WorldWideScience

Sample records for adaptive control system

  1. Adaptive Inflow Control System

    CERN Document Server

    Volkov, Vasily Y; Zhuravlev, Oleg N; Nukhaev, Marat T; Shchelushkin, Roman V

    2014-01-01

    This article presents the idea and realization for the unique Adaptive Inflow Control System being a part of well completion, able to adjust to the changing in time production conditions. This system allows to limit the flow rate from each interval at a certain level, which solves the problem of water and gas breakthroughs. We present the results of laboratory tests and numerical calculations obtaining the characteristics of the experimental setup with dual-in-position valves as parts of adaptive inflow control system, depending on the operating conditions. The flow distribution in the system was also studied with the help of three-dimensional computer model. The control ranges dependences are determined, an influence of the individual elements on the entire system is revealed.

  2. ADAPTIVE GENERALIZED PREDICTIVE CONTROL OF SWITCHED SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    WANG Yi-jing; WANG Long

    2005-01-01

    The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.

  3. Framework of Combined Adaptive and Non-adaptive Attitude Control System for a Helicopter Experimental System

    Institute of Scientific and Technical Information of China (English)

    Akira Inoue; Ming-Cong Deng

    2006-01-01

    This paper presents a framework of a combined adaptive and non-adaptive attitude control system for a helicopter experimental system. The design method is based on a combination of adaptive nonlinear control and non-adaptive nonlinear control. With regard to detailed attitude control system design, two schemes are shown for different application cases.

  4. An adaptive strategy for controlling chaotic system

    Institute of Scientific and Technical Information of China (English)

    曹一家; 张红先

    2003-01-01

    This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems : Duffing oscillator and Rǒssler chaos.

  5. An adaptive strategy for controlling chaotic system

    Institute of Scientific and Technical Information of China (English)

    曹一家; 张红先

    2003-01-01

    This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems: Duffing oscillator and Rossler chaos.

  6. 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

  7. Adaptive tracking control of chaotic systems

    Institute of Scientific and Technical Information of China (English)

    卢钊; 卢和

    2004-01-01

    It is important to develop control techniques able to control not only known chaos but also chaotic systems with unknown parameters. This paper proposes a novel adaptive tracking control approach for identifying the unknown parameters and controlling the chaos, which is not closely related to the particular chaotic system to be controlled. The global uniform boundedness of estimated parameters and the asymptotical stability of the tracking errors are proved by Lyapunov stability theory and LaSalle-Yoshizawa theorem. The suggested method enables stabilization of chaotic motion to a steady state ad well as tracking of any desired trajectory to be achieved in a systematic way. Computer simulation on a complex chaotic system illustrtes the effectiveness of the proposed control method.

  8. 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.

  9. Robust adaptive control of continuous system with unknown deadzone

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Presents an adaptive controller for continuous systems with unknown deadzones and known linear part which consists of an adaptive deadzone inverse to cancel the effects of deadzone and a linear-like control law to track the system output. It concludes from simulation results that this control possesses good robustness and improves the tracking performance of the system.

  10. 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.

  11. Cascade adaptive control of uncertain unified chaotic systems

    Institute of Scientific and Technical Information of China (English)

    Wei Wei; Li Dong-Hai; Wang Jing

    2011-01-01

    The chaos control of uncertain unified chaotic systems is considered. Cascade adaptive control approach with only one control input is presented to stabilize states of the uncertain unified chaotic system at the zero equilibrium point.Since an adaptive controller based on dynamic compensation mechanism is employed, the exact model of the unified chaotic system is not necessarily required.By choosing appropriate controller parameters, chaotic phenomenon can be suppressed and the response speed is tunable. Sufficient condition for the asymptotic stability of the approach is derived. Numerical simulation results confirm that the cascade adaptive control approach with only one control signal is valid in chaos control of uncertain unified chaotic systems.

  12. Adaptive P300 based control system

    OpenAIRE

    Jin J; Allison B.Z.; Sellers E.W.; Brunner & C.; Horki P.; Wang X; Neuper C.

    2011-01-01

    An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasi...

  13. 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.

  14. Adaptive Inverse Optimal Control of a Magnetic Levitation System

    OpenAIRE

    Satoh, Yasuyuki; Nakamura, Hisakazu; Katayama, Hitoshi; Nishitani, Hirokazu

    2009-01-01

    In this article, we proposed an adaptive inverse optimal controller for the magnetic levitation system. First, we designed an inverse optimal controller with a pre-feedback gravity compensator and applied it to the magnetic levitation system. However, this controller cannot guarantee any stability margin. We demonstrated that the controller did not work well (offset error remained) in the experiment. Hence, we proposed an improved controller via an adaptive control technique to guarantee the ...

  15. System Dynamics and Adaptive Control for MEMS Gyroscope Sensor

    OpenAIRE

    Juntao Fei; Hongfei Ding

    2011-01-01

    This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...

  16. Multiple-Model Adaptive Switching Control for Uncertain Multivariable Systems

    NARCIS (Netherlands)

    Baldi, Simone; Battistelli, Giorgio; Mari, Daniele; Mosca, Edoardo; Tesi, Pietro

    2011-01-01

    This paper addresses the problem of controlling an uncertain multi-input multi-output (MIMO) system by means of adaptive switching control schemes. In particular, the paper aims at extending the approach of multiple-model unfalsified adaptive switched control, so far restricted to single-input singl

  17. Integrated Damage-Adaptive Control System (IDACS) Project

    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...

  18. Discrete Time Optimal Adaptive Control for Linear Stochastic Systems

    Institute of Scientific and Technical Information of China (English)

    JIANG Rui; LUO Guiming

    2007-01-01

    The least-squares(LS)algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares(WLS)algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for daptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller,this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.

  19. Adaptive tracking control for a class of uncertain chaotic systems

    Institute of Scientific and Technical Information of China (English)

    Chen Feng-Xiang; Wang Wei; Zhang Wei-Dong

    2007-01-01

    The paper is concerned with adaptive tracking problem for a class of chaotic system with time-varying uncertainty,but bounded by norm polynomial. Based on adaptive technique, it proposes a novel controller to asymptotically track the arbitrary desired bounded trajectory. Simulation on the Rossler chaotic system is performed and the result verifies the effectiveness of the proposed method.

  20. Robust adaptive control for interval time-delay systems

    Institute of Scientific and Technical Information of China (English)

    Yizhong WANG; Huaguang ZHANG; Jun YANG

    2006-01-01

    This paper focuses on the robust adaptive control problems for a class of interval time-delay systems and a class of large-scale interconnected systems. The nonlinear uncertainties of the systems under study are bounded by high-order polynomial functions with unknown gains. Firstly, the adaptive feedback controller which can guarantee the stability of the closed-loop system in the sense of uniform ultimate boundedness is proposed. Then the proposed adaptive idea is extended to robust stabilizing designing method for a class of large-scale interconnected systems. Here, another problem we address is to design a decentralized feedback adaptive controller such that the closed-loop system is stable in the sense of uniform ultimate boundedness for all admissible uncertainties and time-delay. Finally, an illustrative example is given to show the validity of the proposed approach.

  1. Robust adaptive tracking control of robotic systems with uncertainties

    Institute of Scientific and Technical Information of China (English)

    Yaonan WANG; Jinzhu PENG; Wei SUN; Hongshan YU; Hui ZHANG

    2008-01-01

    To deal with the uncertainty factors of robotic systems,a robust adaptive tracking controller is Droposed.The knowledge of the uncertainty factors is assumed to be unidentified;the proposed controller can guarantee robustness to parametric and dynamics uncertainties and can also reject any bounded,immeasurable disturbances entering the System.The stability of the proposed controller is proven by the Lyapunov method.The proposed controller can easily be implemented and the stability of the closed system can be ensured;the tracking error and adaptation parameter error are uniformly ultimately bounded(UUB).Finally,some simulation examples are utilized to illustrate the control performance.

  2. Adaptive Fuzzy Dynamic Surface Control for Uncertain Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    Xiao-Yuan Luo; Zhi-Hao Zhu; Xin-Ping Guan

    2009-01-01

    In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of "explosion of complexity" in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globaily uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller (SMC). Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.

  3. 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...

  4. 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)....

  5. 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...

  6. 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.

  7. Robust adaptive control of nonlinearly parameterized systems with unmodeled dynamics

    Institute of Scientific and Technical Information of China (English)

    LIU Yu-sheng; CHEN Jiang; LI Xing-yuan

    2006-01-01

    Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties.How to control such systems effectively is one of the most challenging problems.This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems.The controller can be used in cases where there exist parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The design of the controller is based on the control Lyapunov function method.A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics,nonlinear uncertainties and unknown bounded disturbances.The backstepping procedure is employed to overcome the complexity in the design.With the proposed method,the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters.there are.It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system.Furthermore,all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately.Simulation results illustrate the effectiveness of the proposed robust adaptive controller.

  8. Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

    Institute of Scientific and Technical Information of China (English)

    Mingjun ZHANG; Huaguang ZHANG

    2006-01-01

    In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.

  9. 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...... and used in a backstepping design of a nonlinear adaptive controller. The stability of the proposed method is validated theoretically by Lyapunov analysis and experimental results show the performance of the system for a wide range of operating points. The method is compared to a conventional method based...

  10. Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

    CERN Document Server

    Xia, Feng; Peng, Chen; Sun, Youxian; Dong, Jinxiang

    2008-01-01

    There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results sh...

  11. 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. PMID:27342993

  12. Adaptive control of Hammerstein-Wiener nonlinear systems

    Science.gov (United States)

    Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong

    2016-07-01

    The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.

  13. Laser vision based adaptive fill control system for TIG welding

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The variation of joint groove size during tungsten inert gas (TIG) welding will result in the non-uniform fill of deposited metal. To solve this problem, an adaptive fill control system was developed based on laser vision sensing. The system hardware consists of a modular development kit (MDK) as the real-time image capturing system, a computer as the controller, a D/A conversion card as the interface of controlled variable output, and a DC TIG welding system as the controlled device. The system software is developed and the developed feature extraction algorithm and control strategy are of good accuracy and robustness. Experimental results show that the system can implement adaptive fill of melting metal with high stability, reliability and accuracy. The groove is filled well and the quality of the weld formation satisfies the relevant industry criteria.

  14. Adaptive control of uncertain time-delay chaotic systems

    Institute of Scientific and Technical Information of China (English)

    Zhuhong ZHANG

    2005-01-01

    This work investigates adaptive control of a large class of uncertain me-delay chaotic systems (UTCSs) with unknown general perturbation terms bounded by a polynomial ( unknown gains). Associated with the different cases of known and unknown system matrices, two corresponding adaptive controllers are proposed to stabilize unstable fixed points of the systems by means of Lyapunov stability theory and linear matrix inequalities (LMI) which can be solved easily by convex optimization algorithms. Two examples are used for examining the effectiveness of the proposed methods.

  15. 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 w

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

    Science.gov (United States)

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

    2012-12-01

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

  17. Robust adaptive output feedback control of nonlinearly parameterized systems

    Institute of Scientific and Technical Information of China (English)

    LIU Yusheng; LI Xingyuan

    2007-01-01

    The ideas of adaptive nonlinear damping and changing supply functions were used to counteract the effects of parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The high-gain observer was used to estimate the state of the system.A robust adaptive output feedback control scheme was proposed for nonlinearly parameterized systems represented by inputoutput models.The scheme does not need to estimate the unknown parameters nor add a dynamical signal to dominate the effects of unmodeled dynamics.It is proven that the proposed control scheme guarantees that all the variables in the closed-loop system are bounded and the mean-square tracking error can be made arbitrarily small by choosing some design parameters appropriately.Simulation results have illustrated the effectiveness of the proposed robust adaptive control scheme.

  18. Adaptive backstepping slide mode control of pneumatic position servo system

    Science.gov (United States)

    Ren, Haipeng; Fan, Juntao

    2016-06-01

    With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental results show that the designed controller can achieve better tracking performance, as compared with some existing methods.

  19. Adaptive mechanism-based congestion control for networked systems

    Science.gov (United States)

    Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

    2013-03-01

    In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

  20. Adaptive control of system with hysteresis using neural networks

    Institute of Scientific and Technical Information of China (English)

    Li Chuntao; Tan Yonghong

    2006-01-01

    An adaptive control scheme is developed for a class of single-input nonlinear systems preceded by unknown hysteresis, which is a non-differentiable and multi-value mapping nonlinearity. The controller based on the three-layer neural network (NN), whose weights are derived from Lyapunov stability analysis, guarantees closed-loop semiglobal stability and convergence of the tracking errors to a small residual set. An example is used to confirm the effectiveness of the proposed control scheme.

  1. Fibradapt trademark: Adaptive Wind Turbine Control System; Fibradapt trademark: Adaptive Wind Turbine Control System

    Energy Technology Data Exchange (ETDEWEB)

    Wernicke, J.-Th. [Wind Force Engineering and Consulting GmbH, Bremerhaven (Germany)

    2004-07-01

    The technology of Time Division Multiplexing (TDM) is compared with conventional strain gauge technologies in practical operation in a wind power system. Load cycles in the rotor blade were measured during plant life, and the data were used in plant control. The system is a tool in technical project management and financial management of a wind park. (orig.)

  2. Adaptive robust control of nonholonomic systems with stochastic disturbances

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    This paper deals with nonholonomic systems in chained form with unknown covariance stochastic disturbances. The objective is to design the almost global adaptive asymptotical controllers in probability u0 and u1 for the systems by using discontinuous control. A switching control law u0 is designed to almost globally asymptotically stabilize the state x0 in both the singular x0 (t0)=0 case and the non-singular x0 (t0)≠0 case. Then the state scaling technique is introduced for the discontinuous feedback into the (x1, x2, …, xn)-subsystem. Thereby, by using backstepping technique the global adaptive asymptotical control law u1 has been presented for (x1, x2, …, xn) -subsystem for both different u0 in non-singular x0 (t0)≠0 case and the singular case x0 (t0)=0. The control algorithm validity is proved by simulation.

