means of computing the length control for a described large geometry maneuver. The algorithm is shown to improve in computational speed at least five times over the algorithm presented in an earlier paper. The acceleration in control computation and other features such as varying velocity profiles and curved trajectories are illustrated by simulation results.

  13. 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.

  14. Improved automatic tuning of PID controller for stable processes.

    Science.gov (United States)

    Kumar Padhy, Prabin; Majhi, Somanath

    2009-10-01

    This paper presents an improved automatic tuning method for stable processes using a modified relay in the presence of static load disturbances and measurement noise. The modified relay consists of a standard relay in series with a PI controller of unity proportional gain. The integral time constant of the PI controller of the modified relay is chosen so as to ensure a minimum loop phase margin of 30( composite function). A limit cycle is then obtained using the modified relay. Hereafter, the PID controller is designed using the limit cycle output data. The derivative time constant is obtained by maintaining the above mentioned loop phase margin. Minimizing the distance of Nyquist curve of the loop transfer function from the imaginary axis of the complex plane gives the proportional gain. The integral time constant of the PID controller is set equal to the integral time constant of the PI controller of the modified relay. The effectiveness of the proposed technique is verified by simulation results.

  15. Robust adaptive backstepping control for reentry reusable launch vehicles

    Science.gov (United States)

    Wang, Zhen; Wu, Zhong; Du, Yijiang

    2016-09-01

    During the reentry process of reusable launch vehicles (RLVs), the large range of flight envelope will not only result in high nonlinearities, strong coupling and fast time-varying characteristics of the attitude dynamics, but also result in great uncertainties in the atmospheric density, aerodynamic coefficients and environmental disturbances, etc. In order to attenuate the effects of these problems on the control performance of the reentry process, a robust adaptive backstepping control (RABC) strategy is proposed for RLV in this paper. This strategy consists of two-loop controllers designed via backstepping method. Both the outer and the inner loop adopt a robust adaptive controller, which can deal with the disturbances and uncertainties by the variable-structure term with the estimation of their bounds. The outer loop can track the desired attitude by the design of virtual control-the desired angular velocity, while the inner one can track the desired angular velocity by the design of control torque. Theoretical analysis indicates that the closed-loop system under the proposed control strategy is globally asymptotically stable. Even if the boundaries of the disturbances and uncertainties are unknown, the attitude can track the desired value accurately. Simulation results of a certain RLV demonstrate the effectiveness of the control strategy.

  16. Robust and Adaptive Control With Aerospace Applications

    CERN Document Server

    Lavretsky, Eugene

    2013-01-01

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

  17. Neuro- PI controller based model reference adaptive control for ...

    African Journals Online (AJOL)

    The control input to the plant is given by the sum of the output of conventional MRAC and the output of NN. The proposed Neural Network -based Model Reference Adaptive Controller (NN-MRAC) can significantly improve the system behavior and force the system to follow the reference model and minimize the error ...

  18. 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.

  19. 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.

  20. ADAPTIVE SUBOPTIMAL CONTROL OF INPUT CONSTRAINED PLANTS

    Directory of Open Access Journals (Sweden)

    Valerii Azarskov

    2011-03-01

    Full Text Available Abstract. This paper deals with adaptive regulation of a discrete-time linear time-invariant plant witharbitrary bounded disturbances whose control input is constrained to lie within certain limits. The adaptivecontrol algorithm exploits the one-step-ahead control strategy and the gradient projection type estimationprocedure using the modified dead zone. The convergence property of the estimation algorithm is shown tobe ensured. The sufficient conditions guaranteeing the global asymptotical stability and simultaneously thesuboptimality of the closed-loop systems are derived. Numerical examples and simulations are presented tosupport the theoretical results.

  1. Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganization.

    Science.gov (United States)

    Pohlmeyer, Eric A; Mahmoudi, Babak; Geng, Shijia; Prins, Noeline W; Sanchez, Justin C

    2014-01-01

    Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder's neural input space (e.g. neurons appearing or being lost amongst electrode recordings). These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI) to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled.

  2. Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganization.

    Directory of Open Access Journals (Sweden)

    Eric A Pohlmeyer

    Full Text Available Brain-machine interface (BMI systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder's neural input space (e.g. neurons appearing or being lost amongst electrode recordings. These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled.

  3. Adaptive observer-based control for a class of chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Hua Changchun E-mail: cch@ysu.edu.cn; Guan Xinping; Li Xiaoli; Shi Peng

    2004-10-01

    In this note, the problem of control for a class of chaotic systems is studied. Only partial information of the systems states is known. First, an adaptive observer is designed to ensure the corresponding error system asymptotically stable. Then, based on the states obtained by the above observer, a nonlinear state feedback controller is constructed for the chaotic system, which, according to the input to state stable (ISS) principal, guarantees the closed-loop chaotic system is asymptotically stable. A numerical example is included to show the effectiveness of the proposed techniques.

  4. 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.

  5. Monitoring the Performance of a neuro-adaptive Controller

    Science.gov (United States)

    Schumann, Johann; Gupta, Pramod

    2004-11-01

    We present a tool to estimate the performance of the neural network in a neural network based adaptive controller. Using a Bayesian approach, this tool supports verification and validation of the adaptive controller as well as on-line monitoring. In this paper, we discuss our approach and present simulation results using the adaptive controller developed for NASA's IFCS (Intelligent Flight Control System) project.

  6. Robust adaptive control for Unmanned Aerial Vehicles

    Science.gov (United States)

    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

  7. Improved methods in neural network-based adaptive output feedback control, with applications to flight control

    Science.gov (United States)

    Kim, Nakwan

    Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

  8. Direct adaptive control for nonlinear uncertain dynamical systems

    Science.gov (United States)

    Hayakawa, Tomohisa

    In light of the complex and highly uncertain nature of dynamical systems requiring controls, it is not surprising that reliable system models for many high performance engineering and life science applications are unavailable. In the face of such high levels of system uncertainty, robust controllers may unnecessarily sacrifice system performance whereas adaptive controllers are clearly appropriate since they can tolerate far greater system uncertainty levels to improve system performance. In this dissertation, we develop a Lyapunov-based direct adaptive and neural adaptive control framework that addresses parametric uncertainty, unstructured uncertainty, disturbance rejection, amplitude and rate saturation constraints, and digital implementation issues. Specifically, we consider the following research topics; direct adaptive control for nonlinear uncertain systems with exogenous disturbances; robust adaptive control for nonlinear uncertain systems; adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints; adaptive reduced-order dynamic compensation for nonlinear uncertain systems; direct adaptive control for nonlinear matrix second-order dynamical systems with state-dependent uncertainty; adaptive control for nonnegative and compartmental dynamical systems with applications to general anesthesia; direct adaptive control of nonnegative and compartmental dynamical systems with time delay; adaptive control for nonlinear nonnegative and compartmental dynamical systems with applications to clinical pharmacology; neural network adaptive control for nonlinear nonnegative dynamical systems; passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems; neural network adaptive dynamic output feedback control for nonlinear nonnegative systems using tapped delay memory units; Lyapunov-based adaptive control framework for discrete-time nonlinear systems with exogenous disturbances

  9. 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.

  10. A Methodology for Investigating Adaptive Postural Control

    Science.gov (United States)

    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

  11. Adaptive control of a Stewart platform-based manipulator

    Science.gov (United States)

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

    1993-01-01

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

  12. 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.

  13. 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...

  14. A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

    Science.gov (United States)

    Wen, John T.; Kreutz, Kenneth; Bayard, David S.

    1988-01-01

    A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

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

    Science.gov (United States)

    Frost, Susan A.; Balas, Mark J.

    2011-01-01

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

  16. Adaptive quality control for multimedia communications

    Directory of Open Access Journals (Sweden)

    Santichai Chuaywong

    2008-01-01

    Full Text Available Multimedia communications are communications with several types of media, such as audio, video and data. The current Internet has some levels of capability to support multimedia communications, unfortunately, the QoS (Quality of Service is still challenging. A large number of QoS mechanisms has been proposed; however, the main concern is for low levels, e.g. layer 2 (Data Link or 3 (Transport. In this paper, mechanisms for control the quality of audio and video are proposed. G.723.1 and MPEG-4 are used as the audio and video codec respectively. The proposed algorithm for adaptive quality control of audio communication is based on forward error correction (FEC. In the case of video communication, the proposed algorithm adapts the value of key frame interval, which is an encoding parameter of MPEG-4. We evaluated our proposed algorithms by computer simulation. We have shown that, in most cases, the proposed scheme gained a higher throughput compared to other schemes.

  17. Adaptive collaborative control of highly redundant robots

    Science.gov (United States)

    Handelman, David A.

    2008-04-01

    The agility and adaptability of biological systems are worthwhile goals for next-generation unmanned ground vehicles. Management of the requisite number of degrees of freedom, however, remains a challenge, as does the ability of an operator to transfer behavioral intent from human to robot. This paper reviews American Android research funded by NASA, DARPA, and the U.S. Army that attempts to address these issues. Limb coordination technology, an iterative form of inverse kinematics, provides a fundamental ability to control balance and posture independently in highly redundant systems. Goal positions and orientations of distal points of the robot skeleton, such as the hands and feet of a humanoid robot, become variable constraints, as does center-of-gravity position. Behaviors utilize these goals to synthesize full-body motion. Biped walking, crawling and grasping are illustrated, and behavior parameterization, layering and portability are discussed. Robotic skill acquisition enables a show-and-tell approach to behavior modification. Declarative rules built verbally by an operator in the field define nominal task plans, and neural networks trained with verbal, manual and visual signals provide additional behavior shaping. Anticipated benefits of the resultant adaptive collaborative controller for unmanned ground vehicles include increased robot autonomy, reduced operator workload and reduced operator training and skill requirements.

  18. 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.

  19. Adaptive Passivity Based Individual Pitch Control for Wind Turbines in the Full Load Region

    DEFF Research Database (Denmark)

    Sørensen, Kim L.; Galeazzi, Roberto; Odgaard, Peter F.

    2014-01-01

    the inclusion of gradient based adaptation laws allows for the on-line compensation of variations in the aerodynamic torque. The closed-loop equilibrium point of the regulation error dynamics is shown to be UGAS (uniformly globally asymptotically stable). Numerical simulations show that the proposed control...

  20. 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.

  1. An adaptive unscented Kalman filter-based adaptive tracking control for wheeled mobile robots with control constrains in the presence of wheel slipping

    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.

  2. Real-time Adaptive Control Using Neural Generalized Predictive Control

    Science.gov (United States)

    Haley, Pam; Soloway, Don; Gold, Brian

    1999-01-01

    The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

  3. 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...

  4. 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.

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

    Science.gov (United States)

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

    2018-02-01

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

  6. 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)

  7. Adaptive powertrain control for plugin hybrid electric vehicles

    Science.gov (United States)

    Kedar-Dongarkar, Gurunath; Weslati, Feisel

    2013-10-15

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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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....

  13. Adaptive output feedback control of aircraft flexible modes

    OpenAIRE

    Ponnusamy, Sangeeth Saagar; Bordeneuve-Guibé, Joël

    2012-01-01

    The application of adaptive output feedback augmentative control to the flexible aircraft problem is presented. Experimental validation of control scheme was carried out using a three disk torsional pendulum. In the reference model adaptive control scheme, the rigid aircraft reference model and neural network adaptation is used to control structural flexible modes and compensate for the effects unmodeled dynamics and parametric variations of a classical high order large passenger aircraft. Th...

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

    Science.gov (United States)

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

    2017-09-01

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

  15. Adaptive proportional–integral–derivative tuning sliding mode control for a shape memory alloy actuator

    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

  16. Adaptive Controller Design for Continuous Stirred Tank Reactor

    OpenAIRE

    K. Prabhu; V. Murali Bhaskaran

    2014-01-01

    Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of C...

  17. Adaptive Filtering, Identification, and Control with Applications to Adaptive Optics

    National Research Council Canada - National Science Library

    Gibson, Steve

    2003-01-01

    .... Additional application areas included optical communication systems, blind identification and deconvolution, active control of noise and vibration, and detection of damage in elastic structures...

  18. Adaptive Fuzzy and Robust H∞ Compensation Control for Uncertain Robot

    Directory of Open Access Journals (Sweden)

    Yuan Chen

    2013-06-01

    Full Text Available In this paper, two types of robust adaptive compensation control schemes for the trajectory tracking control of robot manipulator with uncertain dynamics are proposed. The proposed controllers incorporate the computed-torque control scheme as a nominal portion of the controller; an adaptive fuzzy control algorithm to approximate the structured uncertainties; and a nonlinear H∞ tracking control model as a feedback portion to eliminate the effects of the unstructured uncertainties and approximation errors. The validity of the robust adaptive compensation control schemes is investigated by numerical simulations of a two-link rotary robot manipulator

  19. Model reference adaptive control and adaptive stability augmentation

    DEFF Research Database (Denmark)

    Henningsen, Arne; Ravn, Ole

    1993-01-01

    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...

  20. Modular and Adaptive Control of Sound Processing

    Science.gov (United States)

    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.

  1. Simple robust control laws for robot manipulators. Part 2: Adaptive case

    Science.gov (United States)

    Bayard, D. S.; Wen, J. T.

    1987-01-01

    A new class of asymptotically stable adaptive control laws is introduced for application to the robotic manipulator. Unlike most applications of adaptive control theory to robotic manipulators, this analysis addresses the nonlinear dynamics directly without approximation, linearization, or ad hoc assumptions, and utilizes a parameterization based on physical (time-invariant) quantities. This approach is made possible by using energy-like Lyapunov functions which retain the nonlinear character and structure of the dynamics, rather than simple quadratic forms which are ubiquitous to the adaptive control literature, and which have bound the theory tightly to linear systems with unknown parameters. It is a unique feature of these results that the adaptive forms arise by straightforward certainty equivalence adaptation of their nonadaptive counterparts found in the companion to this paper (i.e., by replacing unknown quantities by their estimates) and that this simple approach leads to asymptotically stable closed-loop adaptive systems. Furthermore, it is emphasized that this approach does not require convergence of the parameter estimates (i.e., via persistent excitation), invertibility of the mass matrix estimate, or measurement of the joint accelerations.

  2. Neural network based adaptive control for nonlinear dynamic regimes

    Science.gov (United States)

    Shin, Yoonghyun

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

  3. Active structural control with stable fuzzy PID techniques

    CERN Document Server

    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...

  4. Neural Control of Chronic Stress Adaptation

    Directory of Open Access Journals (Sweden)

    James eHerman

    2013-08-01

    Full Text Available Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced stress reactivity and eventually become maladaptive. The long-term impact of stress is kept in check by the process of habituation, which reduces HPA axis responses upon repeated exposure to homotypic stressors and likely limits deleterious actions of prolonged glucocorticoid secretion. Habituation is regulated by limbic stress-regulatory sites, and is at least in part glucocorticoid feedback-dependent. Chronic stress also sensitizes reactivity to new stimuli. While sensitization may be important in maintaining response flexibility in response to new threats, it may also add to the cumulative impact of glucocorticoids on the brain and body. Finally, unpredictable or severe stress exposure may cause long-term and lasting dysregulation of the HPA axis, likely due to altered limbic control of stress effector pathways. Stress-related disorders, such as depression and PTSD, are accompanied by glucocorticoid imbalances and structural/ functional alterations in limbic circuits that resemble those seen following chronic stress, suggesting that inappropriate processing of stressful information may be part of the pathological process.

  5. Least-Squares Adaptive Control Using Chebyshev Orthogonal Polynomials

    Science.gov (United States)

    Nguyen, Nhan T.; Burken, John; Ishihara, Abraham

    2011-01-01

    This paper presents a new adaptive control approach using Chebyshev orthogonal polynomials as basis functions in a least-squares functional approximation. The use of orthogonal basis functions improves the function approximation significantly and enables better convergence of parameter estimates. Flight control simulations demonstrate the effectiveness of the proposed adaptive control approach.

  6. 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 ...

  7. 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.

  8. Adaptive Linear Parameter Varying Control for Aeroservoelastic Suppression, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill aircraft safety objectives though automated vehicle recovery while maintaining performance and stability...

  9. Reconciling Stable Asymmetry with Recovery of Function: An Adaptive Systems Perspective on Functional Plasticity.

    Science.gov (United States)

    Bullock, Daniel; And Others

    1987-01-01

    This commentary, written in response to Witelson's work (1987), examines alternative ways of determining how the developmentally stable functional asymmetry (hemispheric specialization) observed in neurologically intact children can be reconciled with the dramatic recovery of function often displayed following unilateral brain damage. (PCB)

  10. Design of a stable fuzzy controller for an articulated vehicle.

    Science.gov (United States)

    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.

  11. Adaptive Intelligent Ventilation Noise Control, Phase II

    Data.gov (United States)

    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...

  12. Adaptive Intelligent Ventilation Noise Control, Phase I

    Data.gov (United States)

    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...

  13. Applications of adaptive filters in active noise control

    Science.gov (United States)

    Darlington, Paul

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

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

    Science.gov (United States)

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

    2012-05-01

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

  15. Monitoring the Performance of a Neuro-Adaptive Controller

    Science.gov (United States)

    Schumann, Johann; Gupta, Pramod

    2004-01-01

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

  16. 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

  17. Stable and Intuitive Control of an Intelligent Assist Device.

    Science.gov (United States)

    Duchaine, V; Mayer St-Onge, Boris; Dalong Gao; Gosselin, C

    2012-01-01

    Safety and dependability are of the utmost importance for physical human-robot interaction due to the potential risks that a relatively powerful robot poses to human beings. From the control standpoint, it is possible to improve safety by guaranteeing that the robot will never exhibit any unstable behavior. However, stability is not the only concern in the design of a controller for such a robot. During human-robot interaction, the resulting cooperative motion should be truly intuitive and should not restrict in any way the human performance. For this purpose, we have designed a new variable admittance control law that guarantees the stability of the robot during constrained motion and also provides a very intuitive human interaction. The former characteristic is provided by the design of a stability observer while the latter is based on a variable admittance control scheme that uses the time derivative of the contact force to assess human intentions. The stability observer is based on a previously published stability investigation of cooperative motion which implies the knowledge of the interaction stiffness. A method to accurately estimate this stiffness online using the data coming from the encoder and from a multiaxis force sensor at the end effector is also provided. The stability and intuitivity of the control law are verified in a user study involving a cooperative drawing task with a 3 degree-of-freedom (dof) parallel robot as well as in experiments performed with a prototype of an industrial Intelligent Assist Device.

  18. 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.

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

    DEFF Research Database (Denmark)

    Ravn, Ole

    1998-01-01

    The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller implement...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown.......The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...

  20. Robust chaos synchronization using input-to-state stable control

    Indian Academy of Sciences (India)

    function vector satisfying the global Lipschitz condition with Lipschitz constant. Lg > 0. The system (5) is considered as a drive system. The synchronization problem of system (5) is considered by using the drive- response configuration. According to the drive-response concept, the controlled response system is given by.

  1. Systems and Methods for Derivative-Free Adaptive Control

    Science.gov (United States)

    Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)

    2015-01-01

    An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

  2. Adaptive control with variable dead-zone nonlinearities

    Science.gov (United States)

    Orlicki, D.; Valavani, L.; Athans, M.; Stein, G.

    1984-01-01

    It has been found that fixed error dead-zones as defined in the existing literature result in serious degradation of performance, due to the conservativeness which characterizes the determination of their width. In the present paper, variable width dead-zones are derived for the adaptive control of plants with unmodeled dynamics. The derivation makes use of information available about the unmodeled dynamics both a priori as well as during the adaptation process, so as to stabilize the adaptive loop and at the same time overcome the conservativeness and performance limitations of fixed-dead zone adaptive or fixed gain controllers.

  3. Adaptive feedback control by constrained approximate dynamic programming.

    Science.gov (United States)

    Ferrari, Silvia; Steck, James E; Chandramohan, Rajeev

    2008-08-01

    A constrained approximate dynamic programming (ADP) approach is presented for designing adaptive neural network (NN) controllers with closed-loop stability and performance guarantees. Prior knowledge of the linearized equations of motion is used to guarantee that the closed-loop system meets performance and stability objectives when the plant operates in a linear parameter-varying (LPV) regime. In the presence of unmodeled dynamics or failures, the NN controller adapts to optimize its performance online, whereas constrained ADP guarantees that the LPV baseline performance is preserved at all times. The effectiveness of an adaptive NN flight controller is demonstrated for simulated control failures, parameter variations, and near-stall dynamics.