  3. ROBUST ADAPTIVE CONTROL OF NONHOLONOMIC SYSTEMS WITH UNCERTAINTIES

    Institute of Scientific and Technical Information of China (English)

    慕小武; 虞继敏; 毕卫萍; 程代展

    2004-01-01

    Robust adaptive control of nonholonomic systems in chained form with linearly parameterized and strongly nonlinear disturbance and drift terms is dicussed.The novelty of the proposed method is a combined use of the state-scaling and the back-stepping procedure.

  4. 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.

  5. Dissipative-based adaptive neural control for nonlinear systems

    Institute of Scientific and Technical Information of China (English)

    Yugang NIU; Xingyu WANG; Junwei LU

    2004-01-01

    A dissipative-based adaptive neural control scheme was developed for a class of nonlinear uncertain systems with unknown nonlinearities that might not be linearly parameterized. The major advantage of the present work was to relax the requirement of matching condition, I.e., the unknown nonlinearities appear on the same equation as the control input in a state-space representation, which was required in most of the available neural network controllers. By synthesizing a state-feedback neural controller to nake the closed-loop system dissipative with respect to a quadratic supply rate, the developed control scheme guarantees that the L2-gain of controlled system was less than or equal to a prescribed level. And then, it is shown that the output tracking error is uniformly ultimate bounded. The design scheme is illustrated using a numerical simulation.

  6. Adaptive Control of Electromagnetic Suspension System by HOPF Bifurcation

    Directory of Open Access Journals (Sweden)

    Aming Hao

    2013-01-01

    Full Text Available EMS-type maglev system is essentially nonlinear and unstable. It is complicated to design a stable controller for maglev system which is under large-scale disturbance and parameter variance. Theory analysis expresses that this phenomenon corresponds to a HOPF bifurcation in mathematical model. An adaptive control law which adjusts the PID control parameters is given in this paper according to HOPF bifurcation theory. Through identification of the levitated mass, the controller adjusts the feedback coefficient to make the system far from the HOPF bifurcation point and maintain the stability of the maglev system. Simulation result indicates that adjusting proportion gain parameter using this method can extend the state stability range of maglev system and avoid the self-excited vibration efficiently.

  7. Adaptation with disturbance attenuation in nonlinear control systems

    Energy Technology Data Exchange (ETDEWEB)

    Basar, T. [Univ. of Illinois, Urbana, IL (United States)

    1997-12-31

    We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.

  8. Direct adaptive control for nonlinear uncertain system based on control Lyapunov function method

    Institute of Scientific and Technical Information of China (English)

    Chen Yimei; Han Zhengzhi; Tang Houjun

    2006-01-01

    The problem of adaptive stabilization of a class of multi-input nonlinear systems with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapunov function method, a direct adaptive controller is designed to complete the global adaptive stability of the uncertain system. At the same time, the controller is also verified to possess the optimality. Example and simulations are provided to illustrate the effectiveness of the proposed method.

  9. 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.

  10. Adaptive Vibration Control System for MR Damper Faults

    Directory of Open Access Journals (Sweden)

    Juan C. Tudón-Martínez

    2015-01-01

    Full Text Available Several methods have been proposed to estimate the force of a semiactive damper, particularly of a magnetorheological damper because of its importance in automotive and civil engineering. Usually, all models have been proposed assuming experimental data in nominal operating conditions and some of them are estimated for control purposes. Because dampers are prone to fail, fault estimation is useful to design adaptive vibration controllers to accommodate the malfunction in the suspension system. This paper deals with the diagnosis and estimation of faults in an automotive magnetorheological damper. A robust LPV observer is proposed to estimate the lack of force caused by a damper leakage in a vehicle corner. Once the faulty damper is isolated in the vehicle and the fault is estimated, an Adaptive Vibration Control System is proposed to reduce the fault effect using compensation forces from the remaining healthy dampers. To fulfill the semiactive damper constraints in the fault adaptation, an LPV controller is designed for vehicle comfort and road holding. Simulation results show that the fault observer has good performance with robustness to noise and road disturbances and the proposed AVCS improves the comfort up to 24% with respect to a controlled suspension without fault tolerance features.

  11. ADAPTIVE CONTROLLER AND ITS APPLICATION IN FORCE SYSTEM OF ASYMMETRIC CYLINDER CONTROLLED BY SYMMETRIC VALVE

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model reference adaptive controller is designed using equilibrium point stability theory and output error equation polynomial. The reference model is selected in such a way that it meets the system dynamic performance. Hardware configuration of asymmetric cylinder controlled by asymmetric valve hydraulic system is replaced by intelligent control algorithm, thus the cost is lowered and easy to application. Simulation results demonstrate that the proposed adaptive control sheme has good adaptive ability and well solves asymmetric dynamic performance problem. The designed adaptive controller is fairly robust to load disturbance and system parameter variation.

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

    Science.gov (United States)

    Wai, Rong-Jong; Lee, Jeng-Dao

    2008-01-01

    A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies. PMID:18269938

  13. 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.

  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. A self-adaptive feedforward rf control system for linacs

    International Nuclear Information System (INIS)

    The design and performance of a self-adaptive feedforward rf control system are reported. The system was built for the linac of the Accelerator Test Facility (ATF) at Brookhaven National Laboratory. Variables of time along the linac macropulse, such as field or phase are discretized and represented as vectors. Upon turn-on or after a large change in the operating-point, the control system acquires the response of the system to test signal vectors and generates a linearized system response matrix. During operation an error vector is generated by comparing the linac variable vectors and a target vector. The error vector is multiplied by the inverse of the system's matrix to generate a correction vector is added to an operating point vector. This control system can be used to control a klystron to produce flat rf amplitude and phase pulses, to control a rf cavity to reduce the rf field fluctuation, and to compensate the energy spread among bunches in a rf linac. Beam loading effects can be corrected and a programmed ramp can be produced. The performance of the control system has been evaluated on the control of a klystron's output as well as an rf cavity. Both amplitude and phase have been regulated simultaneously. In initial tests, the rf output from a klystron has been regulated to an amplitude fluctuation of less than ±0.3% and phase variation of less than ±0.6deg. The rf field of the ATF's photo-cathode microwave gun cavity has been regulated to ±5% in amplitude and simultaneously to ±1deg in phase. Regulating just the rf field amplitude in the rf gun cavity, we have achieved amplitude fluctuation of less than ±2%. (orig.)

  16. 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.

  17. Strategy missile control system design using adaptive fuzzy control based on Popov stability criterion

    Science.gov (United States)

    Zhang, Jianling; An, Jinwen; Wang, Mina

    2005-11-01

    This paper describes the application and simulation of an adaptive fuzzy controller for a missile model. The fuzzy control system is tested using different values of fuzzy controller correctional factor on a nonlinear missile model. It is shown that the self-tuning fuzzy controller is well suited for controlling the pitch loop of the missile control system with air turbulence and parameter variety. The research shows that the Popov stability criterion could successfully guarantee the stability of the fuzzy system. It provides a good method for the design of missile control system. Simulation results suggest significant benefits from fuzzy logic in control task for missile pitch loop control.

  18. Model adaptation in a central controller for a sewer system

    Science.gov (United States)

    van Nooijen, Ronald; Kolechkina, Alla; Mol, Bart

    2013-04-01

    For small sewer systems that combine foul water and storm water sewer functions in flat terrain, central control of the sewer system may have problems during dry weather. These systems are a combination of local gravity flow networks connected by pumps. Under those conditions the level in the wet well (local storage at the pumping station) should be kept below the entrance pipe but above the top of the intake of the pump. The pumps are dimensioned to cope with the combined flow of foul water and precipitation run off so their capacity is relatively large when compared wityh the volume available in the wet well. Under local control this is not a major problem because the effective controller time step is very short. For central control the control time step can become a problem. Especially when there is uncertainty about the relation between level and volume in the wet well. In this paper we describe a way to dynamically adapt the level to volume relation based on dry weather behaviour. This is important because a better estimate of this volume will reduce the number of on/off cycles for the pumps. It will also allow detection and correction for changes in pump performance due to aging.

  19. 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.

  20. Integrated Damage-Adaptive Control System (IDACS) Project

    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...

  1. Neural-network adaptive controller for nonlinear systems and its application in pneumatic servo systems

    Institute of Scientific and Technical Information of China (English)

    Lu LU; Fagui LIU; Weixiang SHI

    2008-01-01

    In this paper, a novel control law is presented, which uses neural-network techniques to approximate the affine class nonlinear system having unknown or uncertain dynamics and noise disturbances. It adopts an adaptive control law to adjust the network parameters online and adds another control component according to H-infinity control theory to attenuate the disturbance. This control law is applied to the position tracking control of pneumatic servo systems. Simulation and experimental results show that the tracking precision and convergence speed is obviously superior to the results by using the basic BP-network controller and self-tuning adaptive controller.

  2. System identification of a mechanical system with impacts using model reference adaptive control

    OpenAIRE

    Virden, D.; Wagg, D.J.

    2005-01-01

    A single degree of freedom mechanical spring-mass system was considered where the motion of the mass is constrained by an adjustable rigid impact stop. A model reference adaptive control algorithm combined with interspike interval techniques was used to consider the viability of identifying system parameters when impacts are present. The unmodified adaptive control algorithm destabilizes during vibro-impact motion, so three modified control algorithms were tested experimentally. The first, th...

  3. Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

    Science.gov (United States)

    Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

    2016-01-01

    Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

  4. Computational issue in the analysis of adaptive control systems

    Science.gov (United States)

    Kosut, Robert L.

    1989-01-01

    Adaptive systems under slow parameter adaption can be analyzed by the method of averaging. This provides a means to assess stability (and instability) properties of most adaptive systems, either continuous-time or (more importantly for practice) discrete-time, as well as providing an estimate of the region of attraction. Although the method of averaging is conceptually straightforward, even simple examples are well beyond hand calculations. Specific software tools are proposed which can provide the basis for user-friendly environment to perform the necessary computations involved in the averaging analysis.

  5. A modified Adaptive Wavelet PID Control Based on Reinforcement Learning for Wind Energy Conversion System Control

    Directory of Open Access Journals (Sweden)

    REZAZADEH, A.

    2010-05-01

    Full Text Available Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS. This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to approximate the policy function of the Actor and the value function of the Critic simultaneously. These controllers are used to control a typical WECS in noiseless and noisy condition and results are compared with an adaptive Radial Basis Function (RBF PID control based on reinforcement learning and conventional PID control. Practical emulated results prove the capability and the robustness of the suggested controller versus the other PID controllers to control of the WECS. The ability of presented controller is tested by experimental setup.

  6. Unfalsified Adaptive Switching Supervisory Control of Time Varying Systems

    NARCIS (Netherlands)

    Battistelli, Giorgio; Hespanha, João; Mosca, Edoardo; Tesi, Pietro

    2009-01-01

    In recent years, unfalsified adaptive switching supervisory control (UASSC) has emerged as an effective technique for tackling the problem of controlling uncertain plants only on the basis of the plant I/O data. The aim of this paper is to construct a novel switching logic, which, when combined with

  7. 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...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...... 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....

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

    International Nuclear Information System (INIS)

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

  9. 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.

  10. A modified Adaptive Wavelet PID Control Based on Reinforcement Learning for Wind Energy Conversion System Control

    OpenAIRE

    REZAZADEH, A.; SEDIGHIZADEH, M.

    2010-01-01

    Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS). This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to appro...

  11. 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.

  12. PFC design via FRIT Approach for Adaptive Output Feedback Control of Discrete-time Systems

    Science.gov (United States)

    Mizumoto, Ikuro; Takagi, Taro; Fukui, Sota; Shah, Sirish L.

    This paper deals with a design problem of an adaptive output feedback control for discrete-time systems with a parallel feedforward compensator (PFC) which is designed for making the augmented controlled system ASPR. A PFC design scheme by a FRIT approach with only using an input/output experimental data set will be proposed for discrete-time systems in order to design an adaptive output feedback control system. Furthermore, the effectiveness of the proposed PFC design method will be confirmed through numerical simulations by designing adaptive control system with adaptive NN (Neural Network) for an uncertain discrete-time system.

  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 Neural Control Design For a Class of Nonlinear Time-delay Systems

    Institute of Scientific and Technical Information of China (English)

    FENG Ling-ling; ZHANG Wei

    2014-01-01

    This paper proposes an indirect adaptive neural control scheme for a class of nonlinear systems with time delays. Based on the backstepping technique and Lyapunov–Krasovskii functional method are combined to construct the indirect adaptive neural controller. The proposed indirect adaptive neural controller guarantees that the state variables converge to a small neighborhood of the origin and all the signals of the closed-loop system are bounded. Finally, an example is used to show the effectiveness of the proposed control strategy.

  15. A practical scheme for adaptive aircraft flight control systems

    Science.gov (United States)

    Athans, M.; Willner, D.

    1974-01-01

    A flight control system design is presented, that can be implemented by analog hardware, to be used to control an aircraft with uncertain parameters. The design is based upon the use of modern control theory. The ideas are illustrated by considering control of STOL longitudinal dynamics.

  16. 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.

  17. An integrated architecture of adaptive neural network control for dynamic systems

    Energy Technology Data Exchange (ETDEWEB)

    Ke, Liu; Tokar, R.; Mcvey, B.

    1994-07-01

    In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.

  18. Backstepping Adaptive Controller of Electro-Hydraulic Servo System of Continuous Rotary Motor

    Institute of Scientific and Technical Information of China (English)

    XiaoJing Wang; ChangFu Xian; CaoLei Wan; JinBao Zhao; LiWei Xiu; AnCai Yu

    2014-01-01

    In order to consider the influence of the continuous rotary motor electro-hydraulic servo system parameters change on its performance, the design method of backstepping adaptive controller is put forward. The mathematical model of electro-hydraulic servo system of continuous rotary motor is established, and the whole system is decomposed into several lower order subsystems, and the virtual control signal is designed for each subsystem from the final subsystem with motor angular displacement to the subsystem with system control input voltage. Based on Lyapunov method and the backstepping theory, an adaptive backstepping controller is designed with the changed parameters adaptive law. It is proved that the system reaches the global asymptotic stability, and the system tracking error asymptotically tends to zero. The simulation results show that the backstepping adaptive controller based on the adaptive law of the changed parameters can improve the performance of continuous rotary motor, and the proposed control strategy is feasible.