  4. Adaptive fuzzy PID control for a quadrotor stabilisation

    Science.gov (United States)

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

    2018-02-01

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

  5. 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...

  6. Hormesis and adaptive cellular control systems

    Science.gov (United States)

    Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...

  7. Adaptive Dynamic Surface Control is designed for Twin Rotor unmanned helicopter in three-dimensional space

    Directory of Open Access Journals (Sweden)

    Amir Reza Moadeli

    2016-01-01

    Full Text Available In this paper, the system control design problem twin rotors helicopters Unmanned Aerial Vehicles (UAV in three dimensional space Without uncertainty based on the dynamic adaptive control is studied. the adaptive Dynamic surface control approach complexity explosion problem in non-linear control step back or backstepping method [45] using the First-order filters removed. The first helicopter dynamic equations and functions are examined. Then, the Dynamic surface control techniques by compare non-linear control technique back stepping [45] is checked and the system is simulation by both techniques adaptive Dynamic surface control and nonlinear control back stepping method. The proposed adaptive dynamics surface nonlinear control method approach is able to guarantees that all the signals in the closed-loop system are asymptotically stable for all initial conditions and you can also choose appropriate design parameters of the system output converges to a small neighborhood of origin ensured . Finally, simulation results are presented, showing the effectiveness of control methods are given.

  8. The role of conscious control in maintaining stable posture.

    Science.gov (United States)

    Uiga, Liis; Capio, Catherine M; Ryu, Donghyun; Wilson, Mark R; Masters, Rich S W

    2018-02-01

    This study aimed to examine the relationship between conscious control of movements, as defined by the Theory of Reinvestment (Masters & Maxwell, 2008; Masters, Polman, & Hammond, 1993), and both traditional and complexity-based COP measures. Fifty-three young adults (mean age=20.93±2.53years), 39 older adults with a history of falling (mean age=69.23±3.84years) and 39 older adults without a history of falling (mean age=69.00±3.72years) were asked to perform quiet standing balance in single- and dual-task conditions. The results showed that higher scores on the Movement Specific Reinvestment Scale (MSRS; Masters, Eves, & Maxwell, 2005; Masters & Maxwell, 2008), a psychometric measure of the propensity for conscious involvement in movement, were associated with larger sway amplitude and a more constrained (less complex) mode of balancing in the medial-lateral direction for young adults only. Scores on MSRS explained approximately 10% of total variation in the medial-lateral sway measures. This association was not apparent under dual-task conditions, during which a secondary task was used to limit the amount of cognitive resources available for conscious processing. No relationship between postural control and score on the MSRS was found for either older adult fallers or non-fallers. Possible explanations for these results are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Adaptive Feature Based Control of Compact Disk Players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Vidal, Enrique Sanchez

    2005-01-01

    -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...... result that the adaptive scheme clearly adapts better to the given faults compared with the non-adaptive version of the feature based control scheme.......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...

  10. Stable Flocking of Multiple Agents Based on Molecular Potential Field and Distributed Receding Horizon Control

    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)

  11. Comparing Computerized Adaptive and Self-Adapted Tests: The Influence of Examinee Achievement Locus of Control.

    Science.gov (United States)

    Wise, Steven L.; And Others

    This study investigated the relationship between examinee achievement-specific locus of control and the differences between self-adapted testing (SAT) and computerized adaptive testing (CAT) in terms of mean estimated proficiency and posttest state anxiety. Subjects were 379 college students. A disordinal interaction was found between test type…

  12. Robust Adaptive Sliding Mode Control for Generalized Function Projective Synchronization of Different Chaotic Systems with Unknown Parameters

    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.

  13. 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.

  14. Revisionist integral deferred correction with adaptive step-size control

    KAUST Repository

    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.

  15. Adaptive Missile Flight Control for Complex Aerodynamic Phenomena

    Science.gov (United States)

    2017-08-09

    ARL-TR-8085 ● AUG 2017 US Army Research Laboratory Adaptive Missile Flight Control for Complex Aerodynamic Phenomena by Frank...Adaptive Missile Flight Control for Complex Aerodynamic Phenomena by Frank Fresconi and Jubaraj Sahu Weapons and Materials Research Directorate...currently valid OMB control number . PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) August 2017 2. REPORT TYPE

  16. 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

  17. Control Augmentation Using Adaptive Fuzzy Neural Networks

    Science.gov (United States)

    Kato, Akio; Wada, Yoshihisa

    Control to improve control characteristics of aircraft, CA (Control Augmentation), is used to realize the desirable motion of aircraft corresponding to pilot's control action. When the control laws using fuzzy inference were designed, trial and error was repeated for optimization of the parameter. Here, in designing control laws using fuzzy neural networks, the systematic optimization of the parameter was possible using the learning algorithm usually used in neural networks, by expressing the fuzzy inference in the form of neural networks. Here, the control laws, which learned the characteristics of the aircraft for one flight condition only, were used in all flight conditions without changing any parameter. Evaluation of the designed control laws showed good performance in all flight conditions. This proves that fuzzy neural networks are an effective and flexible method when applied to control laws for control augmentation of aircraft.

  18. 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.

  19. An integration time adaptive control method for atmospheric composition detection of occultation

    Science.gov (United States)

    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.

  20. Children after Chernobyl: immune cells adaptive changes and stable alterations under low-dose irradiation

    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)

  1. Dynamics and Adaptive Control for Stability Recovery of Damaged Aircraft

    Science.gov (United States)

    Nguyen, Nhan; Krishnakumar, Kalmanje; Kaneshige, John; Nespeca, Pascal

    2006-01-01

    This paper presents a recent study of a damaged generic transport model as part of a NASA research project to investigate adaptive control methods for stability recovery of damaged aircraft operating in off-nominal flight conditions under damage and or failures. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of a generic transport aircraft. Certain types of damage such as damage to one of the wings or horizontal stabilizers can cause the aircraft to become asymmetric, thus resulting in a coupling between the longitudinal and lateral motions. Flight dynamics for a general asymmetric aircraft is derived to account for changes in the center of gravity that can compromise the stability of the damaged aircraft. An iterative trim analysis for the translational motion is developed to refine the trim procedure by accounting for the effects of the control surface deflection. A hybrid direct-indirect neural network, adaptive flight control is proposed as an adaptive law for stabilizing the rotational motion of the damaged aircraft. The indirect adaptation is designed to estimate the plant dynamics of the damaged aircraft in conjunction with the direct adaptation that computes the control augmentation. Two approaches are presented 1) an adaptive law derived from the Lyapunov stability theory to ensure that the signals are bounded, and 2) a recursive least-square method for parameter identification. A hardware-in-the-loop simulation is conducted and demonstrates the effectiveness of the direct neural network adaptive flight control in the stability recovery of the damaged aircraft. A preliminary simulation of the hybrid adaptive flight control has been performed and initial data have shown the effectiveness of the proposed hybrid approach. Future work will include further investigations and high-fidelity simulations of the proposed hybrid adaptive Bight control approach.

  2. Adaptive Automation Based on Air Traffic Controller Decision-Making

    NARCIS (Netherlands)

    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

  3. Model-free adaptive sliding mode controller design for generalized ...

    Indian Academy of Sciences (India)

    L M WANG

    2017-08-16

    Aug 16, 2017 ... A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) ... the neural network theory, a model-free adaptive sliding mode controller is designed to guarantee asymptotic stability of the generalized ..... following optimization parameters are needed: ⎧.

  4. Immersion and Invariance Based Nonlinear Adaptive Flight Control

    NARCIS (Netherlands)

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

    2010-01-01

    In this paper a theoretical framework for nonlinear adaptive flight control is developed and applied to a simplified, over-actuated nonlinear fighter aircraft model. The framework is based on a modular adaptive backstepping scheme with a new type of nonlinear estimator. The nonlinear estimator is

  5. Adaptation.

    Science.gov (United States)

    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

  6. 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.

  7. Adaptive Sliding Mode Control for Hydraulic Drives

    DEFF Research Database (Denmark)

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

    2013-01-01

    . The main target is to overcome problems with linear controllers deteriorating performance due to the inherent nonlinear nature of such systems, without requiring extensive knowledge on system parameters nor advanced control theory. In order to accomplish this task, an integral sliding mode controller...

  8. The motion control of a statically stable biped robot on an uneven floor.

    Science.gov (United States)

    Shih, C L; Chiou, C J

    1998-01-01

    This work studies the motion control of a statically stable biped robot having seven degrees of freedom. Statically stable walking of the biped robot is realized by maintaining the center-of-gravity inside the convex region of the supporting foot and/or feet during both single-support and double-support phases. The main points of this work are framing the stability in an easy and correct way, the design of a bipedal statically stable walker, and walking on sloping surfaces and stairs.

  9. Adaptive control in series load PWM induction heating inverters

    Science.gov (United States)

    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.

  10. 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.

  11. 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....... The experimental results of measured loop-gain at different operating points are presented to validate the theoretical performance of the controller....

  12. 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...

  13. Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

    Science.gov (United States)

    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.

  14. Integrated Damage-Adaptive Control System (IDACS), Phase I

    Data.gov (United States)

    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...

  15. Vehicle-to-infrastructure program cooperative adaptive cruise control.

    Science.gov (United States)

    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...

  16. 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.

  17. Control and adaptation in telecommunication systems mathematical foundations

    CERN Document Server

    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.

  18. Optimizing adaptive learning through testing, diagnostic reflection and learner control

    NARCIS (Netherlands)

    Dirkx, Kim; Kester, Liesbeth; Kirschner, Paul A.

    2011-01-01

    Dirkx, K. J. H., Kester, L., & Kirschner, P. A. (2011, September). Optimizing adaptive learning through testing, diagnostic reflection and learner control. Presentation for visitors of KU Leuven, Open University, Heerlen, The Netherlands.

  19. Integrated Damage-Adaptive Control System (IDACS), Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — SSCI proposes to further develop, implement and test the damage-adaptive control algorithms developed in Phase I within the framework of an Integrated Damage...

  20. Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation

    Data.gov (United States)

    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...

  1. High Efficiency Lighting with Integrated Adaptive Control (HELIAC), Phase II

    Data.gov (United States)

    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...

  2. High Efficiency Lighting with Integrated Adaptive Control (HELIAC), Phase I

    Data.gov (United States)

    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...

  3. 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...

  4. 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...

  5. Adaptive Generalized Predictive Control for Mechatronic Systems

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Böhm, Josef

    2006-01-01

    Roč. 5, č. 8 (2006), s. 1830-1837 ISSN 1109-2777 R&D Projects: GA ČR GP102/06/P275; GA ČR GA102/05/0271 Institutional research plan: CEZ:AV0Z10750506 Keywords : on-line identification * predictive control * input/output equations of predictions * real-time control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0040149.pdf

  6. Adaptive and Resilient Flight Control System for a Small Unmanned Aerial System

    Directory of Open Access Journals (Sweden)

    Gonzalo Garcia

    2013-01-01

    Full Text Available The main purpose of this paper is to develop an onboard adaptive and robust flight control system that improves control, stability, and survivability of a small unmanned aerial system in off-nominal or out-of-envelope conditions. The aerodynamics of aircraft associated with hazardous and adverse onboard conditions is inherently nonlinear and unsteady. The presented flight control system improves functionalities required to adapt the flight control in the presence of aircraft model uncertainties. The fault tolerant inner loop is enhanced by an adaptive real-time artificial neural network parameter identification to monitor important changes in the aircraft’s dynamics due to nonlinear and unsteady aerodynamics. The real-time artificial neural network parameter identification is done using the sliding mode learning concept and a modified version of the self-adaptive Levenberg algorithm. Numerically estimated stability and control derivatives are obtained by delta-based methods. New nonlinear guidance logic, stable in Lyapunov sense, is developed to guide the aircraft. The designed flight control system has better performance compared to a commercial off-the-shelf autopilot system in guiding and controlling an unmanned air system during a trajectory following.

  7. Adaptation of benthic invertebrates to food sources along marine-terrestrial boundaries as indicated by carbon and nitrogen stable isotopes

    Science.gov (United States)

    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.

  8. 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 * Feedback * Feedforward 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

  9. 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.

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

    Science.gov (United States)

    Zia, Omar

    1989-01-01

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

  11. Robust Adaptive Control of a Free-Floating Space Robot System in Cartesian Space

    Directory of Open Access Journals (Sweden)

    Fuhai Zhang

    2015-11-01

    Full Text Available This paper presents a novel, robust, adaptive trajectory-tracking control scheme for the free-floating space robot system in Cartesian space. The dynamic equation of the free-floating space robot system in Cartesian space is derived from the augmented variable method. The proposed basic robust adaptive controller is able to deal with parametric and non-parametric uncertainties simultaneously. Another advantage of the control scheme is that the known and unknown external disturbance bounds can be considered using a modification of the parameter-estimation law. In addition, three cases are certified to achieve robustness for both parametric uncertainties and external disturbances. The simulation results show that the control scheme can ensure stable tracking of the desired trajectory of the end-effector.

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

    Science.gov (United States)

    Nguyen, Nhan T.

    2012-01-01

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

  13. Simple adaptive control for quadcopters with saturated actuators

    Science.gov (United States)

    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.

  14. Spectrum management considerations of adaptive power control in satellite networks

    Science.gov (United States)

    Sawitz, P.; Sullivan, T.

    1983-01-01

    Adaptive power control concepts for the compensation of rain attenuation are considered for uplinks and downlinks. The performance of example power-controlled and fixed-EIRP uplinks is compared in terms of C/Ns and C/Is. Provisional conclusions are drawn with regard to the efficacy of uplink and downlink power control orbit/spectrum utilization efficiency.

  15. Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

    Science.gov (United States)

    Karr, C. L.

    1993-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

  16. Adaptive process control using fuzzy logic and genetic algorithms

    Science.gov (United States)

    Karr, C. L.

    1993-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

  17. Adaptive Control Using a Neural Network Estimator and Dynamic Inversion

    Science.gov (United States)

    Ninomiya, Tetsujiro; Miyazawa, Yoshikazu

    More and more UAVs are developed for various purposes and their flight controllers are required to have sufficient robustness and performance to realize their versatile missions. To design these sophisticated controller is pretty much time-consuming task by traditional design method. Neural network based adaptive control with dynamic inversion is applied to solve this problem. This method has two advantages. One is that the gain scheduling is not necessary because nonlinear dynamic inversion is applied to control nonlinear systems. The other is that neural network improves the controller performance by estimating parameters of the actual plant. Numerical examples show its effectiveness and its ability to adapt to modeling errors. This paper concludes that proposed method reduces the workload of controller design task and it has ability to adapt various errors of nonlinear systems.

  18. Adaptive pitch control for load mitigation of wind turbines

    Science.gov (United States)

    Yuan, Yuan; Tang, J.

    2015-04-01

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

  19. Adaptive Control for Robotic Manipulators Base on RBF Neural Network

    Directory of Open Access Journals (Sweden)

    MA Jing

    2013-09-01

    Full Text Available An adaptive neural network controller is brought forward by the paper to solve trajectory tracking problems of robotic manipulators with uncertainties. The first scheme consists of a PD feedback and a dynamic compensator which is composed by neural network controller and variable structure controller. Neutral network controller is designed to adaptive learn and compensate the unknown uncertainties, variable structure controller is designed to eliminate approach errors of neutral network. The adaptive weight learning algorithm of neural network is designed to ensure online real-time adjustment, offline learning phase is not need; Global asymptotic stability (GAS of system base on Lyapunov theory is analysised to ensure the convergence of the algorithm. The simulation result s show that the kind of the control scheme is effective and has good robustness.

  20. Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System.

    Science.gov (United States)

    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.

  1. Combined MIMO adaptive and decentralized controllers for broadband active noise and vibration control

    NARCIS (Netherlands)

    Berkhoff, Arthur P.; Wesselink, J.M.

    2009-01-01

    Recent implementations of multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations provide considerably improved performance over traditional adaptive algorithms. The most significant performance improvements are in terms of speed of convergence, the amount

  2. Adaptive Fuzzy Sliding Mode Control for a Model-Scaled Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Amir Razzaghian

    2016-11-01

    Full Text Available This paper presents a novel Adaptive Fuzzy Sliding Mode Controller (AFSMC for a model-scaled unmanned helicopter as real nonlinear plant. First, in order to efficient control law design, the nonlinear model of the helicopter is reformulated as an affine nonlinear system. To do this aim, a Dynamic Inverter (DI is introduced as a bijective function. The proposed DI is used to interconnect the helicopter actuators' main inputs to the helicopter dynamic inputs. Then, AFSMC is designed to control it, and the asymptotic stability of the closed loop system is proved using Lyapunov stability theorem. To verify the merits of the proposed controller, it is compared with traditional sliding mode control system. Simulation results confirmed that the controller as a robust and stable control method has desired controlling performance and well cope with the undesirable chattering phenomenon.

  3. Adaptive Feedfoward Feedback Control Framework, Phase I

    Data.gov (United States)

    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...

  4. 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)

  5. ADAPTIVE CONTROL OF FEED LOAD CHANGES IN ALCOHOL FERMENTATION

    Directory of Open Access Journals (Sweden)

    Folly R.

    1997-01-01

    Full Text Available A fed-batch alcohol fermentation on a pilot plant scale with a digital supervisory control system was evaluated as an experimental application case study of an adaptive controller. The verification of intrinsically dynamic variations in the characteristics of the fermentation, observed in previous work, showed the necessity of an adaptive control strategy for controller parameter tuning in order to adjust the changes in the specific rates of consumption, growth and product formation during the process. Satisfactory experimental results were obtained for set-point variations and sugar feed concentration load changes in the manipulated inlet flow to the fermenter

  6. Variable neural adaptive robust control: a switched system approach.

    Science.gov (United States)

    Lian, Jianming; Hu, Jianghai; Żak, Stanislaw H

    2015-05-01

    Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multiinput multioutput uncertain systems. The controllers incorporate a novel variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. It can determine the network structure online dynamically by adding or removing RBFs according to the tracking performance. The structure variation is systematically considered in the stability analysis of the closed-loop system using a switched system approach with the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

  7. Automated Sequential Pushing of Micro Objects By Using Adaptive Controller

    Directory of Open Access Journals (Sweden)

    Mohsen Shahini

    2013-06-01

    Full Text Available This paper focuses on precision automated pushing of multiple micro objects. An adaptive control system is proposed to accurately push and position the micro objects on a substrate. Each micro object exhibits different characteristics in terms of the surface micro forces governing the manipulation process. The controller is designed to compensate for the effect of the micro forces whose aggregated magnitude varies during the process. An experimental setup is designed to validate the performance of the proposed controller. The results of the experiments confirm that the proposed adaptive controller is capable of learning to adjust its parameters effectively, when the surface micro forces change under varying surface and ambient conditions.

  8. 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.

  9. Control Reallocation Strategies for Damage Adaptation in Transport Class Aircraft

    Science.gov (United States)

    Gundy-Burlet, Karen; Krishnakumar, K.; Limes, Greg; Bryant, Don

    2003-01-01

    This paper examines the feasibility, potential benefits and implementation issues associated with retrofitting a neural-adaptive flight control system (NFCS) to existing transport aircraft, including both cable/hydraulic and fly-by-wire configurations. NFCS uses a neural network based direct adaptive control approach for applying alternate sources of control authority in the presence of damage or failures in order to achieve desired flight control performance. Neural networks are used to provide consistent handling qualities across flight conditions, adapt to changes in aircraft dynamics and to make the controller easy to apply when implemented on different aircraft. Full-motion piloted simulation studies were performed on two different transport models: the Boeing 747-400 and the Boeing C-17. Subjects included NASA, Air Force and commercial airline pilots. Results demonstrate the potential for improving handing qualities and significantly increased survivability rates under various simulated failure conditions.

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

    Science.gov (United States)

    Lefevre, Brian D.

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

  11. 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.

  12. Stable benefits of bilateral over unilateral cochlear implantation after two years: A randomized controlled trial.

    Science.gov (United States)

    van Zon, Alice; Smulders, Yvette E; Stegeman, Inge; Ramakers, Geerte G J; Kraaijenga, Veronique J C; Koenraads, Simone P C; Zanten, Gijsbert A Van; Rinia, Albert B; Stokroos, Robert J; Free, Rolien H; Frijns, Johan H M; Huinck, Wendy J; Mylanus, Emmanuel A M; Tange, Rinze A; Smit, Adriana L; Thomeer, Hans G X M; Topsakal, Vedat; Grolman, Wilko

    2017-05-01

    To investigate hearing capabilities and self-reported benefits of simultaneous bilateral cochlear implantation (BiCI) compared with unilateral cochlear implantation (UCI) after a 2-year follow-up and to evaluate the learning effect of cochlear implantees over time. Multicenter randomized controlled trial. Thirty-eight postlingually deafened adults were included in this study and randomly allocated to either UCI or simultaneous BiCI. Our primary outcome was speech intelligibility in noise, with speech and noise coming from straight ahead (Utrecht-Sentence Test with Adaptive Randomized Roving levels). Secondary outcomes were speech intelligibility in noise with spatially separated sources, speech intelligibility in silence (Dutch phoneme test), localization capabilities and self-reported benefits assessed with different quality of hearing and quality of life (QoL) questionnaires. This article describes the results after 2 years of follow-up. We found comparable results for the UCI and simultaneous BiCI group, when speech and noise were both presented from straight ahead. Patients in the BiCI group performed significantly better than patients in the UCI group, when speech and noise came from different directions (P = .01). Furthermore, their localization capabilities were significantly better. These results were consistent with patients' self-reported hearing capabilities, but not with the questionnaires regarding QoL. We found no significant differences on any of the subjective and objective reported outcomes between the 1-year and 2-year follow-up. This study demonstrates important benefits of simultaneous BiCI compared with UCI that remain stable over time. Bilaterally implanted patients benefit significantly in difficult everyday listening situations such as when speech and noise come from different directions. Furthermore, bilaterally implanted patients are able to localize sounds, which is impossible for unilaterally implanted patients. 1b Laryngoscope, 127

  13. A hybrid CPG-ZMP control system for stable walking of a simulated flexible spine humanoid robot.

    Science.gov (United States)

    Or, Jimmy

    2010-04-01

    Biped humanoid robots have gained much popularity in recent years. These robots are mainly controlled by two major control methods, the biologically-inspired approach based on Central Pattern Generator (CPG) and the engineering-oriented approach based on Zero Moment Point (ZMP). Given that flexibility in the body torso is required in some human activities, we believe that it is beneficial for the next generation of humanoid robots to have a flexible spine as humans do. In order to cope with the increased complexity in controlling this type of robot, a new kind of control system is necessary. Currently, there is no controller that allows a flexible spine humanoid robot to maintain stability in real-time while walking with dynamic spine motions. This paper presents a new hybrid CPG-ZMP control system for the walking of a realistically simulated flexible spine humanoid robot. Experimental results showed that using our control method, the robot is able to adapt its spine motions in real-time to allow stable walking. Our control system could be used for the control of the next generation humanoid robots. Copyright 2009 Elsevier Ltd. All rights reserved.

  14. Adaptive control method for functional simulators

    Directory of Open Access Journals (Sweden)

    В.М. Синєглазов

    2008-01-01

    Full Text Available  The structural scheme of operators studying process control and management in the training complex is proposed for observation. Structural scheme includes the division of operators upon the subgroups according to the level of demonstrated knowledge. Also in the article the example of such divisions criteria is presented.

  15. 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.

  16. Hyperchaos control and adaptive synchronization with uncertain ...

    Indian Academy of Sciences (India)

    Mathieu and van der Pol equations, for studying dynamical behaviour, chaos control and its synchronization. The van der Pol oscillator is a nonconservative oscillator with nonlinear damping. Due to this feature, it has become popular for systems with limit cycle oscillations in physics, biology, sociology and even economics.

  17. Developing eco-adaptive cruise control systems.

    Science.gov (United States)

    2014-01-01

    The study demonstrates the feasibility of two eco-driving applications which reduces vehicle fuel consumption and greenhouse gas emissions. In particular, the study develops an eco-drive system that combines eco-cruise control logic with state-of-the...

  18. Adaptive nonlinear neural network controller for rotorcraft vibration

    Science.gov (United States)

    Spencer, Michael G.; Sanner, Robert M.; Chopra, Inderjit

    1997-06-01

    This paper presents research into developing an adaptive nonlinear neural network control algorithm that can be used with smart structure actuators and sensors to control the vibrations of rotor blades. The dynamic equations of motion for a blade have the same form as a multilink manipulator (robot arm) and adaptive nonlinear control algorithms have proven successful in active control of these manipulators. The recent development of neural network control algorithms has provided the ability to adaptively learn in real time a set of parameters that will approximate external forces operating on the blades. The controller combines these two control techniques enabling the controller to adapt its parameters in response to changes in blade properties such as its mass or stiffness and to also learn the parameters necessary to account for the unknown but bounded, periodic disturbance forces such as those caused by the unsteady, periodic aerodynamic forces in the rotor system. Current efforts have been directed at testing the control algorithm on real beams with piezoceramic actuators and sensors. The initial test results have shown that vibration reduction and desired beam motion tracking can be achieved even under the influences of periodic disturbances.

  19. Direct adaptive control of a PUMA 560 industrial robot

    Science.gov (United States)

    Seraji, Homayoun; Lee, Thomas; Delpech, Michel

    1989-01-01

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

  20. Neural and Fuzzy Adaptive Control of Induction Motor Drives

    International Nuclear Information System (INIS)

    Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

    2008-01-01

    This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller

  1. 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.

  2. 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.

  3. On Using Exponential Parameter Estimators with an Adaptive Controller

    Science.gov (United States)

    Patre, Parag; Joshi, Suresh M.

    2011-01-01

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

  4. Adaptive Control of Truss Structures for Gossamer Spacecraft

    Science.gov (United States)

    Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.

    2007-01-01

    Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.

  5. ADAPTIVE OUTPUT CONTROL: SUBJECT MATTER, APPLICATION TASKS AND SOLUTIONS

    Directory of Open Access Journals (Sweden)

    Alexey A. Bobtsov

    2013-01-01

    Full Text Available The problem of adaptive output control for parametric and functionally uncertain plants is considered. Application examples illustrating the practical use of the discussed theory are given along with the mathematical formulation of the problem. A brief review of adaptive output control methods, by both linear and non-linear systems, is presented and an extensive bibliography, in which the reader will find a detailed description of the specific algorithms and their properties, is represented. A new approach to the output control problem - a method of consecutive compensator - is considered in detail.

  6. Adaptive Control with Finite Time Persistency of Excitation.

    Science.gov (United States)

    1986-06-01

    Adaptive FilteringL Prediction and Control, pp. 178-181, Prentice-Hall, Inc., 1984. 3. Astrom , Karl J. and Wittenmark, B., Computer Controlled Systems, pp...Academic Press, Inc., 1980. 7. Astrom , K.J., "Theory and Applications of Adaptive Control: A Survey," Automatica, V. 19, pp. 471-473, September, 1983...September, 1984. 9. Astrom , K.J., Hagander, P., and Sternby, J., "Zeros of Sampled Systems, " Automatica, V. 20, pp. 31-38, January, 1984. 10. Tuschak, R

  7. Adaptive Incentive Controls for Stackelberg Games with Unknown Cost Functionals.

    Science.gov (United States)

    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

  8. An Adaptive Multivariable Control System for Hydroelectric Generating Units

    Directory of Open Access Journals (Sweden)

    Gunne J. Hegglid

    1983-04-01

    Full Text Available This paper describes an adaptive multivariable control system for hydroelectric generating units. The system is based on a detailed mathematical model of the synchronous generator, the water turbine, the exiter system and turbine control servo. The models of the water penstock and the connected power system are static. These assumptions are not considered crucial. The system uses a Kalman filter for optimal estimation of the state variables and the parameters of the electric grid equivalent. The multivariable control law is computed from a Riccatti equation and is made adaptive to the generators running condition by means of a least square technique.

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

    Science.gov (United States)

    Tian, Yu-Chu; Gao, Furong

    1998-06-01

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

  10. 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.

  11. The Basal Ganglia and Adaptive Motor Control

    Science.gov (United States)

    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.

  12. On flexible CAD of adaptive control and identification algorithms

    DEFF Research Database (Denmark)

    Christensen, Anders; Ravn, Ole

    1988-01-01

    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 a t...

  13. Optimal adaptive control for a class of stochastic systems

    NARCIS (Netherlands)

    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

  14. Optimal adaptive control for a class of stochastic systems

    NARCIS (Netherlands)

    Bagchi, Arunabha; Chen, Han-Fu

    1997-01-01

    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

  15. Automated Merging in a Cooperative Adaptive Cruise Control (CACC) System

    NARCIS (Netherlands)

    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,

  16. Automated Merging in a Cooperative Adaptive Cruise Control (CACC) System

    NARCIS (Netherlands)

    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,

  17. 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 ...

  18. Algebraic and adaptive learning in neural control systems

    Science.gov (United States)

    Ferrari, Silvia

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

  19. Nonlinear underwater robot controller design with adaptive disturbance prediction

    Directory of Open Access Journals (Sweden)

    Xin Songa

    2011-08-01

    Full Text Available A new hybrid adaptive control algorithm is proposed for the nonlinear system controller design of underwater robot. Compared with the previous works in the controller design of underwater robot, the main advantages of this work are: (1 A new disturbance prediction and compensation model is proposed; (2 A new adaptive fuzzy smoother is proposed for the control input; (3 A time-varying flow disturbance is considered for the control design which is always neglected in many previous works and several practical experiments under different environment were implemented to verify the control performance. The Lyapunov stability theory proves the stability and convergence of this new control system. Simulation and experiment results demonstrate the performance and the effectiveness of this new algorithm.

  20. Adaptive landing gear concept—feedback control validation

    Science.gov (United States)

    Mikulowski, Grzegorz M.; Holnicki-Szulc, Jan

    2007-12-01

    The objective of this paper is to present an integrated feedback control concept for adaptive landing gears (ALG) and its experimental validation. Aeroplanes are subjected to high dynamic loads as a result of the impact during each landing. Classical landing gears, which are in common use, are designed in accordance with official regulations in a way that ensures the optimal energy dissipation for the critical (maximum) sink speed. The regulations were formulated in order to ensure the functional capability of the landing gears during an emergency landing. However, the landing gears, whose characteristics are optimized for these critical conditions, do not perform well under normal impact conditions. For that situation it is reasonable to introduce a system that would adapt the characteristics of the landing gears according to the sink speed of landing. The considered system assumes adaptation of the damping force generated by the landing gear, which would perform optimally in an emergency situation and would adapt itself for regular landings as well. This research covers the formulation and design of the control algorithms for an adaptive landing gear based on MR fluid, implementation of the algorithms on an FPGA platform and experimental verification on a lab-scale landing gear device. The main challenge of the research was to develop a control methodology that could operate effectively within 50 ms, which is assumed to be the total duration of the phenomenon. The control algorithm proposed in this research was able to control the energy dissipation process on the experimental stand.

  1. A new cold-adapted, alkali-stable and highly salt-tolerant esterase from Bacillus licheniformis.

    Science.gov (United States)

    Zhang, Weijia; Xu, Hui; Wu, Yingqiang; Zeng, Jie; Guo, Ziwei; Wang, Lu; Shen, Cheng; Qiao, Dairong; Cao, Yi

    2018-05-01

    Bacterial esterases and lipases, especially extremozymes attract increasing attention due to various advantages both in good properties and wide applications. In the present study, a cold-adapted, alkali-stable and highly salt-tolerant esterase (Est700) was cloned from Bacillus licheniformis, expressed and purified with a molecular mass of 25 kDa. The optimal temperature of Est700 was 30 °C, with 35% maximal activity retaining at 0 °C. Its optimal pH was 8.0 and showed high stability at pH 5.0-11.0. Noticeably, Est700 was highly activated by 3.5 M NaCl and the extent of this activation is much stronger than that of currently reported halophilic ones. It was also stable in 5 M NaCl with no activity loss. High salt concentrations changed the secondary structure and folding properties of Est700 with formation of more α-helix and less β-sheet domains. With salt incubation, its melting temperature was estimated to be 57.2 °C, which is 12.8 °C higher than that of native one. Interestingly, Est700 lacks the acidic surface that is considered essential for enzyme stability at high salinity. However, it has a mainly positive surface electrostatic potential, which is probably different from most reported halotolerant esterases. These multiple properties make Est700 a valuable candidate in both basic research and industrial applications. Copyright © 2018. Published by Elsevier B.V.

  2. Adaptive Contingency Control: Wind Turbine Operation Integrated with Blade Condition Monitoring

    Data.gov (United States)

    National Aeronautics and Space Administration — We report here on first steps towards integrating systems health monitoring with adaptive contingency controls. In the scenario considered, the adaptive controller...

  3. 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.

  4. Development of fault tolerant adaptive control laws for aerospace systems

    Science.gov (United States)

    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.

  5. Fault-tolerant nonlinear adaptive flight control using sliding mode online learning.

    Science.gov (United States)

    Krüger, Thomas; Schnetter, Philipp; Placzek, Robin; Vörsmann, Peter

    2012-08-01

    An expanded nonlinear model inversion flight control strategy using sliding mode online learning for neural networks is presented. The proposed control strategy is implemented for a small unmanned aircraft system (UAS). This class of aircraft is very susceptible towards nonlinearities like atmospheric turbulence, model uncertainties and of course system failures. Therefore, these systems mark a sensible testbed to evaluate fault-tolerant, adaptive flight control strategies. Within this work the concept of feedback linearization is combined with feed forward neural networks to compensate for inversion errors and other nonlinear effects. Backpropagation-based adaption laws of the network weights are used for online training. Within these adaption laws the standard gradient descent backpropagation algorithm is augmented with the concept of sliding mode control (SMC). Implemented as a learning algorithm, this nonlinear control strategy treats the neural network as a controlled system and allows a stable, dynamic calculation of the learning rates. While considering the system's stability, this robust online learning method therefore offers a higher speed of convergence, especially in the presence of external disturbances. The SMC-based flight controller is tested and compared with the standard gradient descent backpropagation algorithm in the presence of system failures. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Nonlinear Adaptive Power-Level Control for Modular High Temperature Gas-Cooled Reactors

    Science.gov (United States)

    Dong, Zhe

    2013-04-01

    After the Fukushima nuclear accident, much more attention has to be drawn on the safety issues. The improvement of safety has already become the focus of the developing trend of the nuclear energy systems. Due to the inherent safety feature and the potential economic competitiveness, the modular high temperature gas-cooled reactor (MHTGR) has been seen as the central part of the next generation of nuclear plant (NGNP). Power-level control is one of the key techniques that guarantee the safe, stable and efficient operation for nuclear reactors. Since the MHTGR dynamics has the features of strong nonlinearity and uncertainty, in order to improve the operation performance, it is meaningful to develop the nonlinear adaptive power-level control law for the MHTGR. Based on using the natural dynamic features beneficial to system stabilization, a novel nonlinear adaptive power-level control is given for the MHTGR in this paper. It is theoretically proved that this newly-built controller does not only provide globally asymptotic closed-loop stability but is also adaptive to the system uncertainty. This control law is then applied to the power-level regulation of the pebble-bed MHTGR of the HTR-PM power plant. Numerical simulation results show the feasibility of this control law and the relationship between the performance and controller parameters.

  7. Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

    Science.gov (United States)

    Zhang, Yanjun; Tao, Gang; Chen, Mou

    2016-09-01

    This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

  8. 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.

  9. Shared Care in Monitoring Stable Glaucoma Patients: A Randomized Controlled Trial

    NARCIS (Netherlands)

    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

  10. Noninvasive Model Independent Noise Control with Adaptive Feedback Cancellation

    Directory of Open Access Journals (Sweden)

    Jing Yuan

    2008-01-01

    Full Text Available An active noise control (ANC system is model dependent/independent if its controller transfer function is dependent/independent on initial estimates of path models in a sound field. Since parameters of path models in a sound field will change when boundary conditions of the sound field change, model-independent ANC systems (MIANC are able to tolerate variations of boundary conditions in sound fields and more reliable than model-dependent counterparts. A possible way to implement MIANC systems is online path modeling. Many such systems require invasive probing signals (persistent excitations to obtain accurate estimates of path models. In this study, a noninvasive MIANC system is proposed. It uses online path estimates to cancel feedback, recover reference signal, and optimize a stable controller in the minimum H2 norm sense, without any forms of persistent excitations. Theoretical analysis and experimental results are presented to demonstrate the stable control performance of the proposed system.

  11. Frequency Adaptive Control Technique for Periodic Runout and Wobble Cancellation in Optical Disk Drives

    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.

  12. 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

  13. Parallel computation of geometry control in adaptive truss structures

    Science.gov (United States)

    Ramesh, A. V.; Utku, S.; Wada, B. K.

    1992-01-01

    The fast computation of geometry control in adaptive truss structures involves two distinct parts: the efficient integration of the inverse kinematic differential equations that govern the geometry control and the fast computation of the Jacobian, which appears on the right-hand-side of the inverse kinematic equations. This paper present an efficient parallel implementation of the Jacobian computation on an MIMD machine. Large speedup from the parallel implementation is obtained, which reduces the Jacobian computation to an O(M-squared/n) procedure on an n-processor machine, where M is the number of members in the adaptive truss. The parallel algorithm given here is a good candidate for on-line geometry control of adaptive structures using attached processors.

  14. Design of Adaptive Switching Controller for Robotic Manipulators with Disturbance

    Directory of Open Access Journals (Sweden)

    Zhen Yang

    2016-01-01

    Full Text Available Two adaptive switching control strategies are proposed for the trajectory tracking problem of robotic manipulator in this paper. The first scheme is designed for the supremum of the bounded disturbance for robot manipulator being known; while the supremum is not known, the second scheme is proposed. Each proposed scheme consists of an adaptive switching law and a PD controller. Based on the Lyapunov stability theorem, it is shown that two new schemes can guarantee tracking performance of the robotic manipulator and be adapted to the alternating unknown loads. Simulations for two-link robotic manipulator are carried out and show that the two schemes can avoid the overlarge input torque, and the feasibility and validity of the proposed control schemes are proved.

  15. Robot-Control Station Would Adapt To Operator

    Science.gov (United States)

    Diner, Daniel B.

    1993-01-01

    Proposed control station for remote robot adapts control system to personal characteristics and preferences of operator. Automatically adjusts positions and angles of video cameras and monitors, adjusts characteristics of hand controller, process images, and provides graphical displays serving operator best. System of one or more video cameras, controlled by computer, views workspace of robot, as shown in article, "Movable Cameras and Monitors For Viewing Telemanipulator" (NPO-17837). Control station includes several video monitors, hand controller, image-processing system providing graphical displays, voice-input command system, keyboards, and mouse.

  16. Adaptive Backstepping Control of Lightweight Tower Wind Turbine

    DEFF Research Database (Denmark)

    Galeazzi, Roberto; Borup, Kasper Trolle; Niemann, Hans Henrik

    2015-01-01

    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...... 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...

  17. 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.

  18. Mechanisms of motor adaptation in reactive balance control.

    Directory of Open Access Journals (Sweden)

    Torrence D J Welch

    Full Text Available Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations.

  19. An adaptive sliding mode control technology for weld seam tracking

    Science.gov (United States)

    Liu, Jie; Hu, Youmin; Wu, Bo; Zhou, Kaibo; Ge, Mingfeng

    2015-03-01

    A novel adaptive sliding mode control algorithm is derived to deal with seam tracking control problem of welding robotic manipulator, during the process of large-scale structure component welding. The proposed algorithm does not require the precise dynamic model, and is more practical. Its robustness is verified by the Lyapunov stability theory. The analytical results show that the proposed algorithm enables better high-precision tracking performance with chattering-free than traditional sliding mode control algorithm under various disturbances.

  20. Modeling Dynamics and Exploring Control of a Single-Wheeled Dynamically Stable Mobile Robot with Arms

    Science.gov (United States)

    2006-08-31

    Takahashi, T., and Kawamura, A. "A Study on the Zero Moment Point Measurement for Biped Walking Robots ", Proc. of the 7th International Workshop on...STABLE MOBILE ROBOT WITH ARMS" 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER CAPT SCHEARER ERIC M 5e. TASK NUMBER 5f. WORK...Std. Z39.18 Modeling Dynamics and Exploring Control of a Single-Wheeled Dynamically Stable Mobile Robot with Arms Eric M. Schearer CMU-RI-TR-06-37

  1. Algorithms for Optimal Model Distributions in Adaptive Switching Control Schemes

    Directory of Open Access Journals (Sweden)

    Debarghya Ghosh

    2016-03-01

    Full Text Available Several multiple model adaptive control architectures have been proposed in the literature. Despite many advances in theory, the crucial question of how to synthesize the pairs model/controller in a structurally optimal way is to a large extent not addressed. In particular, it is not clear how to place the pairs model/controller is such a way that the properties of the switching algorithm (e.g., number of switches, learning transient, final performance are optimal with respect to some criteria. In this work, we focus on the so-called multi-model unfalsified adaptive supervisory switching control (MUASSC scheme; we define a suitable structural optimality criterion and develop algorithms for synthesizing the pairs model/controller in such a way that they are optimal with respect to the structural optimality criterion we defined. The peculiarity of the proposed optimality criterion and algorithms is that the optimization is carried out so as to optimize the entire behavior of the adaptive algorithm, i.e., both the learning transient and the steady-state response. A comparison is made with respect to the model distribution of the robust multiple model adaptive control (RMMAC, where the optimization considers only the steady-state ideal response and neglects any learning transient.