  19. Improved adaptive fuzzy control for MIMO nonlinear time-delay systems

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    This paper presents an improved observer-based indirect adaptive fuzzy control scheme for multiinput-multioutput (MIMO) nonlinear time-delay systems.The control scheme synthesizes adaptive fuzzy control with adaptive fuzzy identification.An observer is designed to observe the system state,and an identifier is developed to identify the unknown parts of the system.The update laws for parameters utilize two types of errors in the adaptive time-delay fuzzy logic systems,the observation error and the identificat...

  20. Adaptive Fuzzy Containment Control for Uncertain Nonlinear Multiagent Systems

    Directory of Open Access Journals (Sweden)

    Yang Yu

    2014-01-01

    Full Text Available This paper considers the containment control problem for uncertain nonlinear multiagent systems under directed graphs. The followers are governed by nonlinear systems with unknown dynamics while the multiple leaders are neighbors of a subset of the followers. Fuzzy logic systems (FLSs are used to identify the unknown dynamics and a distributed state feedback containment control protocol is proposed. This result is extended to the output feedback case, where observers are designed to estimate the unmeasurable states. Then, an output feedback containment control scheme is presented. The developed state feedback and output feedback containment controllers guarantee that the states of all followers converge to the convex hull spanned by the dynamic leaders. Based on Lyapunov stability theory, it is proved that the containment control errors are uniformly ultimately bounded (UUB. An example is provided to show the effectiveness of the proposed control method.

  1. Adaptive neuro-fuzzy inference system based automatic generation control

    Energy Technology Data Exchange (ETDEWEB)

    Hosseini, S.H.; Etemadi, A.H. [Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran)

    2008-07-15

    Fixed gain controllers for automatic generation control are designed at nominal operating conditions and fail to provide best control performance over a wide range of operating conditions. So, to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to compute control gains. A control scheme based on artificial neuro-fuzzy inference system (ANFIS), which is trained by the results of off-line studies obtained using particle swarm optimization, is proposed in this paper to optimize and update control gains in real-time according to load variations. Also, frequency relaxation is implemented using ANFIS. The efficiency of the proposed method is demonstrated via simulations. Compliance of the proposed method with NERC control performance standard is verified. (author)

  2. 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

    This paper deals with high-performance position control of hydraulics servo systems in general. The hydraulic servo system used is a two link robotic manipulator actuated by two hydraulic servo cylinders. A non-linear model of the hydraulic system and a Newton-Euler based model of the mechanical...

  3. Use of single chip microcomputer in hydraulic digital adaptive control system

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Presents a one-grade adaptive controller with one reference model which is built according to δ MRACS adaptive control theorv and used to control an actual high-order hydraulic system, and the whole hard ware system used, which includes a AT89C51 single chip microcomputer, 74Ls373 flip-latch, 6116 store, eight-bit ADC0809, and so on, and the satisfactory results obtained in study on hydraulic control system.

  4. Adaptive Structural Mode Control Project

    Data.gov (United States)

    National Aeronautics and Space Administration — M4 Engineering proposes the development of an adaptive structural mode control system. The adaptive control system will begin from a "baseline" dynamic model of the...

  5. 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

  6. Adaptive control of bifurcation and chaos in a time-delayed system

    Institute of Scientific and Technical Information of China (English)

    Li Ning; Yuan Hui-Qun; Sun Hai-Yi; Zhang Qing-Ling

    2013-01-01

    In this paper,the stabilization of a continuous time-delayed system is considered.To control the bifurcation and chaos in a time-delayed system,a parameter perturbation control and a hybrid control are proposed.Then,to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes,the adaptive control idea is introduced,i.e.,the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws,respectively.The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem.The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods.They have the advantages of increased stability,adaptability to the changes of the system parameters,control cost saving,and simplicity.Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods.A comparison of the two adaptive control methods is also made in an experimental study.

  7. Adaptive Backstepping controller design and implementation for a matrix-converter-based IM drive system

    OpenAIRE

    R.R. Joshi; R.A. Gupta; A.K. Wadhwani

    2007-01-01

    A systematic controller design and implementation for a matrix-converter-based induction motor drive system is proposed. A nonlinear adaptive backstepping controller is proposed to improve the speed and position responses of the induction motor system. By using the proposed adaptive backstepping controller, the system can track a time-varying speed command and a time-varying position command well. Moreover, the system has a good load disturbance rejection capability. The realization of the co...

  8. Adaptive Control for Uncertain Nonlinear Multi-Input Multi-Output Systems

    Science.gov (United States)

    Cao, Chengyu (Inventor); Hovakimyan, Naira (Inventor); Xargay, Enric (Inventor)

    2014-01-01

    Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.

  9. Adaptive switching control of discrete time nonlinear systems based on multiple models

    Institute of Scientific and Technical Information of China (English)

    Rui KAN

    2004-01-01

    We use the approach of "optimal" switching to design the adaptive control because the design among multiple models is intuitively more practically feasible than the traditional adaptive control in improving the performances. We prove that for a typical class of nonlinear systems disturbed by random noise, the multiple model adaptive switching control based on WLS(Weighted Least Squares) or projected-LS (Least Squares) is stable and convergent.

  10. Determination of Close Loop System Stability in Automobile Adaptive Cruise Control Systems

    Directory of Open Access Journals (Sweden)

    Owunna Ikechukwu

    2016-07-01

    Full Text Available The beginning of the 21st century sees auto makers pursuing research in advanced features like collision warning and avoidance system into their product. Automotive cruise control system has been undergoing development in EU since the PROMETHEUS programme in the late 1980’s, and has currently metamorphous into Adaptive Cruise Control (ACC technology which is presently emerging in the automotive market as a convenience function intended to reduce driver workload. Adaptive cruise control is the first of the new generation of advanced driver’s assistance devices to reach the market, which partially automates the driver’s task and bringing the drivers comfort into perspective. It allows the host vehicle to maintain a set speed and distance from preceding vehicles by a forward object detection sensor. The forward object detection sensor is the focal point of the ACC system, which determines and regulates vehicle acceleration and deceleration through a powertrain torque control system and an automatic brake control system. This study presents overview of adaptive cruise control system, operation principles and the advantages of integrating ACC system in automobiles. Also, the system must be stable for optimum performance, and stability of a close loop system which the cruise system is an example, was determined by calculating the controller gain (K1, K2, K3 and substituting into the characteristic equations. The stability of a close loop system for the values of K1, K2 and K3 when substituted into the characteristic equation produced a negative real part. To achieve stability in close loop systems, all the poles must have negative real values and this is in line with the values obtain for p1, p2 and p3. From the pole zero plots of 1 = (-7 ± 7.14, 2 = (-7± 11.60 and 3 = (-0.08 and -13.91, stability of the system was achieved

  11. Lag Synchronization in Nonlinear Systems Based on Adaptive Control

    Institute of Scientific and Technical Information of China (English)

    赵德勤; 刘曾荣

    2004-01-01

    Active control is an effective method for synchronizing two identical chaotic systems. However, this method works only for a certain class of chaotic systems with known parameters. An improvement method was proposed in order to overcome this limitation in this paper. A classical example was used to demonstrate the method. Finally, numerical examples were given to validate the efficiency of the method.

  12. Adaptive Control System for Autonomous Helicopter Slung Load Operations

    DEFF Research Database (Denmark)

    Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon

    2010-01-01

    This paper presents design and verification of an estimation and control system for a helicopter slung load system. The estimator provides position and velocity estimates of the slung load and is designed to augment existing navigation in autonomous helicopters. Sensor input is provided by a vision...

  13. Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients.

    Science.gov (United States)

    Ge, Shuzhi Sam; Hong, Fan; Lee, Tong Heng

    2004-02-01

    In this paper, adaptive neural control is presented for a class of strict-feedback nonlinear systems with unknown time delays. The proposed design method does not require a priori knowledge of the signs of the unknown virtual control coefficients. The unknown time delays are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. It is proved that the proposed backstepping design method is able to guarantee semiglobal uniformly ultimately boundedness of all the signals in the closed-loop. In addition, the output of the system is proven to converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approach.

  14. A new theorem to synchronization of unified chaotic systems via adaptive control

    Institute of Scientific and Technical Information of China (English)

    Lequan Min; Jianyi Jing

    2003-01-01

    Chaos synchronization has been applied in secure communication, chemical reaction, biological systems, and information processing. A new theorem to synchronization of unified chaotic systems via adaptive control is proposed. The consutructive theorem provides the design scheme for adaptive controller such that a respond system can synchronize with respect to an uncertain drive system. One example for discontinuous chaotic system is proposed to illustrate the effectiveness and feasibility.

  15. Adaptive control and synchronization of an uncertain new hyperchaotic Lorenz system

    Institute of Scientific and Technical Information of China (English)

    Cai Guo-Liang; Zheng Song; Tian Li-Xin

    2008-01-01

    This paper is involved with the adaptive control and synchronization problems for an uncertain new hyperchaotic Lorenz system. Based on the Lyapunov stability theory, the adaptive control law is derived such that the trajectory of hyperchaotic Lorenz system with unknown parameters can be globally stabilized to an unstable equilibrium point of the uncontrolled system. Furthermore, an adaptive control approach is presented to the synchronizations between two identical hyperchaotic systems, particularly between two different uncertain hyperchaotic systems. Numerical simulations show the effectiveness of the presented method.

  16. Robust Adaptive Control

    Science.gov (United States)

    Narendra, K. S.; Annaswamy, A. M.

    1985-01-01

    Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.

  17. Adaptive iterative learning control for high precision motion systems

    OpenAIRE

    Rotariu, I; Steinbuch, M Maarten; Ellenbroek, RML Rogier

    2008-01-01

    Iterative learning control (ILC) is a very effective technique to reduce systematic errors that occur in systems that repetitively perform the same motion or operation. However, several characteristics have prevented standard ILC from being widely used for high precision motion systems. Most importantly, the learned feedforward signal depends on the motion profile (setpoint trajectory) and if this is altered, the learning process has to be repeated. Secondly, ILC amplifies non-repetitive dist...

  18. Adaptive Neural Network Controller for Thermogenerator Angular Velocity Stabilization System

    OpenAIRE

    Horvat, Krunoslav; Šoić, Ines; Kuljača, Ognjen

    2013-01-01

    The paper presents an analytical and simulation approach for the selection of activation functions for the class of neural network controllers for ship’s thermogenerator angular velocity stabilization system. Such systems can be found in many ships. A Lyapunov-like stability analysis is performed in order to obtain a weight update law. A number of simulations were performed to find the best activation function using integral error criteria and statistical T-tests.

  19. Adaptive Impedance Control to Enhance Human Skill on a Haptic Interface System

    Directory of Open Access Journals (Sweden)

    Satoshi Suzuki

    2012-01-01

    Full Text Available Adaptive assistive control for a haptic interface system is proposed in the present paper. The assistive control system consists of three subsystems: a servo controller to match the response of the controlled machine to the virtual model, an online identifier of the operator’s control characteristics, and a variable dynamics control using adaptive mechanism. The adaptive mechanism tunes an impedance of the virtual model for the haptic device according to the identified operator’s characteristics so as to enhance the operator’s control performance. The adaptive law is derived by utilizing a Lyapunov candidate function. Using a haptic interface device composed by a xy-stage, an effectiveness of the proposed control method was evaluated experimentally. As a result, it was confirmed that the operator’s characteristics can be estimated sufficiently and that performance of the operation was enhanced by the variable dynamics assistive control.

  20. A Novel Control-Navigation System- Based Adaptive Optimal Controller & EKF Localization of DDMR

    Directory of Open Access Journals (Sweden)

    Dalia Kass Hanna

    2015-05-01

    Full Text Available This paper presents a newly developed approach for Differential Drive Mobile Robot (DDMR. The main goal is to provide a high dynamic system response in the joint space level, the low level control, as well as to enhance the DDMR localization. The proposed approach depends on a Linear Quadratic Regulator (LQR for the low level control and an Adaptive LQR for the high level control. The investigated DDMR is considered highly nonlinear system due to uncertainty exhibited by the mobile robot incorporated with actuators nonlinearity. DDMR’s uncertainty leads to erroneous localization. An Extended Kalman Filter (EKF -based approach with fusion sensors is used to enhance the robot degree of belief for its posture. Intensive simulation results obtained from the developed uncertain model and the proposed approach have shown very good dynamic performance on the low level control and very good convergence to the desired posture of the mobile robot path with the presence of robot uncertainty.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-12-10

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

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

    International Nuclear Information System (INIS)

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

  3. Adaptive output-feedback following control for time-delay systems

    Directory of Open Access Journals (Sweden)

    Tárník Marián

    2014-12-01

    Full Text Available Adaptive control of the time-delay systems is presented in the paper. Despite the use of MRAC based design, only the model following (not perfect model following is considered. The methods of a classical MRAC design are preserved to the maximum extent which allows further extensions of the algorithm such as the robust adaptive control modifications. The adaptive algorithm effectiveness is presented by means of illustrative examples.

  4. Optimal Adaptive Control of a Class of Stochastic Systems Using Game Theory

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper attempts to study a optimal adaptive con tr ol problem using game theory, and proposes an important practical result that an adaptive processes is a set of sufficient conditions under which pure strategy is essentially complete, and thus the fact that yield a very useful desirable pu re optimal control rule.Optimal Adaptive Control of a Class of Stochastic Systems Using Game Theory

  5. Adaptive synchronization of a class of chaotic systems via variable structure control

    Institute of Scientific and Technical Information of China (English)

    Li Huiguang; Zhang Xinying; Guan Xinping

    2005-01-01

    The synchronization problem under two cases is considered. One is that the bound on the uncertainty existing in the controller is known, the other is that the bound is unknown. In the latter case, the simple adaptation laws for upper bound on the norm of the uncertainty is proposed. Using this adaptive upper bound, a variable structure control is designed. The proposed method does not guarantee the convergence of the adaptive upper bound to the real one but makes the system asymptotically stable.

  6. Adaptive fault-tolerant control of linear systems with actuator saturation and L2-disturbances

    Institute of Scientific and Technical Information of China (English)

    Wei GUAN; Guanghong YANG

    2009-01-01

    This paper studies the problem of designing adaptive fault-tolerant H-infinity controllers for linear timeinvariant systems with actuator saturation. The disturbance tolerance ability of the closed-loop system is measured by an optimal index. The notion of an adaptive H-infinity performance index is proposed to describe the disturbance attenuation performances of closed-loop systems. New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compensations. Based on the on-line estimation of eventual faults, the adaptive fault-tolerant controller parameters are updated automatically to compensate for the fault effects on systems. The designs are developed in the framework of the linear matrix inequality (LMI) approach, which can guarantee the disturbance tolerance ability and adaptive H-infinity performances of closed-loop systems in the cases of actuator saturation and actuator failures. An example is given to illustrate the efficiency of the design method.

  7. Effectiveness of Adaptive Assessment versus Learner Control in a Multimedia Learning System

    Science.gov (United States)

    Chen, Ching-Huei; Chang, Shu-Wei

    2015-01-01

    The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…

  8. Robust adaptive control for uncertain systems with discrete and distributed delays

    Institute of Scientific and Technical Information of China (English)

    Qing ZHU; Shumin FEI; Tao Li; Tianping ZHANG

    2008-01-01

    In this paper,a robust adaptive control scheme is proposed for the stabilization of uncertain linear systems with discrete and distributed delays and bounded peturbaturbations.The uncertainty is assumed to be an unknown continuous function with norm-bounded restriction.The perturbation is sector-bounded.Combining with the liner matrix inequality method,neural networks and adaptive control,the control scheme ensures the exponential stability of the closed-loop system for any admissible uncertainty.

  9. Adaptive Neuro-fuzzy Controller Design for Non-affine Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    JIA Li; GE Shu-zhi; QIU Ming-sen

    2008-01-01

    An adaptive neuro-fuzzy control is investigated for a class of noa-affine nonlinear systems.To do so,rigorous description and quantification of the approximation error of the neuro-fuzzy controller are firstly discussed.Applying this result and Lyapunov stability theory,a novel updating algorithm to adapt the weights,centers,and widths of the neuro-fuzzy controller is presented.Consequently,the proposed design method is able to guaranteg the stability of the closed-loop system and the convergence of the tracking error.Simulation results illustrate the effectiveness of the proposed adaptive neuro-fuzzy control scheme.

  10. Global Chaos Synchronization of Hyperchaotic Lorenz and Hyperchaotic Chen Systems by Adaptive Control

    Directory of Open Access Journals (Sweden)

    Dr. V. Sundarapandian

    2011-06-01

    Full Text Available In this paper, we apply adaptive control method to derive new results for the global chaos synchronization of identical hyperchaotic Lorenz systems (2007, identical hyperchaotic Chen systems (2010 and non-identical hyperchaotic Lorenz and hyperchaotic Chen systems. In this paper, we shall assume that the parameters of both master and slave systems are unknown and we devise adaptive synchronizing schemes using the estimates of parameters for both master and slave systems. Our adaptive synchronization results derived in this paper are established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the adaptive control method is very effective and convenient to synchronize identical and non-identical hyperchaotic Lorenz and hyperchaotic Chensystems. Numerical simulations are shown to demonstrate the effectiveness of the proposed adaptive synchronization schemes for the hyperchaotic systems addressed in this paper.

  11. 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.

  12. Adaptive and Reliable Control Algorithm for Hybrid System Architecture

    Directory of Open Access Journals (Sweden)

    Osama Abdel Hakeem Abdel Sattar

    2012-01-01

    Full Text Available A stand-alone system is defined as an autonomous system that supplies electricity without being connected to the electric grid. Hybrid systems combined renewable energy source, that are never depleted (such solar (photovoltaic (PV, wind, hydroelectric, etc. , With other sources of energy, like Diesel. If these hybrid systems are optimally designed, they can be more cost effective and reliable than single systems. However, the design of hybrid systems is complex because of the uncertain renewable energy supplies, load demands and the non-linear characteristics of some components, so the design problem cannot be solved easily by classical optimisation methods. The use of heuristic techniques, such as the genetic algorithms, can give better results than classical methods. This paper presents to a hybrid system control algorithm and also dispatches strategy design in which wind is the primary energy resource with photovoltaic cells. The dimension of the design (max. load is 2000 kW and the sources is implemented as flow 1500 kw from wind, 500 kw from solar and diesel 2000 kw. The main task of the preposed algorithm is to take full advantage of the wind energy and solar energy when it is available and to minimize diesel fuel consumption.

  13. Application of an adaptive control system to a gold processing plant

    International Nuclear Information System (INIS)

    Installation and operation of a commercially available adaptive process control system in a gold processing plant in Nevada has proven technically and financially successful. Test results show that the system paid for itself through increased throughput within two weeks of commissioning. The control system uses an expert rule base written with both crisp and fuzzy logic rules integrated with continually adapting neural network models used by predictors, and optimizers. This allows the control system to provide optimum process performance under continually varying feed conditions. This paper describes the installation, rule and predictor configuration, and statistically verifiable testing of the control system in an operating plant. (author)

  14. Adaptive fuzzy switched control design for uncertain nonholonomic systems with input nonsmooth constraint

    Science.gov (United States)

    Li, Yongming; Tong, Shaocheng

    2016-10-01

    In this paper, a fuzzy adaptive switched control approach is proposed for a class of uncertain nonholonomic chained systems with input nonsmooth constraint. In the control design, an auxiliary dynamic system is designed to address the input nonsmooth constraint, and an adaptive switched control strategy is constructed to overcome the uncontrollability problem associated with x0(t0) = 0. By using fuzzy logic systems to tackle unknown nonlinear functions, a fuzzy adaptive control approach is explored based on the adaptive backstepping technique. By constructing the combination approximation technique and using Young's inequality scaling technique, the number of the online learning parameters is reduced to n and the 'explosion of complexity' problem is avoid. It is proved that the proposed method can guarantee that all variables of the closed-loop system converge to a small neighbourhood of zero. Two simulation examples are provided to illustrate the effectiveness of the proposed control approach.

  15. Adaptive fuzzy sliding mode control for synchronization of uncertain fractional order chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Tsung-Chih, E-mail: tclin@fcu.edu.tw [Department of Electronic Engineering, Feng-Chia University, Taichung, Taiwan (China); Lee, Tun-Yuan [Department of Electronic Engineering, Feng-Chia University, Taichung, Taiwan (China); Balas, Valentina E. [Aurel Vlaicu University of Arad, B-dul Revolutiei 77, 310130 Arad (Romania)

    2011-10-15

    Highlights: > We study uncertain fractional order chaotic systems synchronization. > Lyapunov synthesis is used to derive control law and adaptive laws. > Based on sliding mode control, chattering phenomena in the control effort can be reduced. - Abstract: This paper deals with chaos synchronization between two different uncertain fractional order chaotic systems based on adaptive fuzzy sliding mode control (AFSMC). With the definition of fractional derivatives and integrals, a fuzzy Lyapunov synthesis approach is proposed to tune free parameters of the adaptive fuzzy controller on line by output feedback control law and adaptive law. Moreover, chattering phenomena in the control efforts can be reduced. The sliding mode design procedure not only guarantees the stability and robustness of the proposed AFSMC, but also the external disturbance on the synchronization error can be attenuated. The simulation example is included to confirm validity and synchronization performance of the advocated design methodology.

  16. Adaptive Control and Synchronization of Sprott J System With Estimation Of Fully Unknown Parameters

    Directory of Open Access Journals (Sweden)

    Islam Mitul

    2015-06-01

    Full Text Available This communication develops an adaptive scheme for control and synchronization of Sprott J system with fully unknown parameters. The scheme provides an elegant strategy of designing estimators for identification of the unknown parameters of the underlying dynamical system. Adaptive control and update laws are proposed to globally stabilize the chaotic Sprott J system. A pair of identical Sprott J systems with un- known parameters are globally synchronized with the help of adaptive control and parameter update laws. The results are established using LaSalle invariance principle, which lays down weaker restrictions on the derivatives of the Lyapunov function, and producing more general results. All the results obtained in the paper are global in nature. Numerical simulations are performed to illustrate the validity and effectiveness of the proposed adaptive control and synchronization scheme in the context of the Sprott J system. The parameter identification capability of the scheme is also explored.

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

    CERN Document Server

    Wu, Zhizheng; Ben Amara, Foued

    2013-01-01

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

  18. Evolving Systems: Nonlinear Adaptive Key Component Control with Persistent Disturbance Rejection

    Science.gov (United States)

    Balas, Mark J.; Frost, Susan A.

    2013-01-01

    This paper presents an introduction to Evolving Systems, which are autonomously controlled subsystems that self-assemble into a new Evolved System with a higher purpose. Evolving Systems of aerospace structures often require additional control when assembling to maintain stability during the entire evolution process. This is the concept of Adaptive Key Component Control which operates through one specific component to maintain stability during the evolution. In addition this control must overcome persistent disturbances that occur while the evolution is in progress. We present theoretical results for the successful operation of Nonlinear Adaptive Key Component control in the presence of such disturbances and an illustrative example.

  19. Optimal higher order learning adaptive control approach for a class of SISO nonlinear systems

    Institute of Scientific and Technical Information of China (English)

    Ronghu CHI; Zhongsheng HOU

    2005-01-01

    In this paper,an optimal higher order learning adaptive control approach is developed for a class of SISO nonlinear systems.This design is model-free and depends directly on pseudo-partial-derivatives derived on-line from the input and output information of the system.A novel weighted one-step-ahead control criterion function is proposed for the control law.The convergence analysis shows that the proposed control law can guarantee the convergence under the assumption that the desired output is a set point.Simulation examples are provided for nonlinear systems to illustrate the better performance of the higher order learning adaptive control.

  20. Application of Model Reference Adaptive Control System to Instrument Pointing System /IPS/

    Science.gov (United States)

    Waites, H. B.

    1979-01-01

    A Model Reference Adaptive Controller (MRAC) is derived for a Shuttle payload called the Instrument Pointing System (IPS). The unique features of this MRAC design are that total state feedback is not required, that the internal structure of the model is independent of the internal structure of the IPS, and that the model input is of bounded variation and not required a priori. An application of Liapunov's stability theorems is used to synthesize a control signal which assures MRAC asymptotic stability. Exponential observers are used to obtain the necessary state information to implement the control synthesis. Results are presented which show how effectively the MRAC can maneuver the IPS.

  1. Adaptive robust control of chaotic oscillations in power system with excitation limits

    Institute of Scientific and Technical Information of China (English)

    Wei Du-Qu; Luo Xiao-Shu

    2007-01-01

    With system parameters falling into a certain area, power system with excitation limits experiences complicated chaotic oscillations which threaten the secure and stable operation of power system. In this paper, to control these unwanted chaotic oscillations, a straightforward adaptive chaos controller based on Lyapunov asymptotical stability theory is designed. Since the presented controller does not need to change the controlled system structure and not to use any information of system except the system state variables, the designed controller is simple and desirable.Simulation results show that the proposed control law is very effective. This work is helpful to maintain the power system's security operation.

  2. Adaptive Fuzzy Robust Control for a Class of Nonlinear Systems via Small Gain Theorem

    Directory of Open Access Journals (Sweden)

    Xingjian Wang

    2013-01-01

    Full Text Available Practical nonlinear systems can usually be represented by partly linearizable models with unknown nonlinearities and external disturbances. Based on this consideration, we propose a novel adaptive fuzzy robust control (AFRC algorithm for such systems. The AFRC effectively combines techniques of adaptive control and fuzzy control, and it improves the performance by retaining the advantages of both methods. The linearizable part will be linearly parameterized with unknown but constant parameters, and the discontinuous-projection-based adaptive control law is used to compensate these parts. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown nonlinearities. Robust control law ensures the robustness of closed-loop control system. A systematic design procedure of the AFRC algorithm by combining the backstepping technique and small-gain approach is presented. Then the closed-loop stability is studied by using small gain theorem, and the result indicates that the closed-loop system is semiglobally uniformly ultimately bounded.

  3. Parameter self-adaptive synchronization control for a kind of financial chaotic systems

    Institute of Scientific and Technical Information of China (English)

    PU Xing-cheng; WANG Hai-ying

    2009-01-01

    A parameter adaptive control approach was applied to a kind of financial chaotic systems. According to Lyapunov stability theorem, synchronization of two financial chaotic systems with different certain parameters or the same uncertain parameters were implemented through designing proper control functions and using parameters self-adaptive control principle. The sufficient synchronization conditions of the two financial systems were obtained. Under the situation of the same uncertain parameters, the synchronization system has simpler controller and better performance. Numerical simulations show the effectiveness of the method.

  4. Adaptive Control and Function Projective Synchronization in 2D Discrete-Time Chaotic Systems

    Institute of Scientific and Technical Information of China (English)

    LI Yin; CHEN Yong; LI Biao

    2009-01-01

    This study addresses the adaptive control and function projective synchronization problems between 2D Rulkov discrete-time system and Network discrete-time system.Based on backstepping design with three controllers, a systematic, concrete and automatic scheme is developed to investigate the function projective synchronization of discrete-time chaotic systems.In addition, the adaptive control function is applied to achieve the state synchronization of two discrete-time systems.Numerical results demonstrate the effectiveness of the proposed control scheme.