  2. L1 Adaptive Control for a Vertical Rotor Orientation System

    Directory of Open Access Journals (Sweden)

    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.

  3. Adaptive Neuro-Fuzzy Inference System based DVR Controller Design

    Directory of Open Access Journals (Sweden)

    Brahim FERDI

    2011-06-01

    Full Text Available PI controller is very common in the control of DVRs. However, one disadvantage of this conventional controller is its inability to still working well under a wider range of operating conditions. So, as a solution fuzzy controller is proposed in literature. But, the main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, Adaptive Neuro-Fuzzy Inference System (ANFIS based controller design is proposed. The resulted controller is composed of Sugeno fuzzy controller with two inputs and one output. According to the error and error rate of the control system and the output data, ANFIS generates the appropriate fuzzy controller. The simulation results have proved that the proposed design method gives reliable powerful fuzzy controller with a minimum number of membership functions.

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

    Science.gov (United States)

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

    2007-01-01

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

  5. Adaptive control strategies for interlimb coordination in legged robots

    DEFF Research Database (Denmark)

    Aoi, Shinya; Manoonpong, Poramate; Ambe, Yuichi

    2017-01-01

    for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task). In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms......Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear....... Recently, investigations of the adaptationmechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination...

  6. 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.

  7. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    Science.gov (United States)

    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.

  8. 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.

  9. Control technique for enhancing the stable operation of distributed generation units within a microgrid

    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

  10. An Improved Adaptive Tracking Controller of Permanent Magnet Synchronous Motor

    Directory of Open Access Journals (Sweden)

    Tat-Bao-Thien Nguyen

    2014-01-01

    Full Text Available This paper proposes a new adaptive fuzzy neural control to suppress chaos and also to achieve the speed tracking control in a permanent magnet synchronous motor (PMSM drive system with unknown parameters and uncertainties. The control scheme consists of fuzzy neural and compensatory controllers. The fuzzy neural controller with online parameter tuning is used to estimate the unknown nonlinear models and construct linearization feedback control law, while the compensatory controller is employed to attenuate the estimation error effects of the fuzzy neural network and ensure the robustness of the controlled system. Moreover, due to improvement in controller design, the singularity problem is surely avoided. Finally, numerical simulations are carried out to demonstrate that the proposed control scheme can successfully remove chaotic oscillations and allow the speed to follow the desired trajectory in a chaotic PMSM despite the existence of unknown models and uncertainties.

  11. 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.

  12. Design of a biped locomotion controller based on adaptive neuro-fuzzy inference systems

    Science.gov (United States)

    Shieh, M.-Y.; Chang, K.-H.; Lia, Y.-S.

    2008-02-01

    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.

  13. Adaptive Control of Artificial Pancreas Systems - A Review

    Directory of Open Access Journals (Sweden)

    Kamuran Turksoy

    2014-01-01

    Full Text Available Artificial pancreas (AP systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.

  14. 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...... controller precisely accounts for the transmission/distribution line impedances. The controller on each converter exchanges data with only its neighbor converters on a sparse communication graph spanned across the Microgrid. Global dynamic model of the Microgrid is derived, with the proposed controller...

  15. Model-free adaptive control of advanced power plants

    Science.gov (United States)

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

    2015-08-18

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

  16. PI controller based model reference adaptive control for nonlinear

    African Journals Online (AJOL)

    user

    efficiently updating the weight is useful in many applications such identification of nonlinear systems. Off-line iterative algorithm can be employed in such care of identification or modeling. However, in the aspect of control, the NN should work in on line manner. In the control system structure, the output of NN is the control ...

  17. Embedded two level direct adaptive fuzzy controller for DC motor speed control

    Directory of Open Access Journals (Sweden)

    Ahmad M. Zaki

    2018-03-01

    Full Text Available This paper presents a proposed approach based on an adaptive fuzzy logic controller for precise control of the DC motor speed. In this concern, the proposed Direct Adaptive Fuzzy Logic Controller (DAFLC is estimated from two levels, where the lower level uses a Mamdani fuzzy controller and the upper level is an inverse model based on a Takagi–Sugeno (T–S method in which its output is used to adapt the parameters of the fuzzy controller in the lower level. The proposed controller is implemented using an Arduino DUE kit. From the practical results, it is proved that the proposed adaptive controller improves, successfully both the performance response and the disturbance due to the load in the speed control of the DC motor.

  18. Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

    Science.gov (United States)

    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.

  19. Adaptive Current Control Method for Hybrid Active Power Filter

    Science.gov (United States)

    Chau, Minh Thuyen

    2016-09-01

    This paper proposes an adaptive current control method for Hybrid Active Power Filter (HAPF). It consists of a fuzzy-neural controller, identification and prediction model and cost function. The fuzzy-neural controller parameters are adjusted according to the cost function minimum criteria. For this reason, the proposed control method has a capability on-line control clings to variation of the load harmonic currents. Compared to the single fuzzy logic control method, the proposed control method shows the advantages of better dynamic response, compensation error in steady-state is smaller, able to online control is better and harmonics cancelling is more effective. Simulation and experimental results have demonstrated the effectiveness of the proposed control method.

  20. Adaptive Wavelet Coding Applied in a Wireless Control System

    Science.gov (United States)

    Gama, Felipe O. S.; O. Salazar, Andrés

    2017-01-01

    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 Eb/N0 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. PMID:29236048

  1. 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.

  2. Adaptive control and synchronization of a fractional-order chaotic ...

    Indian Academy of Sciences (India)

    tem based on the stability theory of fractional-order dynamic systems. The presented schemes, which contain only a single-state variable, are simple and flexible. Numerical simulations are used to demonstrate the feasibility of the presented methods. Keywords. Fractional order; adaptive scheme; control; synchronization.

  3. 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.

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

    African Journals Online (AJOL)

    user

    The paper developed artificial intelligence technique adaptive neuro-fuzzy controller for air conditioning systems at different pressures. The first order Sugeno fuzzy .... condenser heat rejection rate, refrigerant mass flow rate, compressor power, electric power input to the compressor motor and the coefficient of performance.

  5. 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

  6. Driving characteristics and adaptive cruise control : A naturalistic driving study

    NARCIS (Netherlands)

    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

  7. Adaptive control and synchronization of a fractional-order chaotic ...

    Indian Academy of Sciences (India)

    journal of. April 2013 physics pp. 583–592. Adaptive control and synchronization of a fractional-order chaotic system. CHUNLAI LI1,∗ and YAONAN TONG2. 1College of Physics and Electronics; 2School of Information and Communication Engineering,. Hunan Institute of Science and Technology, Yueyang 414006, China.

  8. Vision-based adaptive cruise control using pattern matching

    CSIR Research Space (South Africa)

    Kanjee, R

    2013-10-01

    Full Text Available Adaptive Cruise Control (ACC) is a relatively new system designed to assist automobile drivers in maintaining a safe following distance. This paper proposes and validates a vision-based ACC system which uses a single camera to obtain the clearance...

  9. Evaluating adaptive cruise control strategies in worst-case scenarios

    NARCIS (Netherlands)

    Willigen, W.H. van; Schut, M.C.; Kester, L.J.H.M.

    2011-01-01

    This paper is concerned with safety in (cooperative) adaptive cruise control systems. In these systems, the speed of the cars is maintained automatically, based on the preferred speed of the driver and the speed of the preceding car. Technologies that are used in these systems, such as radar and

  10. Continuous use of an adaptive lung ventilation controller in critically ...

    African Journals Online (AJOL)

    1995-05-05

    May 5, 1995 ... Continuous use of an adaptive lung ventilation controller in critically ill patients in a multi- disciplinary intensive care unit. David M. Linton, Josef x. .... Integration of the flow signal yielded the inspired volume (\\/J and the expired volume (\\/J. Tidal volume 0JT) was calculated as the arithmetical mean of both.

  11. Adaptive Insecure Attachment and Resource Control Strategies during Middle Childhood

    Science.gov (United States)

    Chen, Bin-Bin; Chang, Lei

    2012-01-01

    By integrating the life history theory of attachment with resource control theory, the current study examines the hypothesis that insecure attachment styles reorganized in middle childhood are alternative adaptive strategies used to prepare for upcoming competition with the peer group. A sample of 654 children in the second through seventh grades…

  12. Anticipation and the adaptive control of safety margins in driving

    NARCIS (Netherlands)

    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

  13. Optimal adaptive scheduling and control of beer membrane filtration

    NARCIS (Netherlands)

    Willigenburg, van L.G.; Vollebregt, H.M.; Sman, van der R.G.M.

    2015-01-01

    An adaptive optimal scheduling and controller design is presented that attempts to improve the performance of beer membrane filtration over the ones currently obtained by operators. The research was performed as part of a large European research project called EU Cafe with the aim to investigate the

  14. Synchronization of general complex networks via adaptive control ...

    Indian Academy of Sciences (India)

    2014-03-07

    Mar 7, 2014 ... networks with derivative coupling and time-delay coupling was investigated by adaptive control schemes [42]. However ... [41], the synchronization of complex dynamical networks with non-derivative coupling and derivative coupling .... For any symmetric positive definite matrix. M ∈ Rn×n and x,y ∈ Rn, ...

  15. Cascaded adaptive control of ocean vehicles with significant actuator dynamics

    Directory of Open Access Journals (Sweden)

    Thor I. Fossen

    1994-04-01

    Full Text Available This paper presents a cascade adaptive control scheme for marine vehicles where the non-linear equations of motion include a model of the actuator dynamics. The adaptive controller does not require the parameters of the vehicle dynamics and the actuator time constants to be known a priori. Both the velocity and position tracking errors are shown to converge to zero by applying Barbalat's lemma. Global asymptotic stability is proven for the velocity scheme while the position/attitude controller is only proven to be convergent. Furthermore, all parameter estimates are shown to be bounded. Computer simulations of an ROV speed control system and an autopilot for automatic ship steering are used to illustrate the design methodology.

  16. 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.

  17. Bifurcations, chaos and adaptive backstepping sliding mode control of a power system with excitation limitation

    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.

  18. Neural network based adaptive output feedback control: Applications and improvements

    Science.gov (United States)

    Kutay, Ali Turker

    Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experiments is investigated in this thesis. The purpose is to evaluate the theory behind the development of these controllers numerically and experimentally, identify the needs for further development in practical applications, and to conduct further research in directions that are identified to ultimately enhance applicability of adaptive controllers to real world problems. We mainly focus our attention on adaptive controllers that augment existing fixed gain controllers. A recently developed approach holds great potential for successful implementations on real world applications due to its applicability to systems with minimal information concerning the plant model and the existing controller. In this thesis the formulation is extended to the multi-input multi-output case for distributed control of interconnected systems and successfully tested on a formation flight wind tunnel experiment. The command hedging method is formulated for the approach to further broaden the class of systems it can address by including systems with input nonlinearities. Also a formulation is adopted that allows the approach to be applied to non-minimum phase systems for which non-minimum phase characteristics are modeled with sufficient accuracy and treated properly in the design of the existing controller. It is shown that the approach can also be applied to augment nonlinear controllers under certain conditions and an example is presented where the nonlinear guidance law of a spinning projectile is augmented. Simulation results on a high fidelity 6 degrees-of-freedom nonlinear simulation code are presented. The thesis also presents a preliminary adaptive controller design for closed loop flight control with active flow actuators. Behavior of such actuators in dynamic flight conditions is not known. To test the adaptive controller design in

  19. The application of adaptive Luenberger observer concept in chemical process control: An algorithmic approach

    Science.gov (United States)

    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.

  20. Continuous control of asymmetric forebody vortices in a bi-stable state

    Science.gov (United States)

    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.

  1. 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.

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

    Science.gov (United States)

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

    2016-12-01

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

  3. Robust Adaptive Integral Backstepping Control of a 3-DOF Helicopter

    OpenAIRE

    Zheng Fang; Weinan Gao; Lei Zhang

    2012-01-01

    Unmanned aerial vehicles have enormous potential applications in military and civil fields. A Quanser’s 3‐DOF helicopter is a simplified and benchmark experimental model for validating the effectiveness of various flight control algorithms. The attitude control of the 3‐DOF helicopter is a challenging task since the helicopter is an under‐actuated system with strong coupling and model uncertainty characteristics. In this paper, an adaptive integral backstepping algorithm is proposed to realiz...

  4. 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.

  5. 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.

  6. Adaptive Current Control with PI-Fuzzy Compound Controller for Shunt Active Power Filter

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2013-01-01

    Full Text Available An adaptive control technology and PI-fuzzy compound control technology are proposed to control an active power filter (APF. AC side current compensation and DC capacitor voltage tracking control strategy are discussed and analyzed. Model reference adaptive controller for the AC side current compensation is derived and established based on Lyapunov stability theory; proportional and integral (PI fuzzy compound controller is designed for the DC side capacitor voltage control. The adaptive current controller based on PI-fuzzy compound system is compared with the conventional PI controller for active power filter. Simulation results demonstrate the feasibility and satisfactory performance of the proposed control strategies. It is shown that the proposed control method has an excellent dynamic performance such as small current tracking error, reduced total harmonic distortion (THD, and strong robustness in the presence of parameters variation and nonlinear load.

  7. 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

  8. 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...... sharing. The proposed controller precisely accounts for the transmission/distribution line impedances. The controller on each converter exchanges data with only its neighbor converters on a sparse communication graph spanned across the microgrid. Global dynamic model of the microgrid is derived...

  9. Fuzzy Adaptive Control for Intelligent Autonomous Space Exploration Problems

    Science.gov (United States)

    Esogbue, Augustine O.

    1998-01-01

    The principal objective of the research reported here is the re-design, analysis and optimization of our newly developed neural network fuzzy adaptive controller model for complex processes capable of learning fuzzy control rules using process data and improving its control through on-line adaption. The learned improvement is according to a performance objective function that provides evaluative feedback; this performance objective is broadly defined to meet long-range goals over time. Although fuzzy control had proven effective for complex, nonlinear, imprecisely-defined processes for which standard models and controls are either inefficient, impractical or cannot be derived, the state of the art prior to our work showed that procedures for deriving fuzzy control, however, were mostly ad hoc heuristics. The learning ability of neural networks was exploited to systematically derive fuzzy control and permit on-line adaption and in the process optimize control. The operation of neural networks integrates very naturally with fuzzy logic. The neural networks which were designed and tested using simulation software and simulated data, followed by realistic industrial data were reconfigured for application on several platforms as well as for the employment of improved algorithms. The statistical procedures of the learning process were investigated and evaluated with standard statistical procedures (such as ANOVA, graphical analysis of residuals, etc.). The computational advantage of dynamic programming-like methods of optimal control was used to permit on-line fuzzy adaptive control. Tests for the consistency, completeness and interaction of the control rules were applied. Comparisons to other methods and controllers were made so as to identify the major advantages of the resulting controller model. Several specific modifications and extensions were made to the original controller. Additional modifications and explorations have been proposed for further study. Some of

  10. Simple robust control laws for robot manipulators. Part 1: Non-adaptive case

    Science.gov (United States)

    Wen, J. T.; Bayard, D. S.

    1987-01-01

    A new class of exponentially stabilizing control laws for joint level control of robot arms is introduced. It has been recently recognized that the nonlinear dynamics associated with robotic manipulators have certain inherent passivity properties. More specifically, the derivation of the robotic dynamic equations from the Hamilton's principle gives rise to natural Lyapunov functions for control design based on total energy considerations. Through a slight modification of the energy Lyapunov function and the use of a convenient lemma to handle third order terms in the Lyapunov function derivatives, closed loop exponential stability for both the set point and tracking control problem is demonstrated. The exponential convergence property also leads to robustness with respect to frictions, bounded modeling errors and instrument noise. In one new design, the nonlinear terms are decoupled from real-time measurements which completely removes the requirement for on-line computation of nonlinear terms in the controller implementation. In general, the new class of control laws offers alternatives to the more conventional computed torque method, providing tradeoffs between robustness, computation and convergence properties. Furthermore, these control laws have the unique feature that they can be adapted in a very simple fashion to achieve asymptotically stable adaptive control.

  11. 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.

  12. Robust Command Filtered Adaptive Backstepping Control for a Quadrotor Aircraft

    Directory of Open Access Journals (Sweden)

    Yicheng Liu

    2018-01-01

    Full Text Available This paper addresses a robust trajectory tracking controller for an underactuated quadrotor with external bounded disturbances and unknown inertia parameters. Different from most of the existing control algorithms, the proposed method does not adopt the dual-loop scheme in which the design is divided into position control and attitude control. Instead, command filter backstepping is employed to design the controller based on the integrated motion model such that the stability can be guaranteed strictly for the flight control system. Furthermore, adaptive compensation and robust compensation are introduced to deal with the uncertainty of the inertia parameters and the external bounded disturbances, respectively. Finally, a similar skew symmetric structure is chosen as the desired structure of the closed-loop system to facilitate the analysis of the stability of the integrated system. Stability and robust performance of the designed controller are verified by Lyapunov stability theorem. Simulations are provided to validate the proposed controller.

  13. Comparison of Conventional Closed-Loop Controller with an Adaptive Controller for a Disturbed Thermodynamic System

    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...... and Lyapunov principle leads to a more robust and accurate regulation. Both controllers have been tested on a thermodynamic system exposed to a disturbance. The experiment shows that the adaptive controller handles the disturbance faster and more accurate....

  14. 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)

  15. Stable Control of Firing Rate Mean and Variance by Dual Homeostatic Mechanisms.

    Science.gov (United States)

    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.

  16. Implementation of Adaptive Digital Controllers on Programmable Logic Devices

    Science.gov (United States)

    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

  17. Nonlinear adaptive control of an elastic robotic arm

    Science.gov (United States)

    Singh, S. N.

    1986-01-01

    An approach to control of a class of nonlinear flexible robotic systems is presented. For simplicity, a robot arm (PUMA-type) with three rotational joints is considered. The third link is assumed to be elastic. An adaptive torquer control law is derived for controlling the joint angles. This controller includes a dynamic system in the feedback path, requires only joint angle and rate for feedback, and asymptotically decomposes the elastic dynamics into two subsystems representing the transverse vibrations of the elastic link in two orthogonal planes. To damp out the elastic vibration, a force control law using modal feedback is synthesized. The combination of the torque and force control laws accomplishes joint angle control and elastic mode stabilization.

  18. Adaptive and Robust Sliding Mode Position Control of IPMSM Drives

    Directory of Open Access Journals (Sweden)

    ZAKY, M.

    2017-02-01

    Full Text Available This paper proposes an adaptive and robust sliding mode control (SMC for the position control of Interior Permanent Magnet Synchronous Motor (IPMSM drives. A switching surface of SMC is designed using a Linear Quadratic Regulator (LQR technique to simultaneously control the tracking trajectory and load torque changes. The quadratic optimal control method is used to select the state feedback control gain that constitutes the system dynamic performance under uncertainties and disturbances. Feedback and switching gains are selected to satisfy both stability and fast convergence of the IPMSM. Matlab/Simulink is used to build the drive system. Experimental implementation of the IPMSM drive is carried out using DSP-DS1102 control board. The efficacy of the proposed position control method is validated using theoretical analysis and simulation and experimental results.

  19. Adaptive Tracking Control for Robots With an Interneural Computing Scheme.

    Science.gov (United States)

    Tsai, Feng-Sheng; Hsu, Sheng-Yi; Shih, Mau-Hsiang

    2018-04-01

    Adaptive tracking control of mobile robots requires the ability to follow a trajectory generated by a moving target. The conventional analysis of adaptive tracking uses energy minimization to study the convergence and robustness of the tracking error when the mobile robot follows a desired trajectory. However, in the case that the moving target generates trajectories with uncertainties, a common Lyapunov-like function for energy minimization may be extremely difficult to determine. Here, to solve the adaptive tracking problem with uncertainties, we wish to implement an interneural computing scheme in the design of a mobile robot for behavior-based navigation. The behavior-based navigation adopts an adaptive plan of behavior patterns learning from the uncertainties of the environment. The characteristic feature of the interneural computing scheme is the use of neural path pruning with rewards and punishment interacting with the environment. On this basis, the mobile robot can be exploited to change its coupling weights in paths of neural connections systematically, which can then inhibit or enhance the effect of flow elimination in the dynamics of the evolutionary neural network. Such dynamical flow translation ultimately leads to robust sensory-to-motor transformations adapting to the uncertainties of the environment. A simulation result shows that the mobile robot with the interneural computing scheme can perform fault-tolerant behavior of tracking by maintaining suitable behavior patterns at high frequency levels.

  20. The Stable Trajectory Tracking Control of a Skid-Steered Mobile Platform with Dynamic Uncertainties

    Directory of Open Access Journals (Sweden)

    Seungwoo Jeon

    2015-09-01

    Full Text Available In order to clean the surfaces of air ducts in underground facilities, recent research has been conducted on driving the control and development of an autonomous mobile duct-cleaning platform. The duct-cleaning robots removes contaminants that are inside a duct using the friction between a rotating cleaning brush and the duct surface. For the effective removal of the contaminants and stable steering control of the autonomous mobile platform, the interaction force between the brush and the duct surface needs to be measured. However, it is not possible to achieve an accurate measurement of the contact force for the duct surface and brush, which has a nonlinear deformation characteristic. Therefore, in this study, a simple and robust controller has been proposed. This controller integrates the backstepping method with an I-PD controller for the robust platform control against irregular external forces on the cleaning brush. In addition, various trajectory tracking simulations have been conducted and the results present stable trajectory tracking of the mobile platform in air duct cleaning.

  1. Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control

    Science.gov (United States)

    Eshak, Peter B.

    Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID to estimate and update the controller parameter. Finally, a new controller design was introduced, which integrated both direct and indirect control laws. This controller is known as hybrid adaptive controller. This last control design outperformed the two earlier designs in terms of less NNs effort and better tracking quality. The performance of online PID has an important role in the quality of the hybrid controller; therefore, the quality of the estimation will be of a great importance. Unfortunately, PID is not perfect and the online estimation process has some inherited issues; the online PID estimates are primarily affected by delays and biases. In order to ensure updating reliable estimates to the controller, the estimator consumes some time to converge. Moreover, the estimator will often converge to a biased value. This thesis conducts a sensitivity analysis for the estimation issues, delay and bias, and their effect on the tracking quality. In addition, the performance of the hybrid controller as compared to direct adaptive controller is explored. In order to serve this purpose, a simulation environment in MATLAB/SIMULINK has been created. The simulation environment is customized to provide the user with the flexibility to add different combinations of biases and delays to

  2. Adaptive Impedance Controller for a Robot Astronaut to Climb Stably in a Space Station

    Directory of Open Access Journals (Sweden)

    Bo Wei

    2016-05-01

    Full Text Available Maintaining stability is a significant challenge during the control of a robot astronaut while climbing with human-like dual-arm action in a space station. This challenge is caused by conflicting force generated by dynamic internal forces in the closed chain during dual-arm climbing. In general, an impedance controller is suitable for solving this problem. However, the conflicting force in the rigid closed chain is stored in the virtual spring of the impedance controller (especially in microgravity, where even small disturbances cause a significant change in robot astronaut movements. As such, it is difficult to select suitable control parameters for the stable climbing of a robot astronaut. This paper proposes an adaptive algorithm to optimize the impedance controller parameters. This eliminates conflicting force disturbances, with one arm in compliance with the motion of the other. It provides scope for achieving stable motion without the need for precise control parameters. Finally, the stability of the proposed algorithm is demonstrated by Lyapunov theory using a robot called ASTROBOT. The experimental results show the validity of the proposed algorithm.

  3. Flexible Joints Robotic Manipulator Control By Adaptive Gain Smooth Sliding Observer-Controller

    Directory of Open Access Journals (Sweden)

    A. FILIPESCU

    2003-12-01

    Full Text Available An adaptive gain sliding observer for uncertain parameter nonlinear systems together with an adaptive gain sliding controller is proposed in this paper. It considered nonlinear, SISO affine systems, with uncertainties in steady-state functions and parameters. A further parameter term, adaptively updated, has been introduced in steady state space model of the controlled system, in order to obtain useful information despite fault detection and isolation. By using of the sliding observer with adaptive gain, the robustness to uncertainties is increased and the parameters adaptively updated can provide useful information in fault detection. Also, the state estimation error is bounded accordingly with bound limits of the uncertainties. The both of them, the sliding adaptive observer and sliding controller are designed to fulfill the attractiveness condition of its corresponding switching surface. An application to a single arm with flexible joint robot is presented. In order to alleviate chattering, a parameterized tangent hyperbolic has been used as switching function, instead of pure relay one, to the observer and the controller. Also, the gains of the switching functions, to the sliding observer and sliding controller are adaptively updated depending of estimation error and tracking error, respectively. By the using adaptive gains, the transient and tracking response can be improved.

  4. Embedded intelligent adaptive PI controller for an electromechanical system.

    Science.gov (United States)

    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.

  5. Adaptive suboptimal second-order sliding mode control for microgrids

    Science.gov (United States)

    Incremona, Gian Paolo; Cucuzzella, Michele; Ferrara, Antonella

    2016-09-01

    This paper deals with the design of adaptive suboptimal second-order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second-order systems in Brunovsky canonical form, characterised by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analysed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies, the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state space of the auxiliary system becomes attractive. In the other two strategies, a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady state. The microgrid system in a grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.

  6. 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.

  7. Attitude and Altitude Control of Trirotor UAV by Using Adaptive Hybrid Controller

    OpenAIRE

    Zain Anwar Ali; Daobo Wang; Suhaib Masroor; M. Shafiq Loya

    2016-01-01

    The paper presents an adaptive hybrid scheme which is based on fuzzy regulation, pole-placement, and tracking (RST) control algorithm for controlling the attitude and altitude of trirotor UAV. The dynamic and kinematic model of Unmanned Aerial Vehicle (UAV) is unstable and nonlinear in nature with 6 degrees of freedom (DOF); that is why the stabilization of aerial vehicle is a difficult task. To stabilize the nonlinear behavior of our UAV, an adaptive hybrid controller algorithm is used, in w...

  8. Dynamic Performance of Grid Converters using Adaptive DC Voltage Control

    DEFF Research Database (Denmark)

    Trintis, Ionut; Sun, Bo; Guerrero, Josep M.

    2014-01-01

    This paper investigates a controller that ensures minimum operating dc-link voltage of a back-to-back converter system. The dc-link voltage adapts its reference based on the system state, reference given by an outer loop to the dc-link voltage controller. The operating dc-link voltage should...... be kept as low as possible to increase the power conversion efficiency and increase the reliability of converters. The dynamic performance of the proposed controller is investigated by simulations and experiments....

  9. 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...... signal samples. The ability to reproduce observations is measured as an easily computable signal norm. Compared to other related approaches, our procedure is designed to be able to handle significant measurement noise and closed-loop correlations between output measurements and control signals....

  10. 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...

  11. A low order adaptive control scheme for hydraulic servo systems

    DEFF Research Database (Denmark)

    Andersen, Torben Ole; Pedersen, Henrik Clemmensen; Bech, Michael Møller

    2015-01-01

    , active gain feedforward shows a slightly improved performance. Computed-Torque Control shows better performance, but requires a well described system for best performance. A novel Adaptive Inverse Dynamics Controller was tested and the performance was found to be similar to that of Computed...... system were constructed and linearized. Controllers are implemented and tested on the manipulator. Pressure feedback was found to greatly improve system stability margins. Passive gain feedforward shows improved tracking performance for small changes in load pressure. For large changes in load pressure...

  12. Computational methods for the verification of adaptive control systems

    Science.gov (United States)

    Prasanth, Ravi K.; Boskovic, Jovan; Mehra, Raman K.

    2004-08-01

    Intelligent and adaptive control systems will significantly challenge current verification and validation (V&V) processes, tools, and methods for flight certification. Although traditional certification practices have produced safe and reliable flight systems, they will not be cost effective for next-generation autonomous unmanned air vehicles (UAVs) due to inherent size and complexity increases from added functionality. Affordable V&V of intelligent control systems is by far the most important challenge in the development of UAVs faced by both commercial and military aerospace industry in the United States. This paper presents a formal modeling framework for a class of adaptive control systems and an associated computational scheme. The class of systems considered include neural network-based flight control systems and vehicle health management systems. This class of systems and indeed all adaptive systems are hybrid systems whose continuum dynamics is nonlinear. Our computational procedure is iterative and each iteration has two sequential steps. The first step is to derive an approximating finite-state automaton whose behaviors contain the behaviors of the hybrid system. The second step is to check if the language accepted by the approximating automaton is empty (emptiness checking). The iterations are terminated if the language accepted is empty; otherwise, the approximation is refined and the iteration is continued. This procedure will never produce an "error-free" certificate when the actual system contains errors which is an important requirement in V&V of safety critical systems.

  13. An adaptive learning control system for large flexible structures

    Science.gov (United States)

    Thau, F. E.

    1985-01-01

    The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

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

    Science.gov (United States)

    Volyanskyy, Kostyantyn Y.

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

  15. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    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.

  16. Adaptive model predictive process control using neural networks

    Science.gov (United States)

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

    1997-08-19

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

  17. Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller

    Science.gov (United States)

    Engel, E.; Kovalev, I. V.; Karandeev, D.

    2015-10-01

    The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.

  18. Defense Profiles in Adaptation Process to Sport Competition and Their Relationships with Coping, Stress and Control.

    Science.gov (United States)

    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.

  19. Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity

    Science.gov (United States)

    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.

  20. Adaptive Array Antenna Control Methods with Delay Tolerant Networking for the Winter Road Surveillance System

    Directory of Open Access Journals (Sweden)

    Noriki Uchida

    2017-02-01

    Full Text Available It is considered that the road condition in the winter is one of the significant issues for the safety driving by tourists or residents. However, there are many difficulties of the V2V networks such as the transmission range of wireless networks and the noises from the automobilefs bodies. Thus, this paper introduces the Adaptive Array Antenna (AAA controls for the vehicle-to-vehicle (V2V networks based the Delay Tolerant Networking (DTN in the road surveillance system. In the proposed system, the vehicles equip the AAA control systems with IEEE802.11a/b/g based the DTN, and the wireless directions are controlled by the visual recognitions with Kalman filter algorithm to make the longer and stable wireless connections for the efficiency of the DTN. The porotype system is introduced in this paper, and the results are discussed for the future studies.

  1. Design of adaptive control systems by means of self-adjusting transversal filters

    Science.gov (United States)

    Merhav, S. J.

    1986-01-01

    The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

  2. Adaptive pitch control for variable speed wind turbines

    Science.gov (United States)

    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.

  3. Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance

    OpenAIRE

    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...

  4. Adaptive Reference Control for Pressure Management in Water Networks

    DEFF Research Database (Denmark)

    Kallesøe, Carsten; Jensen, Tom Nørgaard; Wisniewski, Rafal

    2015-01-01

    consumers are considered. Under mild assumptions on the consumption pattern and hydraulic resistances of pipes we use properties of the network graph and Kirchhoffs node and mesh laws to show that simple relations exist between the actuator pressure and critical point pressures inside the network....... 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....

  5. Adaptive Dynamics, Control, and Extinction in Networked Populations

    Science.gov (United States)

    2015-07-09

    extinction . VI. CONCLUSIONS We have presented a method for predicting extinction in stochastic network systems by analyzing a pair-based proxy model...including games on networks (e.g., [40], [41]). Further, we expect that our method of continuously varying a parameter while tracking the path to extinction ...Adaptive Dynamics, Control, and Extinction in Networked Populations Ira B. Schwartz US Naval Research Laboratory Code 6792 Nonlinear System Dynamics

  6. Adaptive control of ROVs with actuator dynamics and saturation

    Directory of Open Access Journals (Sweden)

    Ola-Erik Fjellstad

    1992-07-01

    Full Text Available A direct model reference adaptive controller (MRAC is derived for an underwater vehicle with significant thruster dynamics and limited thruster power. The reference model decomposition (RMD technique is used to compensate for the thruster dynamics. A reference model adjustment (RMA technique modifying the reference model acceleration is used to avoid thruster saturation. The design methods are simulated for the yawing motion of an underwater vehicle.

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

    Science.gov (United States)

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

    2017-10-01

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

  8. Comparison of Adaptive Antenna Arrays Controlled by Gradient Algorithms

    Directory of Open Access Journals (Sweden)

    Z. Raida

    1994-09-01

    Full Text Available The paper presents the Simple Kalman filter (SKF that has been designed for the control of digital adaptive antenna arrays. The SKF has been applied to the pilot signal system and the steering vector one. The above systems based on the SKF are compared with adaptive antenna arrays controlled by the classical LMS and the Variable Step Size (VSS LMS algorithms and by the pure Kalman filter. It is shown that the pure Kalman filter is the most convenient for the control of the adaptive arrays because it does not require any a priori information about noise statistics and excels in high rate of convergence and low misadjustment. Extremely high computational requirements are drawback of this filter. Hence, if low computational power of signal processors is at the disposal, the SKF is recommended to be used. Computational requirements of the SKF are of the same order as the classical LMS algorithm exhibits. On the other hand, all the important features of the pure Kalman filter are inherited by the SKF. The paper shows that presented Kalman filters can be regarded as special gradient algorithms. That is why they can be compared with the LMS family.

  9. Robust adaptive control of underwater vehicles: A comparative study

    Directory of Open Access Journals (Sweden)

    Thor I. Fossen

    1996-01-01

    Full Text Available Robust adaptive control of underwater vehicles in 6 DOF is analysed in the context of measurement noise. The performance of the adaptive control laws of Sadegh and Harowitz (1990 and Slotine and Benedetto (1990 are compared. Both these schemes require that all states are measured, that is the velocities and positions in surge, sway, heave, roll, pitch and yaw. However, for underwater vehicles it is difficult to measure the linear velocities whereas angular velocity measurements can be obtained by using a 3 axes angular rate sensor. This problem is addressed by designing a nonlinear observer for linear velocity state estimation. The proposed observer requires that the position and the attitude are measured, e.g. by using a hydroacoustic positioning system for linear positions, two gyros for roll and pitch and a compass for yaw. In addition angular rate measurements will be assumed available from a 3-axes rate sensor or a state estimator. It is also assumed that the measurement rate is limited to 2 Hz for all the sensors. Simulation studies with a 3 DOF AUV model are used to demonstrate the convergence and robustness of the adaptive control laws and the velocity state observer.

  10. An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer.

    Science.gov (United States)

    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.

  11. Adaptive feedforward control of exhaust recirculation in large diesel engines

    DEFF Research Database (Denmark)

    Nielsen, Kræn Vodder; Blanke, Mogens; Eriksson, Lars

    2017-01-01

    Environmental concern has led the International Maritime Organization to restrict NO푥 emissions from marine diesel engines. Exhaust gas recirculation (EGR) systems have been introduced in order to comply to the new standards. Traditional fixed-gain feedback methods are not able to control the EGR...... is generalized to a class of first order Hammerstein systems with sensor delay and exponentially converging bounds of the control error are proven analytically. It is then shown how to apply the method to the EGR system of a two-stroke crosshead diesel engine. The controller is validated by closed loop...... system adequately in engine loading transients so alternative methods are needed. This paper presents the design, convergence proofs and experimental validation of an adaptive feedforward controller that significantly improves the performance in loading transients. First the control concept...

  12. 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.

  13. Robust Adaptive Integral Backstepping Control of a 3-DOF Helicopter

    Directory of Open Access Journals (Sweden)

    Zheng Fang

    2012-09-01

    Full Text Available Unmanned aerial vehicles have enormous potential applications in military and civil fields. A Quanser's 3-DOF helicopter is a simplified and benchmark experimental model for validating the effectiveness of various flight control algorithms. The attitude control of the 3-DOF helicopter is a challenging task since the helicopter is an under-actuated system with strong coupling and model uncertainty characteristics. In this paper, an adaptive integral backstepping algorithm is proposed to realize robust control of the 3-DOF helicopter. The proposed control algorithm can estimate model uncertainties online and improve the robustness of the control system. Simulation and experiment results demonstrate that the proposed algorithm performs well in tracking and under model uncertainties.

  14. Frequency Adaptability of Harmonics Controllers for Grid-Interfaced Converters

    DEFF Research Database (Denmark)

    Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede

    2017-01-01

    A wider spread adoption of power electronic converters interfaced renewable energy systems has brought more attention to harmonic issues to the electrical grid, and means are taken to improve it in the control. More advanced closed-loop harmonic controllers are thus demanded to enhance...... the renewable energy integration in order to be grid-friendly. However, usually being treated as a constant factor in the design of harmonic controllers, the grid frequency varies with the generation-load imbalance, and thus may lead to deterioration of the power quality. This paper explores the frequency...... 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...

  15. Attitude and Altitude Control of Trirotor UAV by Using Adaptive Hybrid Controller

    Directory of Open Access Journals (Sweden)

    Zain Anwar Ali

    2016-01-01

    Full Text Available The paper presents an adaptive hybrid scheme which is based on fuzzy regulation, pole-placement, and tracking (RST control algorithm for controlling the attitude and altitude of trirotor UAV. The dynamic and kinematic model of Unmanned Aerial Vehicle (UAV is unstable and nonlinear in nature with 6 degrees of freedom (DOF; that is why the stabilization of aerial vehicle is a difficult task. To stabilize the nonlinear behavior of our UAV, an adaptive hybrid controller algorithm is used, in which RST controller tuning is performed by adaptive gains of fuzzy logic controller. Simulated results show that fuzzy based RST controller gives better robustness as compared to the classical RST controller.

  16. Flatness-based adaptive fuzzy control of chaotic finance dynamics

    Science.gov (United States)

    Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.

    2017-11-01

    A flatness-based adaptive fuzzy control is applied to the problem of stabilization of the dynamics of a chaotic finance system, describing interaction between the interest rate, the investment demand and the price exponent. By proving that the system is differentially flat and by applying differential flatness diffeomorphisms, its transformation to the linear canonical (Brunovsky) is performed. For the latter description of the system, the design of a stabilizing state feedback controller becomes possible. A first problem in the design of such a controller is that the dynamic model of the finance system is unknown and thus it has to be identified with the use neurofuzzy approximators. The estimated dynamics provided by the approximators is used in the computation of the control input, thus establishing an indirect adaptive control scheme. The learning rate of the approximators is chosen from the requirement the system's Lyapunov function to have always a negative first-order derivative. Another problem that has to be dealt with is that the control loop is implemented only with the use of output feedback. To estimate the non-measurable state vector elements of the finance system, a state observer is implemented in the control loop. The computation of the feedback control signal requires the solution of two algebraic Riccati equations at each iteration of the control algorithm. Lyapunov stability analysis demonstrates first that an H-infinity tracking performance criterion is satisfied. This signifies elevated robustness against modelling errors and external perturbations. Moreover, the global asymptotic stability is proven for the control loop.

  17. Driver's behavioral adaptation to adaptive cruise control (ACC): the case of speed and time headway.

    Science.gov (United States)

    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.

  18. Incremental Adaptive Fuzzy Control for Sensorless Stroke Control of A Halbach-type Linear Oscillatory Motor

    Science.gov (United States)

    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.

  19. Adaptive Particle Swarm Optimizer with Varying Acceleration Coefficients for Finding the Most Stable Conformer of Small Molecules.

    Science.gov (United States)

    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.

  20. 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)

  1. 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.

  2. Surface treatment of silica nanoparticles for stable and charge-controlled colloidal silica

    Science.gov (United States)

    Kim, Kyoung-Min; Kim, Hye Min; Lee, Won-Jae; Lee, Chang-Woo; Kim, Tae-il; Lee, Jong-Kwon; Jeong, Jayoung; Paek, Seung-Min; Oh, Jae-Min

    2014-01-01

    An attempt was made to control the surface charge of colloidal silica nanoparticles with 20 nm and 100 nm diameters. Untreated silica nanoparticles were determined to be highly negatively charged and have stable hydrodynamic sizes in a wide pH range. To change the surface to a positively charged form, various coating agents, such as amine containing molecules, multivalent metal cation, or amino acids, were used to treat the colloidal silica nanoparticles. Molecules with chelating amine sites were determined to have high affinity with the silica surface to make agglomerations or gel-like networks. Amino acid coatings resulted in relatively stable silica colloids with a modified surface charge. Three amino acid moiety coatings (L-serine, L-histidine, and L-arginine) exhibited surface charge modifying efficacy of L-histidine > L-arginine > L-serine and hydrodynamic size preservation efficacy of L-serine > L-arginine > L-histidine. The time dependent change in L-arginine coated colloidal silica was investigated by measuring the pattern of the backscattered light in a Turbiscan™. The results indicated that both the 20 nm and 100 nm L-arginine coated silica samples were fairly stable in terms of colloidal homogeneity, showing only slight coalescence and sedimentation. PMID:25565824

  3. Chaos control and generalized projective synchronization of heavy symmetric chaotic gyroscope systems via Gaussian radial basis adaptive variable structure control

    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

  4. Combined MIMO adaptive and decentralized controllers for broadband active noise and vibration control

    NARCIS (Netherlands)

    Berkhoff, Arthur P.; Wesselink, J.M.