  5. Adaptive Excitation Control with L2 Disturbance Attenuation for Multi-Machine Power Systems

    Institute of Scientific and Technical Information of China (English)

    梅生伟; 金敏杰; 申铁龙

    2004-01-01

    Generator excitation control plays an important role in improving the dynamic performance and stability of power systems. This paper is concerned with nonlinear decentralized adaptive excitation control for multi-machine power systems. Based on a recursive design method, an adaptive excitation control law with L2 disturbance attenuation is constructed. Furthermore, it is verified that the proposed control scheme possesses the property of decentralization and the robustness in the sense of L2-gain. As a consequence, transient stability of a multi-machine power system is guaranteed, regardless of system parameters variation and faults.

  6. Robust adaptive controller design for a class of nonlinear systems with unknown high frequency gains

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In this note, a robust adaptive control scheme is proposed for a class of nonlinear systems that have unknown multiplicative terms. Unlike previous results, except for the unknown control directions, we do not require a priori bounds on the unknown parameters. We also allow the unknown parameters to be time-varying provided that they are bounded. Our proposed robust adaptive controller is designed to identify on-line the unknown control directions and is a switching type controller, in which the controller parameters are tuned in a switching manner via a switching logic. Global stability of the closed-loop systems have been proved.

  7. Adaptive model predictive control of the hybrid dynamics of a fuel cell system

    OpenAIRE

    Fiacchini, Mirko; Alamo, Teodoro; Albea-Sanchez, Carolina; Fernandez Camacho, Eduardo

    2007-01-01

    International audience In this paper, an adaptive control scheme for the safe operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen ratio do not reach dangerous values. A first level of control is given by a feedforward control. An improved behavior is obtained using an adaptive predictive controller to determine the voltage to be applied to the air compressor. An admissible robust control invariant set for the PWA model of the system i...

  8. Adaptive control of linear multivariable systems with high frequency gain matrix hurwitz

    Institute of Scientific and Technical Information of China (English)

    Ying ZHOU; Yuqiang WU; Shumin FEI

    2005-01-01

    A new adaptive control scheme is proposed for multivariable model reference adaptive control(MRAC) systems based on the nonlinear backstepping approach with vector form.The assumption on a priori knowledge of the high frequency gain matrix in existing results is relaxed and the new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable.This control scheme guarantees the global stability of the closed-loop systems and the tracking error can be arbitrary small.The simulation result for an application example shows the validity of the proposed nonlinear adaptive scheme.

  9. Adaptive neural control for a class of nonlinearly parametric time-delay systems.

    Science.gov (United States)

    Ho, Daniel W C; Li, Junmin; Niu, Yugang

    2005-05-01

    In this paper, an adaptive neural controller for a class of time-delay nonlinear systems with unknown nonlinearities is proposed. Based on a wavelet neural network (WNN) online approximation model, a state feedback adaptive controller is obtained by constructing a novel integral-type Lyapunov-Krasovskii functional, which also efficiently overcomes the controller singularity problem. It is shown that the proposed method guarantees the semiglobal boundedness of all signals in the adaptive closed-loop systems. An example is provided to illustrate the application of the approach.

  10. The Self-Adaptive Fuzzy PID Controller in Actuator Simulated Loading System

    Directory of Open Access Journals (Sweden)

    Chuanhui Zhang

    2013-05-01

    Full Text Available This paper analyzes the structure principle of the actuator simulated loading system with variable stiffness, and establishes the simplified model. What’s more, it also does a research on the application of the self-adaptive tuning of fuzzy PID(Proportion Integration Differentiation in actuator simulated loading system with variable stiffness. Because the loading system is connected with the steering system by a spring rod, there must be strong coupling. Besides, there are also the parametric variations accompanying with the variations of the stiffness. Based on compensation from the feed-forward control on the disturbance brought by the motion of steering engine, the system performance can be improved by using fuzzy adaptive adjusting PID control to make up the changes of system parameter caused by the changes of the stiffness. By combining the fuzzy control with traditional PID control, fuzzy adaptive PID control is able to choose the parameters more properly.

  11. Adaptive output feedback control of a class of uncertain nonlinear systems with unknown time delays

    Science.gov (United States)

    Guan, Wei

    2012-04-01

    This article studies the adaptive output feedback control problem of a class of uncertain nonlinear systems with unknown time delays. The systems considered are dominated by a triangular system without zero dynamics satisfying linear growth in the unmeasurable states. The novelty of this article is that a universal-type adaptive output feedback controller is presented to time-delay systems, which can globally regulate all the states of the uncertain systems without knowing the growth rate. An illustrative example is provided to show the applicability of the developed control strategy.

  12. Adaptive control of an active magnetic bearing flywheel system using neural networks / Angelique Combrinck

    OpenAIRE

    Combrinck, Angelique

    2010-01-01

    The School of Electrical, Electronic and Computer Engineering at the North-West University in Potchefstroom has established an active magnetic bearing (AMB) research group called McTronX. This group provides extensive knowledge and experience in the theory and application of AMBs. By making use of the expertise contained within McTronX and the rest of the control engineering community, an adaptive controller for an AMB flywheel system is implemented. The adaptive controller is ...

  13. Adaptive sliding mode control of interleaved parallel boost converter for fuel cell energy generation system

    DEFF Research Database (Denmark)

    El Fadil, H.; Giri, F.; Guerrero, Josep M.

    2013-01-01

    This paper deals with the problem of controlling energy generation systems including fuel cells (FCs) and interleaved boost power converters. The proposed nonlinear adaptive controller is designed using sliding mode control (SMC) technique based on the system nonlinear model. The latter accounts...... for the boost converter large-signal dynamics as well as for the fuel-cell nonlinear characteristics. The adaptive nonlinear controller involves online estimation of the DC bus impedance ‘seen’ by the converter. The control objective is threefold: (i) asymptotic stability of the closed loop system......, (ii) output voltage regulation under bus impedance uncertainties and (iii) equal current sharing between modules. It is formally shown, using theoretical analysis and simulations, that the developed adaptive controller actually meets its control objectives....

  14. Decentralized direct adaptive neural network control for a class of interconnected systems

    Institute of Scientific and Technical Information of China (English)

    Zhang Tianping; Mei Jiandong

    2006-01-01

    The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconnections is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized direct adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local information. According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.

  15. Wavelet Adaptive Algorithm and Its Application to MRE Noise Control System

    Directory of Open Access Journals (Sweden)

    Zhang Yulin

    2015-01-01

    Full Text Available To address the limitation of conventional adaptive algorithm used for active noise control (ANC system, this paper proposed and studied two adaptive algorithms based on Wavelet. The twos are applied to a noise control system including magnetorheological elastomers (MRE, which is a smart viscoelastic material characterized by a complex modulus dependent on vibration frequency and controllable by external magnetic fields. Simulation results reveal that the Decomposition LMS algorithm (D-LMS and Decomposition and Reconstruction LMS algorithm (DR-LMS based on Wavelet can significantly improve the noise reduction performance of MRE control system compared with traditional LMS algorithm.

  16. Generalized projective synchronization of the fractional-order chaotic system using adaptive fuzzy sliding mode control

    International Nuclear Information System (INIS)

    An adaptive fuzzy sliding mode strategy is developed for the generalized projective synchronization of a fractional-order chaotic system, where the slave system is not necessarily known in advance. Based on the designed adaptive update laws and the linear feedback method, the adaptive fuzzy sliding controllers are proposed via the fuzzy design, and the strength of the designed controllers can be adaptively adjusted according to the external disturbances. Based on the Lyapunov stability theorem, the stability and the robustness of the controlled system are proved theoretically. Numerical simulations further support the theoretical results of the paper and demonstrate the efficiency of the proposed method. Moreover, it is revealed that the proposed method allows us to manipulate arbitrarily the response dynamics of the slave system by adjusting the desired scaling factor λi and the desired translating factor ηi, which may be used in a channel-independent chaotic secure communication. (general)

  17. Adaptive neural network tracking control for a class of unknown nonlinear time-delay systems

    Institute of Scientific and Technical Information of China (English)

    Chen Weisheng; Li Junmin

    2006-01-01

    For a class of unknown nonlinear time-delay systems, an adaptive neural network (NN) control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a robust memoryless adaptive NN tracking controller. Unknown time-delay functions are approximated by NNs, such that the requirement on the nonlinear time-delay functions is relaxed. Based on Lyapunov-Krasoviskii functional, the sem-global uniformly ultimately boundedness (UUB) of all the signals in the closed-loop system is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters. The feasibility is investigated by an illustrative simulation example.

  18. Adaptive Fuzzy Sliding Mode Tracking Control of Uncertain Underactuated Nonlinear Systems: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Faten Baklouti

    2016-01-01

    Full Text Available The trajectory tracking of underactuated nonlinear system with two degrees of freedom is tackled by an adaptive fuzzy hierarchical sliding mode controller. The proposed control law solves the problem of coupling using a hierarchical structure of the sliding surfaces and chattering by adopting different reaching laws. The unknown system functions are approximated by fuzzy logic systems and free parameters can be updated online by adaptive laws based on Lyapunov theory. Two comparative studies are made in this paper. The first comparison is between three different expressions of reaching laws to compare their abilities to reduce the chattering phenomenon. The second comparison is made between the proposed adaptive fuzzy hierarchical sliding mode controller and two other control laws which keep the coupling in the underactuated system. The tracking performances of each control law are evaluated. Simulation examples including different amplitudes of external disturbances are made.

  19. A Digitalized Gyroscope System Based on a Modified Adaptive Control Method.

    Science.gov (United States)

    Xia, Dunzhu; Hu, Yiwei; Ni, Peizhen

    2016-01-01

    In this work we investigate the possibility of applying the adaptive control algorithm to Micro-Electro-Mechanical System (MEMS) gyroscopes. Through comparing the gyroscope working conditions with the reference model, the adaptive control method can provide online estimation of the key parameters and the proper control strategy for the system. The digital second-order oscillators in the reference model are substituted for two phase locked loops (PLLs) to achieve a more steady amplitude and frequency control. The adaptive law is modified to satisfy the condition of unequal coupling stiffness and coupling damping coefficient. The rotation mode of the gyroscope system is considered in our work and a rotation elimination section is added to the digitalized system. Before implementing the algorithm in the hardware platform, different simulations are conducted to ensure the algorithm can meet the requirement of the angular rate sensor, and some of the key adaptive law coefficients are optimized. The coupling components are detected and suppressed respectively and Lyapunov criterion is applied to prove the stability of the system. The modified adaptive control algorithm is verified in a set of digitalized gyroscope system, the control system is realized in digital domain, with the application of Field Programmable Gate Array (FPGA). Key structure parameters are measured and compared with the estimation results, which validated that the algorithm is feasible in the setup. Extra gyroscopes are used in repeated experiments to prove the commonality of the algorithm.

  20. Chaos Synchronization on Parameters Adaptive Control for Chen Chaotic System

    Institute of Scientific and Technical Information of China (English)

    ZHOU Ping

    2003-01-01

    Chaos synchronization of Chen chaotic system for parameters unknown is discussed in this paper using a scalar output. Using the concept of conditional Lyapunov exponents, the negativity of all Lyapunov exponents shows the synchronization of transmitter systems with receiver systems even though system parametes are not known to receiver systems.

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

    Science.gov (United States)

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

    2016-04-01

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

  2. Adaptive neural control for a class of perturbed strict-feedback nonlinear time-delay systems.

    Science.gov (United States)

    Wang, Min; Chen, Bing; Shi, Peng

    2008-06-01

    This paper proposes a novel adaptive neural control scheme for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients. Based on the radial basis function neural network online approximation capability, an adaptive neural controller is presented by combining the backstepping approach and Lyapunov-Krasovskii functionals. The proposed controller guarantees the semiglobal boundedness of all the signals in the closed-loop system and contains minimal learning parameters. Finally, three simulation examples are given to demonstrate the effectiveness and applicability of the proposed scheme.

  3. Application of Neurocomputing in Adaptive Control of Large-Scale Aerospace Systems

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    We are engaged in solving two difficult problems in adaptive control of the large-scale time-variant aerospacesystem. One is parameter identification of time-variant continuous-time state-space model; the other is how to solvealgebraic Riccati equation(ARE) of large order efficiently. In our approach, two neural networks are employed toindependently solve both the system identification problem and the ARE associated with the optimal control problem.Thus the identification and the control computation are combined in closed-loop, adaptive, real-time control system . Theadvantage of this approach is that the neural networks converge to their solutions very quickly and simultaneously.

  4. Adaptive Sliding Control for a Class of Fractional Commensurate Order Chaotic Systems

    Directory of Open Access Journals (Sweden)

    Jian Yuan

    2015-01-01

    Full Text Available This paper proposes adaptive sliding mode control design for a class of fractional commensurate order chaotic systems. We firstly introduce a fractional integral sliding manifold for the nominal systems. Secondly we prove the stability of the corresponding fractional sliding dynamics. Then, by introducing a Lyapunov candidate function and using the Mittag-Leffler stability theory we derive the desired sliding control law. Furthermore, we prove that the proposed sliding manifold is also adapted for the fractional systems in the presence of uncertainties and external disturbances. At last, we design a fractional adaptation law for the perturbed fractional systems. To verify the viability and efficiency of the proposed fractional controllers, numerical simulations of fractional Lorenz’s system and Chen’s system are presented.

  5. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Joint power control has advantages of multi-user detection and power control; and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system was designed. Simulation results show that the algorithm can control the power not only quickly but also precisely with a time change. The method is useful for increasing system capacity.

  6. Neural model-based adaptive control for systems with unknown Preisach-type hysteresis

    Institute of Scientific and Technical Information of China (English)

    Chuntao LI; Yonghong TAN

    2004-01-01

    An adaptive control scheme is presented for systems with unknown hysteresis. In order to handle the case where the hysteresis output is unmeasurale, a novel model is firstly developed to describe the characteristic of hysteresis. This model is motivated by Preisach model but implemented by using neural networks (NN). The main advantage is that it is easily used for controller design. Then, the adaptive controller based on the proposed model is presented for a class of SISO nonlinear systems preceded by unknown hysteresis, which is estimated by the proposed model. The laws for model updating and the control laws for the neural adaptive controller are derived from Lyapunov stability theorem, therefore the semi- global stability of the closed-loop system is guaranteed. At last, the simulation results are illustrated.