    2011-01-01

    Model errors in multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. In this paper, a combination of high-authority control(HAC)and low-authority control (LAC)is considered for improved

  5. Planar jumping with stable landing through foot orientation design and ankle joint control

    Science.gov (United States)

    Yuan, Qilong; Chen, I.-Ming

    2012-06-01

    This paper introduces a method to generate the planar jumping motion for biped robot. In this work, through determining the upper body posture trajectory in the flight phase, the foot landing posture is made to be flat while landing. Together with properly designing the trajectory for local center of gravity and the foot landing velocity, the soft landing trajectory is generated. A controller on the ankle joint is added to avoid significant impact with the ground and stabilize the robot after landing. Jumping motion with stable landing is achieved in a dynamic simulation environment based on this method.

  6. Adaptive process control for three-point bending

    Science.gov (United States)

    Schaller, T.; Raggenbass, A.; Reissner, J.

    1995-08-01

    The increasing level of competition in the sheet-metal working industry requires measures to reduce costs. There is considerable potential in the simplification of process procedures. Automated handling and the further processing of bent semifinished products require a high level of manufacturing precision in bending processes. However deviations in angles of several degrees from the desired values can arise as a result of material variations within one batch. An adaptive control system is developed in order to avoid expensive further manufacturing steps. This calculates the parameters required for the correction of the process control from variations in process values measured online. These adjustment values must be communicated to the bending machine and set during the ongoing forming process. For larger series of parts the coefficients of the correction matrix are also continuously improved, so that an optimum adaptive correction can be achieved for the current scatter in the material properties. The adaptive correction procedure is particularly effective in combination with the three-point bending technology. The highest levels of angular precision can already be achieved after a short independent optimization phase. However, the current spectrum of parts for a certain manufacturing task and a defined quality requirement should provide the basis for decisions concerning the economy of this process arrangement.

  7. 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......The integration of renewable energy technology is making the power distribution system more flexible, but also introducing challenges for traditional technology. With the nature of intermittent and less inertial, renewable energy-based generations need effective control methods to cooperate...... with other devices, such as storage, loads and the utility grid. The widely used power frequency (P–f) droop control is based on the precondition of inductive line impedance, but the low-voltage system is mainly resistive, and also the different load character needs to be considered. This study presents...

  8. 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...

  9. Direct model reference adaptive control of robotic arms

    Science.gov (United States)

    Kaufman, Howard; Swift, David C.; Cummings, Steven T.; Shankey, Jeffrey R.

    1993-01-01

    The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.

  10. Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

    Science.gov (United States)

    Nguyen, Nhan T.

    2018-01-01

    Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

  11. Adaptive dynamic programming with applications in optimal control

    CERN Document Server

    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...

  12. Adaptive control for solar energy based DC microgrid system development

    Science.gov (United States)

    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.

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

    OpenAIRE

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

    2017-01-01

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

  14. Design and analysis of full range adaptive cruise control with integrated collision a voidance strategy

    NARCIS (Netherlands)

    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)

  15. Adaptive control of systems in cascade with saturation

    Science.gov (United States)

    Kannan, Suresh K.

    This thesis extends the use of neural-network-based model reference adaptive control to systems that occur as cascades. In general, these systems are not feedback linearizable. The approach taken is that of approximate feedback linearization of upper subsystems whilst treating the lower-subsystem states as virtual actuators. Similarly, lower-subsystems are also feedback linearized. Typically, approximate inverses are used for linearization purposes. Model error arising from the use of an approximate inverse is minimized using a neural-network as an adaptive element. Incorrect adaptation due to (virtual) actuator saturation and dynamics is avoided using the Pseudocontrol Hedging method. Using linear approximate inverses and linear reference models generally result in large desired pseudocontrol for large external commands. Even if the provided external command is feasible (null-controllable), there is no guarantee that the reference model trajectory is feasible. In order to mitigate this, nonlinear reference models based on nested-saturation methods are used to constrain the evolution of the reference model and thus the plant states. The method presented in this thesis lends itself to the inner-outer loop control of air vehicles, where the inner-loop controls attitude dynamics and the outer-loop controls the translational dynamics of the vehicle. The outer-loop treats the closed loop attitude dynamics as an actuator. Adaptation to uncertainty in the attitude, as well as the translational dynamics, is introduced, thus minimizing the effects of model error in all six degrees of freedom and leading to more accurate position tracking. A pole-placement approach is used to choose compensator gains for the tracking error dynamics. This alleviates timescale separation requirements, allowing the outer loop bandwidth to be closer to that of the inner loop, thus increasing position tracking performance. A poor model of the attitude dynamics and a basic kinematics model is

  16. Comparative proteomics of two life cycle stages of stable isotope-labeled Trypanosoma brucei reveals novel components of the parasite's host adaptation machinery.

    Science.gov (United States)

    Butter, Falk; Bucerius, Ferdinand; Michel, Margaux; Cicova, Zdenka; Mann, Matthias; Janzen, Christian J

    2013-01-01

    Trypanosoma brucei developed a sophisticated life cycle to adapt to different host environments. Although developmental differentiation of T. brucei has been the topic of intensive research for decades, the mechanisms responsible for adaptation to different host environments are not well understood. We developed stable isotope labeling by amino acids in cell culture in trypanosomes to compare the proteomes of two different life cycle stages. Quantitative comparison of 4364 protein groups identified many proteins previously not known to be stage-specifically expressed. The identification of stage-specific proteins helps to understand how parasites adapt to different hosts and provides new insights into differences in metabolism, gene regulation, and cell architecture. A DEAD-box RNA helicase, which is highly up-regulated in the bloodstream form of this parasite and which is essential for viability and proper cell cycle progression in this stage is described as an example.

  17. 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.

  18. 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.

  19. Adaptive neuro-fuzzy sliding mode control of multi-joint movement using intraspinal microstimulation.

    Science.gov (United States)

    Asadi, Ali-Reza; Erfanian, Abbas

    2012-07-01

    During the last decade, intraspinal microstimulation (ISMS) has been proposed as a potential technique for restoring motor function in paralyzed limbs. A major challenge to restoration of a desired functional limb movement through the use of ISMS is the development of a robust control strategy for determining the stimulation patterns. Accurate and stable control of limbs by functional intraspinal microstimulation is a very difficult task because neuromusculoskeletal systems have significant nonlinearity, time variability, large latency and time constant, and muscle fatigue. Furthermore, the controller must be able to compensate the effect of the dynamic interaction between motor neuron pools and electrode sites during ISMS. In this paper, we present a robust strategy for multi-joint control through ISMS in which the system parameters are adapted online and the controller requires no offline training phase. The method is based on the combination of sliding mode control with fuzzy logic and neural control. Extensive experiments on six rats are provided to demonstrate the robustness, stability, and tracking accuracy of the proposed method. Despite the complexity of the spinal neuronal networks, our results show that the proposed strategy could provide accurate tracking control with fast convergence and could generate control signals to compensate for the effects of muscle fatigue.

  20. A new adaptive configuration of PID type fuzzy logic controller.

    Science.gov (United States)

    Fereidouni, Alireza; Masoum, Mohammad A S; Moghbel, Moayed

    2015-05-01

    In this paper, an adaptive configuration for PID type fuzzy logic controller (FLC) is proposed to improve the performances of both conventional PID (C-PID) controller and conventional PID type FLC (C-PID-FLC). The proposed configuration is called adaptive because its output scaling factors (SFs) are dynamically tuned while the controller is functioning. The initial values of SFs are calculated based on its well-tuned counterpart while the proceeding values are generated using a proposed stochastic hybrid bacterial foraging particle swarm optimization (h-BF-PSO) algorithm. The performance of the proposed configuration is evaluated through extensive simulations for different operating conditions (changes in reference, load disturbance and noise signals). The results reveal that the proposed scheme performs significantly better over the C-PID controller and the C-PID-FLC in terms of several performance indices (integral absolute error (IAE), integral-of-time-multiplied absolute error (ITAE) and integral-of-time-multiplied squared error (ITSE)), overshoot and settling time for plants with and without dead time. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  1. An improved Direct Adaptive Fuzzy controller for an uncertain DC Motor Speed Control System

    OpenAIRE

    Chunjie Zhou; Shuang Huang; Quan Yin; Duc Cuong Quach

    2013-01-01

    In this paper, we present an improved Direct Adaptive Fuzzy (IDAF) controller applied to general control DC motor speed system. In particular, an IDAF algorithm is designed to control an uncertain DC motor speed to track a given reference signal. In fact, the quality of the control system depends significantly on the amount of fuzzy rules-fuzzy sets and the updating coefficient of the adaptive rule. This can be observed clearly by the system error when the reference input is constant and out ...

  2. Damping Force Tracking Control of MR Damper System Using a New Direct Adaptive Fuzzy Controller

    Directory of Open Access Journals (Sweden)

    Xuan Phu Do

    2015-01-01

    Full Text Available This paper presents a new direct adaptive fuzzy controller and its effectiveness is verified by investigating the damping force tracking control of magnetorheological (MR fluid based damper (MR damper in short system. In the formulation of the proposed controller, a model of interval type 2 fuzzy controller is combined with the direct adaptive control to achieve high performance in vibration control. In addition, H∞ (H infinity tracking technique is used in building a model of the direct adaptive fuzzy controller in which an enhanced iterative algorithm is combined with the fuzzy model. After establishing a closed-loop control structure to achieve high control performance, a cylindrical MR damper is adopted and damping force tracking results are obtained and discussed. In addition, in order to demonstrate the effectiveness of the proposed control strategy, two existing controllers are modified and tested for comparative work. It has been demonstrated from simulation and experiment that the proposed control scheme provides much better control performance in terms of damping force tracking error. This leads to excellent vibration control performance of the semiactive MR damper system associated with the proposed controller.

  3. Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.

    Science.gov (United States)

    Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip

    2015-05-01

    An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.

  4. Fault diagnosis and fault-tolerant control based on adaptive control approach

    CERN Document Server

    Shen, Qikun; Shi, Peng

    2017-01-01

    This book provides recent theoretical developments in and practical applications of fault diagnosis and fault tolerant control for complex dynamical systems, including uncertain systems, linear and nonlinear systems. Combining adaptive control technique with other control methodologies, it investigates the problems of fault diagnosis and fault tolerant control for uncertain dynamic systems with or without time delay. As such, the book provides readers a solid understanding of fault diagnosis and fault tolerant control based on adaptive control technology. Given its depth and breadth, it is well suited for undergraduate and graduate courses on linear system theory, nonlinear system theory, fault diagnosis and fault tolerant control techniques. Further, it can be used as a reference source for academic research on fault diagnosis and fault tolerant control, and for postgraduates in the field of control theory and engineering. .

  5. ER fluid applications to vibration control devices and an adaptive neural-net controller

    Science.gov (United States)

    Morishita, Shin; Ura, Tamaki

    1993-07-01

    Four applications of electrorheological (ER) fluid to vibration control actuators and an adaptive neural-net control system suitable for the controller of ER actuators are described: a shock absorber system for automobiles, a squeeze film damper bearing for rotational machines, a dynamic damper for multidegree-of-freedom structures, and a vibration isolator. An adaptive neural-net control system composed of a forward model network for structural identification and a controller network is introduced for the control system of these ER actuators. As an example study of intelligent vibration control systems, an experiment was performed in which the ER dynamic damper was attached to a beam structure and controlled by the present neural-net controller so that the vibration in several modes of the beam was reduced with a single dynamic damper.

  6. Environmental controls on stable isotopes of precipitation in Lanzhou, China: An enhanced network at city scale.

    Science.gov (United States)

    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.

  7. 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.

  8. Adaptive integral dynamic surface control of a hypersonic flight vehicle

    Science.gov (United States)

    Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick

    2015-07-01

    In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.

  9. 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

  10. Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

    Science.gov (United States)

    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.

  11. Fuzzy Adaptive Control for Trajectory Tracking of Autonomous Underwater Vehicle

    Directory of Open Access Journals (Sweden)

    Saeed Nakhkoob

    2014-01-01

    Full Text Available In this paper, the problem of the position and attitude tracking of an autonomous underwater vehicle (AUV in the horizontal plane, under the presence of ocean current disturbances is discussed. The effect of the gradual variation of the parameters is taken into account. The effectiveness of the adaptive controller is compared with a feedback linearization method and fuzzy gain control approach. The proposed strategy has been tested through simulations. Also, the performance of the propos-ed method is compared with other strategies given in some other studies. The boundedness and asymptotic converge-nce properties of the control algorithm and its semi-global stability are analytically proven using Lyapunov stability theory and Barbalat’s lemma.

  12. Nonlinear vibration with control for flexible and adaptive structures

    CERN Document Server

    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 ...

  13. ADEX optimized adaptive controllers and systems from research to industrial practice

    CERN Document Server

    Martín-Sánchez, Juan M

    2015-01-01

    This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...

  14. Adaptive-passive vibration control systems for industrial applications

    Science.gov (United States)

    Mayer, D.; Pfeiffer, T.; Vrbata, J.; Melz, T.

    2015-04-01

    Tuned vibration absorbers have become common for passive vibration reduction in many industrial applications. Lightly damped absorbers (also called neutralizers) can be used to suppress narrowband disturbances by tuning them to the excitation frequency. If the resonance is adapted in-operation, the performance of those devices can be significantly enhanced, or inertial mass can be decreased. However, the integration of actuators, sensors and control electronics into the system raises new design challenges. In this work, the development of adaptive-passive systems for vibration reduction at an industrial scale is presented. As an example, vibration reduction of a ship engine was studied in a full scale test. Simulations were used to study the feasibility and evaluate the system concept at an early stage. Several ways to adjust the resonance of the neutralizer were evaluated, including piezoelectric actuation and common mechatronic drives. Prototypes were implemented and tested. Since vibration absorbers suffer from high dynamic loads, reliability tests were used to assess the long-term behavior under operational conditions and to improve the components. It was proved that the adaptive systems are capable to withstand the mechanical loads in an industrial application. Also a control strategy had to be implemented in order to track the excitation frequency. The most mature concepts were integrated into the full scale test. An imbalance exciter was used to simulate the engine vibrations at a realistic level experimentally. The neutralizers were tested at varying excitation frequencies to evaluate the tracking capabilities of the control system. It was proved that a significant vibration reduction is possible.

  15. Optimal Pid Controller Design Using Adaptive Vurpso Algorithm

    Science.gov (United States)

    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.

  16. 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......-changing environmental energy sources. In this paper, we present an improved and extended version of ODMAC and we analyze it by means of an analytical model that can approximate several performance metrics in an arbitrary network topology. The simulations and the analytical experiments show ODMAC's ability to satisfy...

  17. Adaptive learning in a compartmental model of visual cortex - how feedback enables stable category learning and refinement

    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

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

    OpenAIRE

    METİN, Muzaffer; GÜÇLÜ, Rahmi

    2014-01-01

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

  19. Adaptive fuzzy neural network control design via a T-S fuzzy model for a robot manipulator including actuator dynamics.

    Science.gov (United States)

    Wai, Rong-Jong; Yang, Zhi-Wei

    2008-10-01

    This paper focuses on the development of adaptive fuzzy neural network control (AFNNC), including indirect and direct frameworks for an n-link robot manipulator, to achieve high-precision position tracking. In general, it is difficult to adopt a model-based design to achieve this control objective due to the uncertainties in practical applications, such as friction forces, external disturbances, and parameter variations. In order to cope with this problem, an indirect AFNNC (IAFNNC) scheme and a direct AFNNC (DAFNNC) strategy are investigated without the requirement of prior system information. In these model-free control topologies, a continuous-time Takagi-Sugeno (T-S) dynamic fuzzy model with online learning ability is constructed to represent the system dynamics of an n-link robot manipulator. In the IAFNNC, an FNN estimator is designed to tune the nonlinear dynamic function vector in fuzzy local models, and then, the estimative vector is used to indirectly develop a stable IAFNNC law. In the DAFNNC, an FNN controller is directly designed to imitate a predetermined model-based stabilizing control law, and then, the stable control performance can be achieved by only using joint position information. All the IAFNNC and DAFNNC laws and the corresponding adaptive tuning algorithms for FNN weights are established in the sense of Lyapunov stability analyses to ensure the stable control performance. Numerical simulations and experimental results of a two-link robot manipulator actuated by dc servomotors are given to verify the effectiveness and robustness of the proposed methodologies. In addition, the superiority of the proposed control schemes is indicated in comparison with proportional-differential control, fuzzy-model-based control, T-S-type FNN control, and robust neural fuzzy network control systems.

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

    Science.gov (United States)

    Xiao, Nan; Gao, Wei; Song, Zongxi

    2017-10-01

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

  1. Patterns and controls of seasonal variability of carbon stable isotopes of particulate organic matter in lakes.

    Science.gov (United States)

    Gu, Binhe; Schelske, Claire L; Waters, Matthew N

    2011-04-01

    Carbon stable isotopes (δ(13)C) of particulate organic matter (POM) have been used as indicators for energy flow, primary productivity and carbon dioxide concentration in individual lakes. Here, we provide a synthesis of literature data from 32 freshwater lakes around the world to assess the variability of δ(13)C(POM) along latitudinal, morphometric and biogeochemical gradients. Seasonal mean δ(13)C(POM), a temporally integrated measure of the δ(13)C(POM), displayed weak relationships with all trophic state indices [total phosphorus (TP), total nitrogen (TN), and chlorophyll a (Chl a)], but decreased significantly with the increase in latitude, presumably in response to the corresponding decrease in water temperature and increase in CO(2) concentration. The seasonal minimum δ(13)C(POM) also correlated negatively with latitude while seasonal maximum δ(13)C(POM) correlated positively with all trophic state indices, pH, and δ(13)C of dissolved inorganic carbon (DIC). Seasonal amplitude of δ(13)C(POM) (the difference between seasonal maximum and minimum values) correlated significantly with pH, TP and Chl a concentrations and displayed small variations in oligotrophic, mesotrophic and low latitude eutrophic lakes, which is attributed to low primary productivity and abundant non-living POM in the low trophic state lakes and relatively stable environmental conditions in the subtropics. Seasonal amplitude of δ(13)C(POM) was the greatest in high latitude eutrophic lakes. Greater seasonal changes in solar energy and light regime may be responsible for the large seasonal variability in high latitude productive lakes. This synthesis provides new insights on the factors controlling variations in stable carbon isotopes of POM among lakes on the global scale.

  2. A model predictive control approach to design a parameterized adaptive cruise control

    NARCIS (Netherlands)

    Naus, G.J.L.; Ploeg, J.; Molengraft, M.J.G. van de; Heemels, W.P.M.H.; Steinbuch, M.

    2010-01-01

    The combination of different desirable characteristics and situation-dependent behavior cause the design of adaptive cruise control (ACC) systems to be time consuming and tedious. This chapter presents a systematic approach for the design and tuning of an ACC, based on model predictive control

  3. Design and implementation of parameterized adaptive cruise control: An explicit model predictive control approach

    NARCIS (Netherlands)

    Naus, G.J.L.; Ploeg, J.; Molengraft, M.J.G. van de; Heemels, W.P.M.H.; Steinbuch, M.

    2010-01-01

    The combination of different characteristics and situation-dependent behavior cause the design of adaptive cruise control (ACC) systems to be time consuming. This paper presents a systematic approach for the design of a parameterized ACC, based on explicit model predictive control. A unique feature

  4. 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)

  5. 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)

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

    Directory of Open Access Journals (Sweden)

    Baghdad BELABES

    2008-12-01

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

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

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin

    2013-01-01

    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...... that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines....