  7. L1 adaptive controller of nonlinear reference system in presence of unmatched uncertainties

    Institute of Scientific and Technical Information of China (English)

    宋海涛; 张涛; 张国良

    2016-01-01

    An extension of L1 adaptive control is proposed for the unmatched uncertain nonlinear system with the nonlinear reference system that defines the performance specifications. The control law adapts fast and tracks the reference system with the guaranteed robustness and transient performance in the presence of unmatched uncertainties. The interval analysis is used to build the quasi-linear parameter-varying model of unmatched nonlinear system, and the robust stability of the proposed controller is addressed by sum of squares programming. The transient performance analysis shows that within the limit of hardware a large adaption gain can improve the asymptotic tracking performance. Simulation results are provided to demonstrate the theoretical findings of the proposed controller.

  8. Programmable System on Chip Distributed Communication and Control Approach for Human Adaptive Mechanical System

    Directory of Open Access Journals (Sweden)

    Ahmad A.M. Faudzi

    2010-01-01

    Full Text Available Problem statement: Communication and control are two main components in any Mechatronics system. They can be designed either by centralized or decentralized approach. Both approaches can be chosen based on application designed and specific requirements of the designer. In this study, decentralized or normally called distributed approach was selected to solved communication and control of a human adaptive mechanical system namely Intelligent Chair Tools (ICT. The ICT seating system is powered by thirty six intelligent pneumatic actuators to facilitate investigation of chair shapes from spring and damping effect of seating and backrest surface. Three studies are proposed from the sitting experiments namely chair shapes, chair spring and chair damping properties. Approach: PSoC microcontroller was selected based on its features of having configurable analog and digital blocks. Its flexible modules and programmable peripherals ease designer in designing the communication and control of ICT in improved and faster way. Three protocols of USB, SPI and I2C were used for the communication system of ICT using PSoC. Flow charts of each communication protocols algorithms were discussed. On the other hand, the control system used PSoC’s ADC and counter modules to read inputs of pressure and encoder respectively. PWM module is used to control the valve and data communication was achieved using I2C module. Block diagram of unified control was discussed for further understandings of the control algorithms. Results: The PSoC specification, development design and experimental evaluation of ICT system are presented and discussed. Three studies of chair shapes, chair spring property and chair damping property from sitting experiment were shown. Conclusion/Recommendations: The PSoC microcontroller selection was discussed and application of its distributed communication and control was successfully applied to ICT. This distributed approach can be applied to other

  9. Indirect adaptive fuzzy control for a class of nonlinear discrete-time systems

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    An indirect adaptive fuzzy control scheme is developed for a class of nonlinear discrete-time systems. In this method, two fuzzy logic systems are used to approximate the unknown functions, and the parameters of membership functions in fuzzy logic systems are adjusted according to adaptive laws for the purpose of controlling the plant to track a reference trajectory. It is proved that the scheme can not only guarantee the boundedness of the input and output of the closed-loop system, but also make the tracking error converge to a small neighborhood of the origin. Simulation results indicate the effectiveness of this scheme.

  10. Distributed Adaptive Droop Control for DC Distribution Systems

    DEFF Research Database (Denmark)

    Nasirian, Vahidreza; Davoudi, Ali; Lewis, Frank;

    2014-01-01

    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...... the local perunit current of each converter with the neighbors’ on a communication graph and, accordingly, provides an impedance correction term. This term is then used to update the droop coefficient and synchronize per-unit currents or, equivalently, provide proportional load sharing. The proposed...

  11. Nonlinear adaptive control systems design of BTT missile based on fully tuned RBF neural networks

    Science.gov (United States)

    Hu, Yunan; Jin, Yuqiang; Li, Jing

    2003-09-01

    Based on fully tuned RBF neural networks and backstepping control techniques, a novel nonlinear adaptive control scheme is proposed for missile control systems with a general set of uncertainties. The effect of the uncertainties is synthesized one term in the design procedure. Then RBF neural networks are used to eliminate its effect. The nonlinear adaptive controller is designed using backstepping control techniques. The control problem is resolved while the control coefficient matrix is unknown. The adaptive tuning rules for updating all of the parameters of the fully tuned RBF neural networks are firstly derived by the Lyapunov stability theorem. Finally, nonlinear 6-DOF numerical simulation results for a BTT missile model are presented to demonstrate the effectiveness of the proposed method.

  12. Multivariable output feedback robust adaptive tracking control design for a class of delayed systems

    Science.gov (United States)

    Mirkin, Boris; Gutman, Per-Olof

    2015-02-01

    In this paper, we develop a model reference adaptive control scheme for a class of multi-input multi-output nonlinearly perturbed dynamic systems with unknown time-varying state delays which is also robust with respect to an external disturbance with unknown bounds. The output feedback adaptive control scheme uses feedback actions only, and thus does not require a direct measurement of the command or disturbance signals. A suitable Lyapunov-Krasovskii type functional is introduced to design the adaptation algorithms and to prove stability.

  13. High-Order Stochastic Adaptive Controller Design with Application to Mechanical System

    OpenAIRE

    Jie Tian; Wei Feng; Yuzhen Wang

    2012-01-01

    The main purpose of this paper is to apply stochastic adaptive controller design to mechanical system. Firstly, by a series of coordinate transformations, the mechanical system can be transformed to a class of special high-order stochastic nonlinear system, based on which, a more general mathematical model is considered, and the smooth state-feedback controller is designed. At last, the simulation for the mechanical system is given to show the effectiveness of the design scheme.

  14. Robust Adaptive Neural Control of a Class of MIMO Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    HU Tingliang; ZHU Jihong; SUN Zengqi

    2007-01-01

    In this paper we present a robust adaptive control for a class of uncertain continuous time multiple input multiple output (MIMO) nonlinear systems. Multiple multi-layer neural networks are employed to approximate the uncertainty of the nonlinear functions,and robustifying control terms are used to compensate for approximation errors.All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis so that, under appropriate assumptions, semiglobal stability of the closed - loop system is guaranteed, and the tracking error asymptotically converges to zero. Simulations performed on a two-link robot manipulator illustrate the approach and its performance.

  15. Decentralized adaptive robust controller design for complex system based on partition of unity

    Institute of Scientific and Technical Information of China (English)

    WANG Wenqing; HAN Chongzhao

    2007-01-01

    A new method for designing decentralized adaptive robust controllers was proposed which focuses on a class of more general uncertain complex systems,using the concept of the partition of unity in differential geometry to deal with system uncertainties.In this method the uncertainty of the system to be controlled was normalized firstly,and then the partition of unity that was subordinated to an open covering of state variables compact set was constructed.Subsequently the approximation was realized by using its property that can approximate nonlinear continuous function with arbitrary precision,and then the decentralized adaptive robust controller of complex systems and adaptive laws of approximate parameter estimation were designed.Compared to existing methods,the proposed algorithm requires simpler assumed conditions and no complicated computations.Simulation result shows that the method is valid.

  16. Non-linear and adaptive control of a refrigeration system

    OpenAIRE

    Rasmussen, Henrik,; Larsen, Lars F. S.

    2011-01-01

    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 u...

  17. Adaptive control of stochastic Hammerstein-Wiener nonlinear systems with measurement noise

    Science.gov (United States)

    Zhang, Bi; Mao, Zhizhong

    2016-01-01

    This paper deals with the adaptive control of a class of stochastic Hammerstein-Wiener nonlinear systems with measurement noise. Despite the fundamental progress achieved so far, a general theory framework about adaptive control of Hammerstein-Wiener models is still absent. Such situation is mainly due to the lack of an appropriate parameterisation model. To this end, this paper presents a novel parameterisation model that is to replace unmeasurable internal variables with their estimations. Then, the adaptive control algorithm to be applied is derived on the basis of self-tuning control. In addition, due to the use of the internal variable estimations, the stability and convergence properties are different from the self-tuning control. Our aim, in theoretical analysis, is to discover what limitations are in using the estimations instead of the true values in a control algorithm. Representative numerical examples are given and the simulation results verify the theoretical analysis.

  18. Terminal Sliding Mode Control with Adaptive Law for Uncertain Nonlinear System

    Directory of Open Access Journals (Sweden)

    Zhanshan Zhao

    2015-01-01

    Full Text Available A novel nonsingular terminal sliding mode controller is proposed for a second-order system with unmodeled dynamics uncertainties and external disturbances. We need not achieve the knowledge for boundaries of uncertainties and external disturbances in advance. The adaptive control gains are obtained to estimate the uncertain parameters and external disturbances which are unknown but bounded. The closed loop system stability is ensured with robustness and adaptation by the Lyapunov stability theorem in finite time. An illustrative example of second-order nonlinear system with unmodeled dynamics and external disturbances is given to demonstrate the effectiveness of the presented scheme.

  19. TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

    DEFF Research Database (Denmark)

    Yao, Wei; Fang, Jiakun; Zhao, Ping;

    2013-01-01

    the characteristics of the conventional PID, but adjust the parameters of PID controller online using identified Jacobian information from RBFNN. Hence, it has strong adaptability to the variation of the system operating condition. The effectiveness of the proposed controller is tested on a two-machine five-bus power...

  20. Research on Improved Adaptive Control for Static Synchronous Compensator in Power System

    Directory of Open Access Journals (Sweden)

    Chao Zhang

    2015-01-01

    Full Text Available This paper deals with the problems of “explosion of term,” uncertain parameter in static synchronous compensator (STATCOM system with nonlinear time-delay. An improved adaptive controller is proposed to enhance the transient stability of system states and reduce computational complexity of STATCOM control system. In contrast to backstepping control scheme in high order systems, the problem of “explosion of term” is avoided by designing dynamic surface controller. The low pass filter is included to allow a design where the model is not differentiated and thus has prevented the mathematical complexities effectively. In addition, unlike the traditional adaptive control schemes, the certainty equivalence principle is not required for estimating the uncertain parameter by system immersion and manifold invariant (I&I adaptive control. A smooth function is added to ensure that the estimation error converges to zero in finite time. The effectiveness of the proposed controller is verified by the simulations. Compared with adaptive backstepping and proportion integration differentiation (PID, the oscillation amplitudes of transient response are reduced by nearly half, and the time of reaching steady state is shortened by at least 11%.

  1. Adaptive discrete-time sliding-mode control of nonlinear systems described by Wiener models

    Science.gov (United States)

    Salhi, Houda; Kamoun, Samira; Essounbouli, Najib; Hamzaoui, Abdelaziz

    2016-03-01

    In this paper, we propose an adaptive control scheme that can be applied to nonlinear systems with unknown parameters. The considered class of nonlinear systems is described by the block-oriented models, specifically, the Wiener models. These models consist of dynamic linear blocks in series with static nonlinear blocks. The proposed adaptive control method is based on the inverse of the nonlinear function block and on the discrete-time sliding-mode controller. The parameters adaptation are performed using a new recursive parametric estimation algorithm. This algorithm is developed using the adjustable model method and the least squares technique. A recursive least squares (RLS) algorithm is used to estimate the inverse nonlinear function. A time-varying gain is proposed, in the discrete-time sliding mode controller, to reduce the chattering problem. The stability of the closed-loop nonlinear system, with the proposed adaptive control scheme, has been proved. An application to a pH neutralisation process has been carried out and the simulation results clearly show the effectiveness of the proposed adaptive control scheme.

  2. An Observer-Based Adaptive Iterative Learning Control Using Filtered-FNN Design for Robotic Systems

    OpenAIRE

    Ying-Chung Wang; Chiang-Ju Chien

    2014-01-01

    An observer-based adaptive iterative learning control using a filtered fuzzy neural network is proposed for repetitive tracking control of robotic systems. A state tracking error observer is introduced to design the iterative learning controller using only the measurement of joint position. We first derive an observation error model based on the state tracking error observer. Then, by introducing some auxiliary signals, the iterative learning controller is proposed based on the use of an aver...

  3. Adaptive Backstepping controller design and implementation for a matrix-converter-based IM drive system

    Directory of Open Access Journals (Sweden)

    R.R. Joshi

    2007-06-01

    Full Text Available A systematic controller design and implementation for a matrix-converter-based induction motor drive system is proposed. A nonlinear adaptive backstepping controller is proposed to improve the speed and position responses of the induction motor system. By using the proposed adaptive backstepping controller, the system can track a time-varying speed command and a time-varying position command well. Moreover, the system has a good load disturbance rejection capability. The realization of the controller is very simple. All of the control loops, including the current loop, speed loop and position loop, are implemented by a digital signal processor. Several experimental results are given to validate the theoretical analysis.

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

    CERN Document Server

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

    2014-01-01

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

  5. ADAPTIVE PRACTICAL OUTPUT MANEUVERING CONTROL FOR A CLASS OF NONLINEAR SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    Chunling WEI; Yuqiang WU; Shumin FEI

    2007-01-01

    This paper deals with the adaptive practical output maneuvering control problems for a class of nonlinear systems with uncontrollable unstable linearization.The objective is to design a smooth adaptive maneuvering controller to solve the geometric and dynamic tasks with an arbitrary small steady tracking error.The method of adding a power integrator and the robust recursive design technique are employed to force the system output to track a desired path and make the tracking speed to follow a desired speed along the path.An example is considered and simulation results are given.The proposed design procedure can be illustrated by the use of this example.

  6. Adaptive Fuzzy Control for Uncertain Fractional-Order Financial Chaotic Systems Subjected to Input Saturation

    Science.gov (United States)

    Wang, Chenhui

    2016-01-01

    In this paper, control of uncertain fractional-order financial chaotic system with input saturation and external disturbance is investigated. The unknown part of the input saturation as well as the system’s unknown nonlinear function is approximated by a fuzzy logic system. To handle the fuzzy approximation error and the estimation error of the unknown upper bound of the external disturbance, fractional-order adaptation laws are constructed. Based on fractional Lyapunov stability theorem, an adaptive fuzzy controller is designed, and the asymptotical stability can be guaranteed. Finally, simulation studies are given to indicate the effectiveness of the proposed method. PMID:27783648

  7. Complete synchronization of uncertain chaotic systems via a single proportional adaptive controller: A comparative study

    Energy Technology Data Exchange (ETDEWEB)

    Ahmad, Israr, E-mail: iak-2000plus@yahoo.com; Saaban, Azizan Bin, E-mail: azizan.s@uum.edu.my; Ibrahim, Adyda Binti, E-mail: adyda@uum.edu.my [School of Quantitative Sciences, College of Arts & Sciences, UUM (Malaysia); Shahzad, Mohammad, E-mail: dmsinfinite@gmail.com [College of Applied Sciences Nizwa, Ministry of Higher Education, Sultanate of Oman (Oman)

    2015-12-11

    This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.

  8. Research of robust adaptive trajectory linearization control based on T-S fuzzy system

    Institute of Scientific and Technical Information of China (English)

    Jiang Changsheng; Zhang Chunyu; Zhu Liang

    2008-01-01

    A robust adaptive trajectory linearization control (RATLC) algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.

  9. STATE-FEEDBACK ADAPTIVE STABILIZING CONTROL DESIGN FOR A CLASS OF HIGH-ORDER NONLINEAR SYSTEMS WITH UNKNOWN CONTROL COEFFICIENTS

    Institute of Scientific and Technical Information of China (English)

    Zongyao SUN; Yungang LIU

    2007-01-01

    In this paper, a new approach is successfully addressed to design the state-feedback adaptive stabilizing control law for a class of high-order nonlinear systems in triangular form and with unknown and nonidentical control coefficients, whose stabilizing control has been investigated recently under the knowledge that the lower bounds of the control coefficients are exactly known. In the present paper,without any knowledge of the lower bounds of the control coefficients, based on the adaptive technique and appropriately choosing design parameters, we give the recursive design procedure of the stabilizing control law by utilizing the approach of adding a power integrator together with tuning functions. The state-feedback adaptive control law designed not only preserves the equilibrium at the origin, but also guarantees the global asymptotic stability of the closed-loop states and the uniform boundedness of all the other closed-loop signals.

  10. 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.

  11. Adaptive Robust Actuator Fault Accommodation for a Class of Uncertain Nonlinear Systems with Unknown Control Gains

    Directory of Open Access Journals (Sweden)

    Yuefei Wu

    2014-01-01

    Full Text Available An adaptive robust fault tolerant control approach is proposed for a class of uncertain nonlinear systems with unknown signs of high-frequency gain and unmeasured states. In the recursive design, neural networks are employed to approximate the unknown nonlinear functions, K-filters are designed to estimate the unmeasured states, and a dynamical signal and Nussbaum gain functions are introduced to handle the unknown sign of the virtual control direction. By incorporating the switching function σ algorithm, the adaptive backstepping scheme developed in this paper does not require the real value of the actuator failure. It is mathematically proved that the proposed adaptive robust fault tolerant control approach can guarantee that all the signals of the closed-loop system are bounded, and the output converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by the simulation examples.

  12. Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

    Science.gov (United States)

    Chen, Mou; Tao, Gang

    2016-08-01

    In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems. PMID:26340792

  13. Adaptive Fuzzy Control System of Servomechanism for Electro-Discharge Machining Combined with Ultrasonic Vibration

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    For electro-discharge machining, only in the optimum state could the highest material removal rate be realized. In practical machining process, the timely elevation of the tool electrode is needed to eliminate chipping, which ordinarily occupies quite a lot of time. Therefore, besides the control of the machining parameters, the control of the optimum discharge gap and the conversion of different machining states is also needed. In this paper, the adaptive fuzzy control system of servomechanism for EDM co...

  14. Adaptive Neural Control for a Class of Outputs Time-Delay Nonlinear Systems

    Directory of Open Access Journals (Sweden)

    Ruliang Wang

    2012-01-01

    Full Text Available This paper considers an adaptive neural control for a class of outputs time-delay nonlinear systems with perturbed or no. Based on RBF neural networks, the radius basis function (RBF neural networks is employed to estimate the unknown continuous functions. The proposed control guarantees that all closed-loop signals remain bounded. The simulation results demonstrate the effectiveness of the proposed control scheme.

  15. A New Hyperchaotic System and the Synchronization Using Active Variable Universe Adaptive Fuzzy Controller

    Directory of Open Access Journals (Sweden)

    Baojie Zhang

    2013-01-01

    Full Text Available This paper presents a new hyperchaotic system by introducing an additional state variable into Lorenz system. The system’s characteristics, including the dissipativity, equilibrium, and Lyapunov exponents, are studied. A controller is developed which consists of an active control term and a variable universe adaptive fuzzy system. By using this controller, the synchronization of the new hyperchaotic systems with uncertain linear part is accomplished according to Lyapunov’s direct method. Simulation results illustrate the effectiveness of the proposed method.

  16. Robust Adaptive Backstepping Control Design for a Nonlinear Hydraulic-Mechanical System

    DEFF Research Database (Denmark)

    Choux, Martin; Karimi, Hamid Reza; Hovland, Geir;

    2009-01-01

    The complex dynamics that characterize hydraulic systems make it difficult for the control design to achieve prescribed goals in an efficient manner. In this paper, we present the design and analysis of a robust nonlinear controller for a nonlinear hydraulic-mechanical (NHM) system. The system...... consists of an electrohydraulic servo valve and two hydraulic cylinders. Specifically, by considering a part of the dynamics of the NHM system as a norm-bounded uncertainty, two adaptive controllers are developed based on the backstepping technique that ensure the tracking error signals asymptotically...... the Lyapunov functional method and inequality techniques. Simulation results demonstrate the performance and feasibility of the proposed method....

  17. Robust synchronization of chaotic non-autonomous systems using adaptive-feedback control

    Energy Technology Data Exchange (ETDEWEB)

    Lei Youming [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)]. E-mail: leiyouming@nwpu.edu.cn; Xu Wei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Shen Jianwei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)

    2007-01-15

    In this paper, we apply the simple adaptive-feedback control scheme to synchronize a class of chaotic non-autonomous systems. Based on the invariance principle of differential equations, some generic sufficient conditions for global asymptotic synchronization are obtained. Unlike the usual linear feedback, the variable feedback strength is automatically adapted to completely synchronize two identical systems and simple to implement in practice. As illustrative examples, synchronization of two parametrically excited chaotic pendulums and that of two 4D new systems are considered here. Numerical simulations show the proposed method is effective and robust against the effect of noise.

  18. Adaptive Neuro Fuzzy Inference System Based DTC Control for Matrix Converter

    Directory of Open Access Journals (Sweden)

    Venugopal Chitra

    2012-04-01

    Full Text Available In this study an Adaptive Neuro Fuzzy Inference System is introduced to select the switching states of Matrix Converters. Matrix converters have received more attention in research and industrial application due its advantages like four quadrant operation, sinusoidal input and output waveforms, controllable displacement factor, less number of switches etc., Matrix Converters are efficient in speed control of Induction motors than the conventional converters. There are two different control techniques namely field oriented control and Direct Torque Control systems available for closed loop operation of induction motors. The Direct Torque Control technique provides control of torque and flux directly. The major drawback of Direct Torque Control technique is the presence of ripples in torque and flux curves. This due to the presence of two level and three level hysteresis controllers in torque and flux control stages respectively. Also the conventional space vector and look up table method of switching state selection reduces the accuracy of switch state selection in the appropriate time width. This reduces the speed control performance of the motor. Also in this paper the hysteresis controllers are replaced by fuzzy controllers. the complete ANFIS based DTC for Matrix Converter is simulated in MATLAB/SIMULINK and the results shows that the use of Adaptive neuro fuzzy inference in Matrix Converter system increases the speed control performance of Induction Motor.

  19. Adaptive impedance control of a hydraulic suspension system using particle swarm optimisation

    Science.gov (United States)

    Fateh, Mohammad Mehdi; Moradi Zirkohi, Majid

    2011-12-01

    This paper presents a novel active control approach for a hydraulic suspension system subject to road disturbances. A novel impedance model is used as a model reference in a particular robust adaptive control which is applied for the first time to the hydraulic suspension system. A scheme is introduced for selecting the impedance parameters. The impedance model prescribes a desired behaviour of the active suspension system in a wide range of different road conditions. Moreover, performance of the control system is improved by applying a particle swarm optimisation algorithm for optimising control design parameters. Design of the control system consists of two interior loops. The inner loop is a force control of the hydraulic actuator, while the outer loop is a robust model reference adaptive control (MRAC). This type of MRAC has been applied for uncertain linear systems. As another novelty, despite nonlinearity of the hydraulic actuator, the suspension system and the force loop together are presented as an uncertain linear system to the MRAC. The proposed control method is simulated on a quarter-car model. Simulation results show effectiveness of the method.

  20. ADAPTIVE FLIGHT CONTROL SYSTEM OF ARMED HELICOPTER USING WAVELET NEURAL NETWORK METHOD

    Institute of Scientific and Technical Information of China (English)

    ZHURong-gang; JIANGChangsheng; FENGBin

    2004-01-01

    A discussion is devoted to the design of an adaptive flight control system of the armed helicopter using wavelet neural network method. Firstly, the control loop of the attitude angle is designed with a dynamic inversion scheme in a quick loop and a slow loop. respectively. Then, in order to compensate the error caused by dynamic inversion, the adaptive flight control system of the armed helicopter using wavelet neural network method is put forward, so the BP wavelet neural network and the Lyapunov stable wavelet neural network are used to design the helicopter flight control system. Finally, the typical maneuver flight is simulated to demonstrate its validity and effectiveness. Result proves that the wavelet neural network has an engineering practical value and the effect of WNN is good.

  1. 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. PMID:26219099

  2. 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.

  3. Design of control adaptability system model for TV media organization structure

    Institute of Scientific and Technical Information of China (English)

    WANG Dong-dong; WANG Ya-lin; MA Tao

    2008-01-01

    To resolve the control adaptability problem of TV media in complex competitive environment, a con-trol system model of TV media organization structure was designed. Based on the designed system model for TV media organization structure, the relations among the main factors of the system constitution, missions, organi-zing decision entity, and carrying bodies were analyzed. By means of applying multi-objective decision method and complex control system theory, and combining the integration model of TV media organization structure, the basic model was concluded and the corresponding parameters were designed. The current organization process of TV media is analyzed by this model, which comes to the adaptability appearance with different parameters. The results indicate that the model can estimate current TV media organization structure for the chain appearance of communications and the correlation between platforms and policy-making agencies.

  4. Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems.

    Science.gov (United States)

    Vrabie, Draguna; Lewis, Frank

    2009-04-01

    In this paper we present in a continuous-time framework an online approach to direct adaptive optimal control with infinite horizon cost for nonlinear systems. The algorithm converges online to the optimal control solution without knowledge of the internal system dynamics. Closed-loop dynamic stability is guaranteed throughout. The algorithm is based on a reinforcement learning scheme, namely Policy Iterations, and makes use of neural networks, in an Actor/Critic structure, to parametrically represent the control policy and the performance of the control system. The two neural networks are trained to express the optimal controller and optimal cost function which describes the infinite horizon control performance. Convergence of the algorithm is proven under the realistic assumption that the two neural networks do not provide perfect representations for the nonlinear control and cost functions. The result is a hybrid control structure which involves a continuous-time controller and a supervisory adaptation structure which operates based on data sampled from the plant and from the continuous-time performance dynamics. Such control structure is unlike any standard form of controllers previously seen in the literature. Simulation results, obtained considering two second-order nonlinear systems, are provided. PMID:19362449

  5. Functional Based Adaptive and Fuzzy Sliding Controller for Non-Autonomous Active Suspension System

    Science.gov (United States)

    Huang, Shiuh-Jer; Chen, Hung-Yi

    In this paper, an adaptive sliding controller is developed for controlling a vehicle active suspension system. The functional approximation technique is employed to substitute the unknown non-autonomous functions of the suspension system and release the model-based requirement of sliding mode control algorithm. In order to improve the control performance and reduce the implementation problem, a fuzzy strategy with online learning ability is added to compensate the functional approximation error. The update laws of the functional approximation coefficients and the fuzzy tuning parameters are derived from the Lyapunov theorem to guarantee the system stability. The proposed controller is implemented on a quarter-car hydraulic actuating active suspension system test-rig. The experimental results show that the proposed controller suppresses the oscillation amplitude of the suspension system effectively.

  6. AI-based adaptive control and design of autopilot system for nonlinear UAV

    Indian Academy of Sciences (India)

    Anil Kumar Yadav; Prerna Gaur

    2014-08-01

    The objective of this paper is to design an autopilot system for unmanned aerial vehicle (UAV) to control the speed and altitude using electronic throttle control system (ETCS) and elevator, respectively. A DC servo motor is used for designing of ETCS to control the throttle position for appropriate amount of air mass flow. 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 altitude controls are to achieve a wide range of air speed, improved energy efficiency and fuel economy with reduced pollutant emission. The energy efficiency using specific energy rate per velocity of UAV is also presented in this paper.

  7. Non-certainty Equivalent Adaptive Exciting Control of Multi-machine Power Systems

    OpenAIRE

    Xiujuan Dong; Shengtao Li; Nan Jiang; Yuanwei Jing

    2013-01-01

    Transient stability problem for multi-machine infinite bus system with the generator excitation was addressed via the non-certainty equivalent nonlinear re-parameterization method. The system need not to be linearized. The damping coefficient uncertainty was considered. A non-certainty equivalent excitation controller and a novel parameter updating law were obtained simultaneously via adaptive backstepping and Lyapunov methods to achieve stability of the error systems. Simulation results show...