  8. Adaptive fuzzy control of neutron power of the TRIGA Mark III reactor; Control difuso adaptable de la potencia neutronica del reactor Triga Mark III

    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)

  9. Mechanisms controlling the carbon stable isotope composition of phytoplankton in karst reservoirs

    Directory of Open Access Journals (Sweden)

    Baoli Wang

    2013-02-01

    Full Text Available In order to systematically understand the mechanisms controlling the carbon stable isotope composition of phytoplankton (δ13CPHYin freshwater ecosystems, seasonal changes in δ13CPHY and related environmental factors were determined in karst reservoirs from the Wujiang river basin, China. Substantial and systematic differences within seasons and reservoirs were observed for δ13CPHY, which ranged from -39.2‰ to -15.1‰. An increase in water temperature triggered fast growth of phytoplankton which assimilated more dissolved inorganic carbon (DIC, resulting in the increase of δ13CPHY, δ13CDIC and pH. When the concentration of dissolved carbon dioxide (CO2 was less than 10 mmol L–1, phytoplankton shifted to using HCO3– as a carbon source. This resulted in the sharp increase of δ13CPHY. The carbon stable isotope composition of phytoplankton tended to decrease with the increase of Bacillariophyta, which dominated in January and April, but tended to increase with the increase of Chlorophyta and Dinophyta, which dominated in July. Multiple regression equations suggested that the influence of biological factors such as taxonomic difference on δ13CPHY could be equal or more important than that of physical and chemical factors. Thus, the effect of taxonomic differences on δ13CPHY must be considered when explaining the δ13C of organic matter in lacustrine ecosystem.

  10. Wire rope tension control of hoisting systems using a robust nonlinear adaptive backstepping control scheme.

    Science.gov (United States)

    Zhu, Zhen-Cai; Li, Xiang; Shen, Gang; Zhu, Wei-Dong

    2018-01-01

    This paper concerns wire rope tension control of a double-rope winding hoisting system (DRWHS), which consists of a hoisting system employed to realize a transportation function and an electro-hydraulic servo system utilized to adjust wire rope tensions. A dynamic model of the DRWHS is developed in which parameter uncertainties and external disturbances are considered. A comparison between simulation results using the dynamic model and experimental results using a double-rope winding hoisting experimental system is given in order to demonstrate accuracy of the dynamic model. In order to improve the wire rope tension coordination control performance of the DRWHS, a robust nonlinear adaptive backstepping controller (RNABC) combined with a nonlinear disturbance observer (NDO) is proposed. Main features of the proposed combined controller are: (1) using the RNABC to adjust wire rope tensions with consideration of parameter uncertainties, whose parameters are designed online by adaptive laws derived from Lyapunov stability theory to guarantee the control performance and stability of the closed-loop system; and (2) introducing the NDO to deal with uncertain external disturbances. In order to demonstrate feasibility and effectiveness of the proposed controller, experimental studies have been conducted on the DRWHS controlled by an xPC rapid prototyping system. Experimental results verify that the proposed controller exhibits excellent performance on wire rope tension coordination control compared with a conventional proportional-integral (PI) controller and adaptive backstepping controller. Copyright © 2017 ISA. All rights reserved.

  11. Kalman filtering to suppress spurious signals in Adaptive Optics control

    Energy Technology Data Exchange (ETDEWEB)

    Poyneer, L; Veran, J P

    2010-03-29

    In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.

  12. The Adaptive Neural Network Control of Quadrotor Helicopter

    Directory of Open Access Journals (Sweden)

    A. S. Yushenko

    2017-01-01

    Output” system approximating the control signal for the system motion in the immediate vicinity of the sliding surface. The auxiliary neural network approximates the corrective control signal required to smooth out the high-frequency jitter effect near the sliding surface.In the course of the study a quad-copter model was designed in the MATLAB environment according to the dynamic equations as well as a controller for three angles (roll, pitch and yaw. The controller consists of a neural network for approximating the main control signals and three neural networks for approximating corrective control signals (one per the axis. Environmental perturbations are involved in model.Based on the system behavior simulation the effectiveness of the proposed control method is shown. Each of the orientation angles (roll, pitch and yaw follows the desired trajectory with high accuracy. The stability of the system motion in the sliding surface vicinity is proved by Lyapunov method. The simulation results of the neural network controller and a quad-copter dynamic model in the MATLAB environment allow us to draw conclusion that the proposed control method ensures the stable motion along a given trajectory even despite environmental perturbations.

  13. On-line, adaptive state estimator for active noise control

    Science.gov (United States)

    Lim, Tae W.

    1994-01-01

    Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control

  14. Development of adaptive sensorimotor control in infant sitting posture.

    Science.gov (United States)

    Chen, Li-Chiou; Jeka, John; Clark, Jane E

    2016-03-01

    A reliable and adaptive relationship between action and perception is necessary for postural control. Our understanding of how this adaptive sensorimotor control develops during infancy is very limited. This study examines the dynamic visual-postural relationship during early development. Twenty healthy infants were divided into 4 developmental groups (each n=5): sitting onset, standing alone, walking onset, and 1-year post-walking. During the experiment, the infant sat independently in a virtual moving-room in which anterior-posterior oscillations of visual motion were presented using a sum-of-sines technique with five input frequencies (from 0.12 to 1.24 Hz). Infants were tested in five conditions that varied in the amplitude of visual motion (from 0 to 8.64 cm). Gain and phase responses of infants' postural sway were analyzed. Our results showed that infants, from a few months post-sitting to 1 year post-walking, were able to control their sitting posture in response to various frequency and amplitude properties of the visual motion. Infants showed an adult-like inverted-U pattern for the frequency response to visual inputs with the highest gain at 0.52 and 0.76 Hz. As the visual motion amplitude increased, the gain response decreased. For the phase response, an adult-like frequency-dependent pattern was observed in all amplitude conditions for the experienced walkers. Newly sitting infants, however, showed variable postural behavior and did not systemically respond to the visual stimulus. Our results suggest that visual-postural entrainment and sensory re-weighting are fundamental processes that are present after a few months post sitting. Sensorimotor refinement during early postural development may result from the interactions of improved self-motion control and enhanced perceptual abilities. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Adaptive control of camera position for stereo vision

    Science.gov (United States)

    Crisman, Jill D.; Cleary, Michael E.

    1994-03-01

    A major problem in using two-camera stereo machine vision to perform real-world tasks, such as visual object tracking, is deciding where to position the cameras. Humans accomplish the analogous task by positioning their heads and eyes for optimal stereo effects. This paper describes recent work toward developing automated control strategies for camera motion in stereo machine vision systems for mobile robot navigation. Our goal is to achieve fast, reliable pursuit of a target while avoiding obstacles. Our strategy results in smooth, stable camera motion despite robot and target motion. Our algorithm has been shown to be successful at navigating a mobile robot, mediating visual target tracking and ultrasonic obstacle detection. The architecture, hardware, and simulation results are discussed.

  16. The effect of massage on neonatal jaundice in stable preterm newborn infants: a randomized controlled trial.

    Science.gov (United States)

    Basiri-Moghadam, Mahdi; Basiri-Moghadam, Kokab; Kianmehr, Mojtaba; Jani, Somaye

    2015-06-01

    To evaluate the effects of massage therapy on transcutaneous bilirubin of stable preterm infants. The controlled clinical trial was conducted in 2014 at Shahid Hasheminejhad Hospital, Iran, and comprised preterm neonatal children in the neonatal intensive care unit. The newborns were divided into two groups of massage and control via random allocation. The children in the control group received the routine therapy whereas those in the massage group underwent the same four days of routine plus 20 minutes of massage twice a day. The transcutaneous bilirubin and the number of excretions of the newborns were noted from the first to the fourth day of the intervention and results were compared between the two groups. There were 40 newborns in the study l 20(50%) each in the two groups. There was a significant difference in the number of times of defecation (p=0.002) and in the level of bilirubin (p=0.003) between the groups with those in the massage group having a higher number of defecations as well as a lower level of transcutaneous bilirubin. Through massage therapy the bilirubin level in preterm newborns can be controlled and a need for phototherapy can also be delayed.

  17. 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.

  18. Passification based simple adaptive control of quadrotor attitude: Algorithms and testbed results

    Science.gov (United States)

    Tomashevich, Stanislav; Belyavskyi, Andrey; Andrievsky, Boris

    2017-01-01

    In the paper, the results of the Passification Method with the Implicit Reference Model (IRM) approach are applied for designing the simple adaptive controller for quadrotor attitude. The IRM design technique makes it possible to relax the matching condition, known for habitual MRAC systems, and leads to simple adaptive controllers, ensuring fast tuning the controller gains, high robustness with respect to nonlinearities in the control loop, to the external disturbances and the unmodeled plant dynamics. For experimental evaluation of the adaptive systems performance, the 2DOF laboratory setup has been created. The testbed allows to safely test new control algorithms in the laboratory area with a small space and promptly make changes in cases of failure. The testing results of simple adaptive control of quadrotor attitude are presented, demonstrating efficacy of the applied simple adaptive control method. The experiments demonstrate good performance quality and high adaptation rate of the simple adaptive control system.

  19. Design of an adaptive controller for dive-plane control of a torpedo-shaped AUV

    Science.gov (United States)

    Cao, Jian; Su, Yumin; Zhao, Jinxin

    2011-09-01

    Underwater vehicles operating in complex ocean conditions present difficulties in determining accurate dynamic models. To guarantee robustness against parameter uncertainty, an adaptive controller for dive-plane control, based on Lyapunov theory and back-stepping techniques, was proposed. In the closed-loop system, asymptotic tracking of the reference depth and pitch angle trajectories was accomplished. Simulation results were presented which show effective dive-plane control in spite of the uncertainties in the system parameters.

  20. IPMSM velocity and current control using MTPA based adaptive fractional order sliding mode controller

    Directory of Open Access Journals (Sweden)

    Sayed Hamed Hosseini

    2017-06-01

    Full Text Available This paper presents a two-loop approach for velocity and stator currents control of an Interior-type Permanent Magnet Synchronous Motor (IPMSM. In the outer loop, the reference torque obtained from a conventional PI controller gives two-axis stator reference currents based on Maximum-Torque per Ampere (MTPA strategy. In the inner loop, an adaptive fractional order sliding mode controller is designed to reach the two-axis stator currents to their reference values obtained from the MTPA method. To achieve this idea, fractional order sliding surfaces and an adaptive controller with adjustable parameters are employed. The adaptive controller is designed to increase the robustness of the proposed method against the uncertainties in stator resistance and inductances. A Lyapunov based adaptation mechanism is proposed for adjustment of the controller parameters. The optimal value of the fractional orders are obtained by optimization of an integral time absolute error performance index. The simulation results show the robustness of the proposed method against the uncertainties in stator resistance and stator inductances.

  1. Proinsulin is stable at room temperature for 24 hours in EDTA: A clinical laboratory analysis (adAPT 3.

    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.

  2. Decentralized adaptive sliding mode control of a space robot actuated by control moment gyroscopes

    Directory of Open Access Journals (Sweden)

    Jia Yinghong

    2016-06-01

    Full Text Available An adaptive sliding mode control (ASMC law is proposed in decentralized scheme for trajectory tracking control of a new concept space robot. Each joint of the system is a free ball joint capable of rotating with three degrees of freedom (DOF. A cluster of control moment gyroscopes (CMGs is mounted on each link and the base to actuate the system. The modified Rodrigues parameters (MRPs are employed to describe the angular displacements, and the equations of motion are derived using Kane’s equations. The controller for each link or the base is designed separately in decentralized scheme. The unknown disturbances, inertia parameter uncertainties and nonlinear uncertainties are classified as a “lumped” matched uncertainty with unknown upper bound, and a continuous sliding mode control (SMC law is proposed, in which the control gain is tuned by the improved adaptation laws for the upper bound on norm of the uncertainty. A general amplification function is designed and incorporated in the adaptation laws to reduce the control error without conspicuously increasing the magnitude of the control input. Uniformly ultimate boundedness of the closed loop system is proved by Lyapunov’s method. Simulation results based on a three-link system verify the effectiveness of the proposed controller.

  3. A robust adaptive load frequency control for micro-grids.

    Science.gov (United States)

    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.

  4. New hybrid adaptive neuro-fuzzy algorithms for manipulator control with uncertainties- comparative study.

    Science.gov (United States)

    Alavandar, Srinivasan; Nigam, M J

    2009-10-01

    Control of an industrial robot includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. In this paper, some new hybrid adaptive neuro-fuzzy control algorithms (ANFIS) have been proposed for manipulator control with uncertainties. These hybrid controllers consist of adaptive neuro-fuzzy controllers and conventional controllers. The outputs of these controllers are applied to produce the final actuation signal based on current position and velocity errors. Numerical simulation using the dynamic model of six DOF puma robot arm with uncertainties shows the effectiveness of the approach in trajectory tracking problems. Performance indices of RMS error, maximum error are used for comparison. It is observed that the hybrid adaptive neuro-fuzzy controllers perform better than only conventional/adaptive controllers and in particular hybrid controller structure consisting of adaptive neuro-fuzzy controller and critically damped inverse dynamics controller.

  5. Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton

    Science.gov (United States)

    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

  6. A randomized controlled trial of acupuncture in stable ischemic heart disease patients.

    Science.gov (United States)

    Mehta, Puja K; Polk, Donna M; Zhang, Xiao; Li, Ning; Painovich, Jeannette; Kothawade, Kamlesh; Kirschner, Joan; Qiao, Yi; Ma, Xiuling; Chen, Yii-Der Ida; Brantman, Anna; Shufelt, Chrisandra; Minissian, Margo; Merz, C Noel Bairey

    2014-09-20

    Heart rate variability (HRV) is reduced in stable ischemic heart disease (SIHD) patients and is associated with sudden cardiac death (SCD). We evaluated the impact of traditional acupuncture (TA) on cardiac autonomic function measured by HRV in SIHD patients. We conducted a randomized controlled study of TA, sham acupuncture (SA), and waiting control (WC) in 151 SIHD subjects. The TA group received needle insertion at acupuncture sites, the SA group received a sham at non-acupuncture sites, while the WC group received nothing. The TA and SA groups received 3 treatments/week for 12 weeks. 24-Hour, mental arithmetic stress, and cold pressor (COP) HRV was collected at entry and exit, along with BP, lipids, insulin resistance, hs-CRP, salivary cortisol, peripheral endothelial function by tonometry (PAT), and psychosocial variables. Mean age was 63 ± 10; 50% had prior myocardial infarction. Comparison of WC and SA groups demonstrated differences consistent with the unblinded WC status; therefore by design, the control groups were not merged. Exit mental stress HRV was higher in TA vs. SA for markers of parasympathetic tone (p ≤ 0.025), including a 17% higher vagal activity (p=0.008). There were no differences in exit 24-hour or COP HRV, BP, lipids, insulin resistance, hs-CRP, salivary cortisol, PAT, or psychosocial variables. TA results in intermediate effects on autonomic function in SIHD patients. TA effect on HRV may be clinically relevant and should be explored further. These data document feasibility and provide sample size estimation for a clinical trial of TA in SIHD patients for the prevention of SCD. We conducted a randomized, single-blind trial of traditional acupuncture (TA) vs. sham acupuncture (SA) vs waiting control (WC) in stable ischemic heart disease (SIHD) patients to evaluate cardiac autonomic function measured by heart rate variability (HRV). Exit mental stress HRV was higher in the TA compared to SA group for time and frequency domain markers of

  7. Experimental study on direct adaptive control of a PUMA 560 industrial robot

    Science.gov (United States)

    Seraji, H.; Lee, T.; Delpech, M.

    1990-01-01

    The implementation and experimental validation of a direct adaptive control scheme on a PUMA 560 industrial robot is discussed. The design theory for direct adaptive control of manipulators is outlined and the test facility and software are described. Results are presented from the experiments on the simultaneous control of all of the six joint angles and control of the end-effector position and orientation of the robot. Also, the possible applications of the direct adaptive control scheme are considered.

  8. 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

  9. 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...

  10. Flight Validation of a Metrics Driven L(sub 1) Adaptive Control

    Science.gov (United States)

    Dobrokhodov, Vladimir; Kitsios, Ioannis; Kaminer, Isaac; Jones, Kevin D.; Xargay, Enric; Hovakimyan, Naira; Cao, Chengyu; Lizarraga, Mariano I.; Gregory, Irene M.

    2008-01-01

    The paper addresses initial steps involved in the development and flight implementation of new metrics driven L1 adaptive flight control system. The work concentrates on (i) definition of appropriate control driven metrics that account for the control surface failures; (ii) tailoring recently developed L1 adaptive controller to the design of adaptive flight control systems that explicitly address these metrics in the presence of control surface failures and dynamic changes under adverse flight conditions; (iii) development of a flight control system for implementation of the resulting algorithms onboard of small UAV; and (iv) conducting a comprehensive flight test program that demonstrates performance of the developed adaptive control algorithms in the presence of failures. As the initial milestone the paper concentrates on the adaptive flight system setup and initial efforts addressing the ability of a commercial off-the-shelf AP with and without adaptive augmentation to recover from control surface failures.

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

    Directory of Open Access Journals (Sweden)

    Taochang Li

    2014-01-01

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

  12. Insufficient control of heart rate in stable coronary artery disease patients in Latvia.

    Science.gov (United States)

    Balode, Inga; Mintāle, Iveta; Latkovskis, Gustavs; Jēgere, Sanda; Narbute, Inga; Bajāre, Iveta; Greenlaw, Nicola; Steg, Philippe Gabriel; Ferrari, Roberto; Ērglis, Andrejs

    2014-01-01

    Heart rate (HR) ≥70 beats per minute (bpm) increases cardiovascular risk in coronary artery disease (CAD) patients. The objective of the analysis is to characterize HR as well as other clinical parameters in outpatients with stable CAD in Latvia. CLARIFY is an ongoing international registry of outpatients with established CAD. Latvian data regarding 120 patients enrolled in CLARIFY and collected at baseline visit during 2009-2010 were analyzed. The mean HR was 67.7±9.5 and 66.9±10.7bpm when measured by pulse palpation and electrocardiography, respectively. HR ≤60bpm and ≥70bpm was observed in 25% and 35.8% of patients, respectively. When analyzing patients with angina symptoms, 22.8% had HR ≤60bpm while HR ≥70bpm was observed in 33.3% of the cases. HR ≥70bpm was observed in 36.2% of patients with symptoms of chronic heart failure. Beta-blockers were used in 81.7% of the patients. Metoprolol (long acting succinate), bisoprolol, nebivolol and carvedilol in average daily doses 63.8, 5.3, 4.5, and 10.4mg/d were used in 47, 37, 11 and 3 cases, respectively. Among patients with HR ≥70bpm 79.1% were using beta-blockers. Medications did not differ significantly between the three groups according to HR level (≤60, 61-69 and ≥70bpm). Despite the wide use of beta-blockers, HR is insufficiently controlled in the analyzed sample of stable CAD patients in Latvia. Target HR ≤60bpm is achieved only in 25% of the patients while more than one third have increased HR ≥70bpm. Copyright © 2014 Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  13. Climatic and physiological controls on the stable isotope composition of modern and ancient Cupressaceae

    Science.gov (United States)

    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

  14. Adaptive Algorithms for Active Noise and Vibration Control

    National Research Council Canada - National Science Library

    Bodson, Marc

    2000-01-01

    .... In particular, the extension of the method to adaptive echo cancellation was investigated. Progress was also made on adaptive algorithms for the rejection of periodic disturbances without measurement of the disturbance or of its...

  15. Rear-heavy car control by adaptive linear optimal preview

    Science.gov (United States)

    Thommyppillai, M.; Evangelou, S.; Sharp, R. S.

    2010-05-01

    Adaptive linear optimal preview control theory is applied to a simple but non-linear car model, with parameters chosen to make the rear axle saturate first in any quasi-steady manoeuvre. The tendency of such a car to spin above a critical speed, which is a function of its running state, causes control to be especially difficult when operating near to the limit of the rear-axle force system. As in previous work, trim states and optimal gains are computed off-line for a given speed and a full range of lateral accelerations. Gain-scheduling with interpolation over trims and gain sets is used to keep the control appropriate to the running conditions, as they change. Simulations of manoeuvres are used to test and demonstrate the system capability. It is shown that utilising the rear-axle lateral-slip ratio as the scheduling variable, in the case of this rear-heavy car, gives excellent tracking, even when the tyres are run close to full saturation. It is implied by this and previous work that the general case can be treated effectively by monitoring both front- and rear-axle slips and scheduling on a worst-case basis.

  16. 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.

  17. STDP with adaptive synaptic delay for robot navigation control

    Science.gov (United States)

    Arena, Paolo; Patané, Luca; Distefano, Francesco; Bucolo, Sebastiano; Aiello, Orazio

    2007-05-01

    In this work a biologically inspired network of spiking neurons is used for robot navigation control. The two tasks taken into account are obstacle avoidance and landmark-based navigation. The system learns the correlation among unconditioned stimuli (pre-wired sensors) and conditioned stimuli (high level sensors) through Spike Timing Dependent Plasticity (STDP). In order to improve the robot behaviours not only the synaptic weight but also the synaptic delay is subject to learning. Modulating the synaptic delay the robot is able to store the landmark position, like in a short time memory, and to use this information to smooth the turning actions prolonging the landmark effects also when it is no more visible. Simulations are carried out in a dynamic simulation environment and the robotic system considered is a cockroach-inspired hexapod robot. The locomotion signals are generated by a Central Pattern Generator and the spiking network is devoted to control the heading of the robot acting on the amplitude of the leg steps. Several scenarios have been proposed, for instance a T-shaped labyrinth, used in laboratory experiments with mice to demonstrate classical and operant conditioning, has been considered. Finally the proposed adaptive navigation control structure can be extended in a modular way to include other features detected by new sensors included in the correlation-based learning process.

  18. Extended Stable Boundary of LCL-Filtered Grid-Connected Inverter Based on An Improved Grid-Voltage Feedforward Control

    DEFF Research Database (Denmark)

    Lu, Minghui; Xin, Zhen; Wang, Xiongfei

    2016-01-01

    For the LCL-filtered grid-connected inverter, it has been reported that the digital time delays will narrow the stable region of current control loop when the inverter-side current is used for implementing the feedback control. A sufficient stable condition is that the filter resonance frequency....... Theoretical analysis is then provided to validate its feasibility and stability. Compared to other widely used active damping strategies, no extra sensors are needed because the filter capacitor voltage, which is used for voltage feedforward control, is also sampled for phase-locked loop in this paper...

  19. Design of Attitude Control System for UAV Based on Feedback Linearization and Adaptive Control

    Directory of Open Access Journals (Sweden)

    Wenya Zhou

    2014-01-01

    Full Text Available Attitude dynamic model of unmanned aerial vehicles (UAVs is multi-input multioutput (MIMO, strong coupling, and nonlinear. Model uncertainties and external gust disturbances should be considered during designing the attitude control system for UAVs. In this paper, feedback linearization and model reference adaptive control (MRAC are integrated to design the attitude control system for a fixed wing UAV. First of all, the complicated attitude dynamic model is decoupled into three single-input single-output (SISO channels by input-output feedback linearization. Secondly, the reference models are determined, respectively, according to the performance indexes of each channel. Subsequently, the adaptive control law is obtained using MRAC theory. In order to demonstrate the performance of attitude control system, the adaptive control law and the proportional-integral-derivative (PID control law are, respectively, used in the coupling nonlinear simulation model. Simulation results indicate that the system performance indexes including maximum overshoot, settling time (2% error range, and rise time obtained by MRAC are better than those by PID. Moreover, MRAC system has stronger robustness with respect to the model uncertainties and gust disturbance.

  20. Design of Smith-like Predictive Controller with Communication Delay Adaptation

    OpenAIRE

    Jasmin Velagic

    2008-01-01

    This paper addresses the design of predictive networked controller with adaptation of a communication delay. The networked control system contains random delays from sensor to controller and from controller to actuator. The proposed predictive controller includes an adaptation loop which decreases the influence of communication delay on the control performance. Also, the predictive controller contains a filter which improves the robustness of the control system. The perfo...

  1. Development of a stable positive control to be used for quality assurance of rapid diagnostic tests for malaria

    NARCIS (Netherlands)

    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

  2. Robust adaptive fuzzy neural tracking control for a class of unknown ...

    Indian Academy of Sciences (India)

    2School of Computer Science and Engineering, Xinjiang University of Finance and Economics,. Urumchi 830012 ... The fuzzy neural controller including a fuzzy neural network identifier (FNNI) is the principal controller. The FNNI is ... Keywords. Chaos control; adaptive control; adaptive identifier; fuzzy neural network; back-.

  3. Decentralized adaptive control of interconnected nonlinear systems with unknown control directions.

    Science.gov (United States)

    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.

  4. Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

    Science.gov (United States)

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

    2017-01-01

    This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

  5. Adaptive Backstepping Controller Design for Leveling Control of an Underwater Platform Based on Joint Space

    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.

  6. 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.

  7. 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.

  8. Water intake, faecal output and intestinal motility in horses moved from pasture to a stabled management regime with controlled exercise

    Science.gov (United States)

    Williams, S; Horner, J; Orton, E; Green, M; McMullen, S; Mobasheri, A; Freeman, S L

    2015-01-01

    Reasons for performing study A change in management from pasture to stabling is a risk factor for equine colic. Objectives To investigate the effect of a management change from pasture with no controlled exercise to stabling with light exercise on aspects of gastrointestinal function related to large colon impaction. The hypothesis was that drinking water intake, faecal output, faecal water content and large intestinal motility would be altered by a transition from a pastured to a stabled regime. Study design Within-subject management intervention trial involving changes in feeding and exercise using noninvasive techniques. Methods Seven normal horses were evaluated in a within-subjects study design. Horses were monitored while at pasture 24 h/day, and for 14 days following a transition to a stabling regime with light controlled exercise. Drinking water intake, faecal output and faecal dry matter were measured. Motility of the caecum, sternal flexure and left colon (contractions/min) were measured twice daily by transcutaneous ultrasound. Mean values were pooled for the pastured regime and used as a reference for comparison with stabled data (Days 1–14 post stabling) for multilevel statistical analysis. Results Drinking water intake was significantly increased (mean ± s.d. pasture 2.4 ± 1.8 vs. stabled 6.4 ± 0.6 l/100 kg bwt/day), total faecal output was significantly decreased (pasture 4.62 ± 1.69 vs. stabled 1.81 ± 0.5 kg/100 kg bwt/day) and faecal dry matter content was significantly increased (pasture 18.7 ± 2.28 vs. stabled 27.2 ± 1.93% DM/day) on all days post stabling compared with measurements taken at pasture (P<0.05). Motility was significantly decreased in all regions of the large colon collectively on Day 2 post stabling (-0.76 contractions/min), and in the left colon only on Day 4 (-0.62 contractions/min; P<0.05). Conclusions There were significant changes in large intestinal motility patterns and parameters relating to gastrointestinal water

  9. A robust adaptive load frequency control for micro-grids

    DEFF Research Database (Denmark)

    Khooban, Mohammad-Hassan; Niknam, Taher; Blaabjerg, Frede

    2016-01-01

    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...... 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...... 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...

  10. 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.

  11. 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

  12. Information-educational environment with adaptive control of learning process

    Science.gov (United States)

    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.

  13. Adaptive sliding mode control on inner axis for high precision flight motion simulator

    Science.gov (United States)

    Fu, Yongling; Niu, Jianjun; Wang, Yan

    2008-10-01

    Discrete adaptive sliding mode control (ASMC) with exponential reaching law is proposed to alleviate the influence of the factors such as the periodical fluctuation torque of motor, nonlinear friction, and other disturbance which will deteriorate the tracking performance of a DC torque motor driven inner axis for a high precision flight motion simulator, considering the limited compensating ability of the ASMC for these uncertainty, an equivalent friction advance compensator based on Stribeck model is also presented for extra-low speed servo of the system. Firstly, the way direct using the available parts of the inner axis itself to ascertain the parameters for Stribeck model is listed. Secondly, adaptive approach is used to overcome the difficulty of choice the key parameter for exponential reaching law, and the stability of the algorithm is analyzed. Lastly, comparable experiments are carried out to verify the valid of the combined approach. The experiments results show with a stable 0.00006°/s speed response, 95% of time the tracking error is within 0.0002°, other servos such as sine wave tracking are also with high precision.

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

    Science.gov (United States)

    Nguyen, Nhan

    2013-01-01

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

  15. Real-time control of geometry and stiffness in adaptive structures

    Science.gov (United States)

    Ramesh, A. V.; Utku, S.; Wada, B. K.

    1991-01-01

    The basic theory is presented for the geometry, stiffness, and damping control of adaptive structures, with emphasis on adaptive truss structures. Necessary and sufficient conditions are given for stress-free geometry control in statically determinate and indeterminate adaptive discrete structures. Two criteria for selecting the controls are proposed, and their use in real-time control is illustrated by numerical simulation results. It is shown that the stiffness and damping control of adaptive truss structures for vibration suppression is possible by elongation and elongation rate dependent feedback forces from the active elements.

  16. 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

  17. Atmospherically stable nanoscale zero-valent iron particles formed under controlled air contact: characteristics and reactivity.

    Science.gov (United States)

    Kim, Hong-Seok; Ahn, Jun-Young; Hwang, Kyung-Yup; Kim, Il-Kyu; Hwang, Inseong

    2010-03-01

    Atmospherically stable NZVI (nanoscale zero-valent iron) particles were produced by modifying shell layers of Fe(H2) NZVI particles (RNIP-10DS) by using a controlled air contact method. Shell-modified NZVI particles were resistant to rapid aerial oxidation and were shown to have TCE degradation rate constants that were equivalent to 78% of those of pristine NZVI particles. Fe(H2) NZVI particles that were vigorously contacted with air (rapidly oxidized) showed a substantially compromised reactivity. Aging of shell-modified particles in water for one day resulted in a rate increase of 54%, implying that depassivation of the shell would play an important role in enhancing reactivity. Aging of shell-modified particles in air led to rate decreases by 14% and 46% in cases of one week and two months of aging, respectively. A series of instrumental analyses using transmission electron microscopy, X-ray diffractography, X-ray photoelectron spectroscopy, and X-ray absorption near-edge structure showed that the shells of modified NZVI particles primarily consisted of magnetite (Fe(3)O(4)). Analyses also implied that the new magnetite layer produced during shell modification was protective against shell passivation. Aging of shell-modified particles in water yielded another major mineral phase, goethite (alpha-FeOOH), whereas aging in air produced additional shell phases such as wustite (FeO), hematite (alpha-Fe(2)O(3)), and maghemite (gamma-Fe(2)O(3)).

  18. Multivariable Control Law Design for the AFTI/F-16 with a Failed Control Surface Using a Parameter-Adaptive Controller.

    Science.gov (United States)

    1987-12-01

    R.. Parameter-Adaptive Control Algorithms - A Tutorial." Automatica. Vol 18. No. 5. 1982. pp 513-528. 12. Wittenmark. B.. and Karl J Astrom ...1.3.2 Adaptive Controls. Research into adaptive control was motivated in the 1950s by high performance aircraft requirements (10:471). Astrom stated...February 1985. N 0 *N 10. Astrom . K.J.. -Theory and Application of Adaptive Control- A Survey,- Automatica. Vol 19. NO. 5. 1983. pp 471-486. 11. Isermann

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

    Science.gov (United States)

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

    2014-01-01

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

  20. Adaptation

    International Development Research Centre (IDRC) Digital Library (Canada)

    . Dar es Salaam. Durban. Bloemfontein. Antananarivo. Cape Town. Ifrane ... program strategy. A number of CCAA-supported projects have relevance to other important adaptation-related themes such as disaster preparedness and climate.

  1. Computational Design of a pH Stable Enzyme: Understanding Molecular Mechanism of Penicillin Acylase's Adaptation to Alkaline Conditions

    Science.gov (United States)

    Suplatov, Dmitry; Panin, Nikolay; Kirilin, Evgeny; Shcherbakova, Tatyana; Kudryavtsev, Pavel; Švedas, Vytas

    2014-01-01

    Protein stability provides advantageous development of novel properties and can be crucial in affording tolerance to mutations that introduce functionally preferential phenotypes. Consequently, understanding the determining factors for protein stability is important for the study of structure-function relationship and design of novel protein functions. Thermal stability has been extensively studied in connection with practical application of biocatalysts. However, little work has been done to explore the mechanism of pH-dependent inactivation. In this study, bioinformatic analysis of the Ntn-hydrolase superfamily was performed to identify functionally important subfamily-specific positions in protein structures. Furthermore, the involvement of these positions in pH-induced inactivation was studied. The conformational mobility of penicillin acylase in Escherichia coli was analyzed through molecular modeling in neutral and alkaline conditions. Two functionally important subfamily-specific residues, Gluβ482 and Aspβ484, were found. Ionization of these residues at alkaline pH promoted the collapse of a buried network of stabilizing interactions that consequently disrupted the functional protein conformation. The subfamily-specific position Aspβ484 was selected as a hotspot for mutation to engineer enzyme variant tolerant to alkaline medium. The corresponding Dβ484N mutant was produced and showed 9-fold increase in stability at alkaline conditions. Bioinformatic analysis of subfamily-specific positions can be further explored to study mechanisms of protein inactivation and to design more stable variants for the engineering of homologous Ntn-hydrolases with improved catalytic properties. PMID:24959852

  2. Computational design of a pH stable enzyme: understanding molecular mechanism of penicillin acylase's adaptation to alkaline conditions.

    Directory of Open Access Journals (Sweden)

    Dmitry Suplatov

    Full Text Available Protein stability provides advantageous development of novel properties and can be crucial in affording tolerance to mutations that introduce functionally preferential phenotypes. Consequently, understanding the determining factors for protein stability is important for the study of structure-function relationship and design of novel protein functions. Thermal stability has been extensively studied in connection with practical application of biocatalysts. However, little work has been done to explore the mechanism of pH-dependent inactivation. In this study, bioinformatic analysis of the Ntn-hydrolase superfamily was performed to identify functionally important subfamily-specific positions in protein structures. Furthermore, the involvement of these positions in pH-induced inactivation was studied. The conformational mobility of penicillin acylase in Escherichia coli was analyzed through molecular modeling in neutral and alkaline conditions. Two functionally important subfamily-specific residues, Gluβ482 and Aspβ484, were found. Ionization of these residues at alkaline pH promoted the collapse of a buried network of stabilizing interactions that consequently disrupted the functional protein conformation. The subfamily-specific position Aspβ484 was selected as a hotspot for mutation to engineer enzyme variant tolerant to alkaline medium. The corresponding Dβ484N mutant was produced and showed 9-fold increase in stability at alkaline conditions. Bioinformatic analysis of subfamily-specific positions can be further explored to study mechanisms of protein inactivation and to design more stable variants for the engineering of homologous Ntn-hydrolases with improved catalytic properties.

  3. Optimized Aircraft Electric Control System Based on Adaptive Tabu Search Algorithm and Fuzzy Logic Control

    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.

  4. Adaptive Feed-Forward Control of Low Frequency Interior Noise

    CERN Document Server

    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.

  5. Adaptive, Distributed Control of Constrained Multi-Agent Systems

    Science.gov (United States)

    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.

  6. Control code for laboratory adaptive optics teaching system

    Science.gov (United States)

    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.

  7. Personal control over the cure of breast cancer : adaptiveness, underlying beliefs and correlates

    NARCIS (Netherlands)

    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

  8. Personal control over the cure of breast cancer: adaptiveness, underlying beliefs and correlates

    NARCIS (Netherlands)

    Henselmans, Inge; Sanderman, Robbert; Helgeson, Vicki S.; de Vries, Jakob; Smink, Ans; Ranchor, Adelita V.

    2010-01-01

    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

  9. An adaptive optimisation scheme for controlling air flow process with satisfactory transient performance

    Directory of Open Access Journals (Sweden)

    Sivakumar Dakshinamurthy

    2010-07-01

    Full Text Available A non-identifier-based adaptive PI controller is designed using a gradient approach to improve the performance of a control system when device aging and environmental factors degrade the efficiency of the process. The design approach is based on the model reference adaptive control technique. The controller drives the difference (error between the process response and desired model output to zero asymptotically at a rate constrained by the desired characteristics of the model. The tuning rules are designed and justified for a non-linear process with dominant dynamics of second order. The advantage of this method for tracking and regulation compared to adaptive MIT control was validated in real time by conducting experiments on a laboratory air flow control system using the dSPACE interface in the SIMULINK software. The experimental results show that the process with adaptive PI controller has better dynamic performance and robustness than that with traditional adaptive MIT controller.

  10. Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Tat-Bao-Thien Nguyen

    2014-01-01

    Full Text Available In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.

  11. 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.

  12. Adaptive formation control of quadrotor unmanned aerial vehicles with bounded control thrust

    Directory of Open Access Journals (Sweden)

    Rui Wang

    2017-04-01

    Full Text Available In this paper, the flight formation control problem of a group of quadrotor unmanned aerial vehicles (UAVs with parametric uncertainties and external disturbances is studied. Unit-quaternions are used to represent the attitudes of the quadrotor UAVs. Separating the model into a translational subsystem and a rotational subsystem, an intermediary control input is introduced to track a desired velocity and extract desired orientations. Then considering the internal parametric uncertainties and external disturbances of the quadrotor UAVs, the priori-bounded intermediary adaptive control input is designed for velocity tracking and formation keeping, by which the bounded control thrust and the desired orientation can be extracted. Thereafter, an adaptive control torque input is designed for the rotational subsystem to track the desired orientation. With the proposed control scheme, the desired velocity is tracked and a desired formation shape is built up. Global stability of the closed-loop system is proven via Lyapunov-based stability analysis. Numerical simulation results are presented to illustrate the effectiveness of the proposed control scheme.

  13. Adaptive observer for speed sensorless PM motor control

    DEFF Research Database (Denmark)

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

    2003-01-01

    This paper presents an adaptive observer for extimating the rotor position and speed of a permanent magnet synchronous motors (PMSM). The observer compensates for voltage offsets and permanent magnet strength variations. The adaptation structure for estimating the strength of the permanent magnet...

  14. The ADAPT design model : towards instructional control of transfer

    NARCIS (Netherlands)

    Jelsma, Otto; van Merrienboer, Jeroen J.G.; van Merrienboer, J.J.G.; Bijlstra, Jim P.; Bijlstra, J.P.

    1990-01-01

    This paper presents a detailed description of the ADAPT (Apply Delayed Automatization for Positive Transfer) design model. ADAPT is based upon production system models of learning and provides guidelines for developing instructional systems that offer transfer of leamed skills. The model suggests

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

    Directory of Open Access Journals (Sweden)

    Shun-Yuan Wang

    2015-03-01

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

  16. Adapt

    Science.gov (United States)

    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

  17. 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

  18. General and simple approach for control cage and cylindrical mesopores, and thermal/hydrothermal stable frameworks.

    Science.gov (United States)

    El-Safty, Sherif A; Mizukami, Fujio; Hanaoka, Takaaki

    2005-05-19

    Highly ordered cage and cylindrical mesoporeous silica monoliths (HOM) with 2- and 3-dimensional (2D and 3D, respectively) structures, mesopore/micropore volumes, and thick-walled frameworks were successfully fabricated by instant direct templating of lyotropic phases of copolymer (EO(m)-PO(n)-EO(m)) surfactants. Large cage-like pores with uniform constriction sizes up to 10 nm and open cylindrical channel-like mesopores can be easily achieved by this simple and efficient synthesis design. Our results show that the cage-like pores could be fabricated at relatively lower copolymer concentrations used in the lyotropic phase domains at copolymer/TMOS ratios of 35 wt %. These ordered cage pore architectures underwent transition to open-cylindrical pores by increasing the copolymer concentration. High EO/PO block copolymers, in general, were crucially affected on the increase of the interior cavity sizes and on the stability of the cage mesopore characters. However, for F108 (EO(141)PO(44)EO(141)) systems, the fabrication of ordered and stable cage pore monoliths was achieved with significantly higher copolymer concentrations up to 90 wt %. Interestingly, the effective copolymer molecular nature was also observed in the ability to design various ordered mesophase geometries in large domain sizes. Our findings here show evidence that the synthetic strategy provides realistic control over a wide range of mesostructured phase geometries and their extended long-range ordering in the final replicas of the silica monolith frameworks. In addition, the HOM silica monoliths exhibited considerable structural stability against higher thermal temperature (up to 1000 degrees C) and longer hydrothermal treatment times under boiling water and steam. The remarkable structural findings of 3D frameworks, transparent monoliths, and micropores combined with large cage- and cylindrical-like mesopores are expected to find promising uses in materials chemistry.

  19. Online adaptation and over-trial learning in macaque visuomotor control

    Directory of Open Access Journals (Sweden)

    Daniel A. Braun

    2011-06-01

    Full Text Available 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.

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

    Science.gov (United States)

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

    2011-01-01

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