  8. Global adaptive output feedback control for a class of nonlinear time-delay systems.

    Science.gov (United States)

    Zhai, Jun-yong; Zha, Wen-ting

    2014-01-01

    This paper addresses the problem of global output feedback control for a class of nonlinear time-delay systems. The nonlinearities are dominated by a triangular form satisfying linear growth condition in the unmeasurable states with an unknown growth rate. With a change of coordinates, a linear-like controller is constructed, which avoids the repeated derivatives of the nonlinearities depending on the observer states and the dynamic gain in backstepping approach and therefore, simplifies the design procedure. Using the idea of universal control, we explicitly construct a universal-type adaptive output feedback controller which globally regulates all the states of the nonlinear time-delay systems.

  9. Adaptive Fuzzy Control of Strict-Feedback Nonlinear Time-Delay Systems With Unmodeled Dynamics.

    Science.gov (United States)

    Yin, Shen; Shi, Peng; Yang, Hongyan

    2016-08-01

    In this paper, an approximated-based adaptive fuzzy control approach with only one adaptive parameter is presented for a class of single input single output strict-feedback nonlinear systems in order to deal with phenomena like nonlinear uncertainties, unmodeled dynamics, dynamic disturbances, and unknown time delays. Lyapunov-Krasovskii function approach is employed to compensate the unknown time delays in the design procedure. By combining the advances of the hyperbolic tangent function with adaptive fuzzy backstepping technique, the proposed controller guarantees the semi-globally uniformly ultimately boundedness of all the signals in the closed-loop system from the mean square point of view. Two simulation examples are finally provided to show the superior effectiveness of the proposed scheme. PMID:26302525

  10. Adaptive Fuzzy Control of Strict-Feedback Nonlinear Time-Delay Systems With Unmodeled Dynamics.

    Science.gov (United States)

    Yin, Shen; Shi, Peng; Yang, Hongyan

    2016-08-01

    In this paper, an approximated-based adaptive fuzzy control approach with only one adaptive parameter is presented for a class of single input single output strict-feedback nonlinear systems in order to deal with phenomena like nonlinear uncertainties, unmodeled dynamics, dynamic disturbances, and unknown time delays. Lyapunov-Krasovskii function approach is employed to compensate the unknown time delays in the design procedure. By combining the advances of the hyperbolic tangent function with adaptive fuzzy backstepping technique, the proposed controller guarantees the semi-globally uniformly ultimately boundedness of all the signals in the closed-loop system from the mean square point of view. Two simulation examples are finally provided to show the superior effectiveness of the proposed scheme.

  11. Adaptive output feedback control for nonlinear time-delay systems using neural network

    Institute of Scientific and Technical Information of China (English)

    Weisheng CHEN; Junmin LI

    2006-01-01

    This paper extends the adaptive neural network (NN) control approaches to a class of unknown output feedback nonlinear time-delay systems. An adaptive output feedback NN tracking controller is designed by backstepping technique. NNs are used to approximate unknown functions dependent on time delay. Delay-dependent filters are introduced for state estimation. The domination method is used to deal with the smooth time-delay basis functions. The adaptive bounding technique is employed to estimate the upper bound of the NN approximation errors. Based on LyapunovKrasovskii functional, the semi-global uniform ultimate boundedness of all the signals in the closed-loop system is proved.The feasibility is investigated by two illustrative simulation examples.

  12. Decentralised nonlinear equilibrium point adaptive control of generator for improving multimachine power system transient stability

    Energy Technology Data Exchange (ETDEWEB)

    Wu, J.; Yokoyama, A. [Tokyo Univ., Tokyo (Japan); Lu, Q. [TsingHua Univ., Tsinghua (China); Goto, M. [Nagoya Univ., Nagoya (Japan); Konishi, H. [Hitachi Ltd. (Japan)

    2003-11-01

    Decentralised nonlinear control of generator excitation and turbine governor based on the feedback linearization approach is proposed. To make the proposed nonlinear control possess adaptive ability under the changing conditions of power systems, the extended observation decoupled state space in which mechanical power is considered as variable is proposed, and the local stability of the post fault equilibrium point is established rigorously from a mathematical viewpoint. Nonlinear simulations are performed in a three-machine power system and in the ten-machine West Japan power system, and the effectiveness of the proposed nonlinear control and the convergence characteristics of the post fault equilibrium point observer are validated. (Author)

  13. Adaptive randomized algorithms for analysis and design of control systems under uncertain environments

    Science.gov (United States)

    Chen, Xinjia

    2015-05-01

    We consider the general problem of analysis and design of control systems in the presence of uncertainties. We treat uncertainties that affect a control system as random variables. The performance of the system is measured by the expectation of some derived random variables, which are typically bounded. We develop adaptive sequential randomized algorithms for estimating and optimizing the expectation of such bounded random variables with guaranteed accuracy and confidence level. These algorithms can be applied to overcome the conservatism and computational complexity in the analysis and design of controllers to be used in uncertain environments. We develop methods for investigating the optimality and computational complexity of such algorithms.

  14. SELF-ADAPTIVE CONTROLS OF A COMPLEX CELLULAR SIGNALING TRANSDUCTION SYSTEM

    Institute of Scientific and Technical Information of China (English)

    LI Hong; ZHOU Zhiyuan; DAI Rongyang; LUO Bo; ZHENG Xiaoli; YANG Wenli; HE Tao; WU Minglu

    2004-01-01

    In cells, the interactions of distinct signaling transduction pathways originating from cross-talkings between signaling molecules give rise to the formation of signaling transduction networks, which contributes to the changes (emergency) of kinetic behaviors of signaling system compared with single molecule or pathway. Depending on the known experimental data, we have constructed a model for complex cellular signaling transduction system, which is derived from signaling transduction of epidermal growth factor receptor in neuron. By the computational simulating methods, the self-adaptive controls of this system have been investigated. We find that this model exhibits a relatively stable selfadaptive system, especially to over-stimulation of agonist, and the amplitude and duration of signaling intermediates in it could be controlled by multiple self-adaptive effects, such as "signal scattering", "positive feedback", "negative feedback" and "B-Raf shunt". Our results provide an approach to understanding the dynamic behaviors of complex biological systems.

  15. Robust Adaptive Control for a Class of Uncertain Nonlinear Systems with Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Ruliang Wang

    2013-01-01

    Full Text Available We present adaptive neural control design for a class of perturbed nonlinear MIMO time-varying delay systems in a block-triangular form. Based on a neural controller, it is obtained by constructing a quadratic-type Lyapunov-Krasovskii functional, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tracking error dynamics converge to a neighborhood of the desired trajectories. The simulation results demonstrate the effectiveness of the proposed control scheme.

  16. 3D positional control of magnetic levitation system using adaptive control: improvement of positioning control in horizontal plane

    Science.gov (United States)

    Nishino, Toshimasa; Fujitani, Yasuhiro; Kato, Norihiko; Tsuda, Naoaki; Nomura, Yoshihiko; Matsui, Hirokazu

    2012-01-01

    The objective of this paper is to establish a technique that levitates and conveys a hand, a kind of micro-robot, by applying magnetic forces: the hand is assumed to have a function of holding and detaching the objects. The equipment to be used in our experiments consists of four pole-pieces of electromagnets, and is expected to work as a 4DOF drive unit within some restricted range of 3D space: the three DOF are corresponding to 3D positional control and the remaining one DOF, rotational oscillation damping control. Having used the same equipment, Khamesee et al. had manipulated the impressed voltages on the four electric magnetics by a PID controller by the use of the feedback signal of the hand's 3D position, the controlled variable. However, in this system, there were some problems remaining: in the horizontal direction, when translating the hand out of restricted region, positional control performance was suddenly degraded. The authors propose a method to apply an adaptive control to the horizontal directional control. It is expected that the technique to be presented in this paper contributes not only to the improvement of the response characteristic but also to widening the applicable range in the horizontal directional control.

  17. Adaptive Harmonic Detection Control of Grid Interfaced Solar Photovoltaic Energy System with Power Quality Improvement

    Science.gov (United States)

    Singh, B.; Goel, S.

    2015-03-01

    This paper presents a grid interfaced solar photovoltaic (SPV) energy system with a novel adaptive harmonic detection control for power quality improvement at ac mains under balanced as well as unbalanced and distorted supply conditions. The SPV energy system is capable of compensation of linear and nonlinear loads with the objectives of load balancing, harmonics elimination, power factor correction and terminal voltage regulation. The proposed control increases the utilization of PV infrastructure and brings down its effective cost due to its other benefits. The adaptive harmonic detection control algorithm is used to detect the fundamental active power component of load currents which are subsequently used for reference source currents estimation. An instantaneous symmetrical component theory is used to obtain instantaneous positive sequence point of common coupling (PCC) voltages which are used to derive inphase and quadrature phase voltage templates. The proposed grid interfaced PV energy system is modelled and simulated in MATLAB Simulink and its performance is verified under various operating conditions.

  18. Cooperative control of multi-agent systems optimal and adaptive design approaches

    CERN Document Server

    Lewis, Frank L; Hengster-Movric, Kristian; Das, Abhijit

    2014-01-01

    Task complexity, communication constraints, flexibility and energy-saving concerns are all factors that may require a group of autonomous agents to work together in a cooperative manner. Applications involving such complications include mobile robots, wireless sensor networks, unmanned aerial vehicles (UAVs), spacecraft, and so on. In such networked multi-agent scenarios, the restrictions imposed by the communication graph topology can pose severe problems in the design of cooperative feedback control systems.  Cooperative control of multi-agent systems is a challenging topic for both control theorists and practitioners and has been the subject of significant recent research. Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs.  It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design.  B...

  19. Global adaptive stabilisation for nonlinear systems with unknown control directions and input disturbance

    Science.gov (United States)

    Man, Yongchao; Liu, Yungang

    2016-05-01

    This paper addresses the global adaptive stabilisation via switching and learning strategies for a class of uncertain nonlinear systems. Remarkably, the systems in question simultaneously have unknown control directions, unknown input disturbance and unknown growth rate, which makes the problem in question challenging to solve and essentially different from those in the existing literature. To solve the problem, an adaptive scheme via switching and learning is proposed by skilfully integrating the techniques of backstepping design, adaptive learning and adaptive switching. One key point in the design scheme is the introduction of the learning mechanism, in order to compensate the unknown input disturbance, and the other one is the design of the switching mechanism, through tuning the design parameters online to deal with the unknown control directions, unknown bound and period of input disturbance and unknown growth rate. The designed controller guarantees that all the signals of the resulting closed-loop systems are bounded, and furthermore, the closed-loop system states globally converge to zero.

  20. Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

    Science.gov (United States)

    Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

    2013-09-01

    In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

  1. An Adaptive Fuzzy-Logic Traffic Control System in Conditions of Saturated Transport Stream

    Science.gov (United States)

    Marakhimov, A. R.; Igamberdiev, H. Z.; Umarov, Sh. X.

    2016-01-01

    This paper considers the problem of building adaptive fuzzy-logic traffic control systems (AFLTCS) to deal with information fuzziness and uncertainty in case of heavy traffic streams. Methods of formal description of traffic control on the crossroads based on fuzzy sets and fuzzy logic are proposed. This paper also provides efficient algorithms for implementing AFLTCS and develops the appropriate simulation models to test the efficiency of suggested approach. PMID:27517081

  2. A Self-Adaptive Control Method for Uncertainty Systems Based on ANN with AEP

    Institute of Scientific and Technical Information of China (English)

    WANG Ping; YANG Ru-qing

    2007-01-01

    A self-adaptive control method is proposed basedon an artificial neural network(ANN) with acceleratedevolutionary programming(AEP.) algorithm. The neuralnetwork is used to model the uncertainty process, fromwhich the teacher signals are produced online to regulate theparameters of the controller. The accelerated evolutionaryprogramming is used to train the neural network. Theexperiment results show that the method can obviouslyimprove the dynamic performance of uncertainty systems.

  3. Smart monitoring system based on adaptive current control for superconducting cable test

    Energy Technology Data Exchange (ETDEWEB)

    Arpaia, Pasquale [Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Napoli (Italy); Technology Department, European Organization for Nuclear Research (CERN), 1217 Geneva (Switzerland); Ballarino, Amalia; Montenero, Giuseppe [Technology Department, European Organization for Nuclear Research (CERN), 1217 Geneva (Switzerland); Daponte, Vincenzo [Technology Department, European Organization for Nuclear Research (CERN), 1217 Geneva (Switzerland); Department of Electronics, Information, and Bioengineering, Polytechnic of Milan, 20133 Milano (Italy); Svelto, Cesare [Department of Electronics, Information, and Bioengineering, Polytechnic of Milan, 20133 Milano (Italy)

    2014-12-15

    A smart monitoring system for superconducting cable test is proposed with an adaptive current control of a superconducting transformer secondary. The design, based on Fuzzy Gain Scheduling, allows the controller parameters to adapt continuously, and finely, to the working variations arising from transformer nonlinear dynamics. The control system is integrated in a fully digital control loop, with all the related benefits, i.e., high noise rejection, ease of implementation/modification, and so on. In particular, an accurate model of the system, controlled by a Fuzzy Gain Scheduler of the superconducting transformer, was achieved by an experimental campaign through the working domain at several current ramp rates. The model performance was characterized by simulation, under all the main operating conditions, in order to guide the controller design. Finally, the proposed monitoring system was experimentally validated at European Organization for Nuclear Research (CERN) in comparison to the state-of-the-art control system [P. Arpaia, L. Bottura, G. Montenero, and S. Le Naour, “Performance improvement of a measurement station for superconducting cable test,” Rev. Sci. Instrum.83, 095111 (2012)] of the Facility for the Research on Superconducting Cables, achieving a significant performance improvement: a reduction in the system overshoot by 50%, with a related attenuation of the corresponding dynamic residual error (both absolute and RMS) up to 52%.

  4. INTELLIGENT CONTROL USING ADAPTIVE PID CONTROLLER

    OpenAIRE

    Dr. P. Vijayakumar; UNNIKRISHNAN P C

    2014-01-01

    In this paper an adaptive stable PID controller is briefly explained and validated by simulations and experimentation. The adaptive PID controller employs almost strict positive realness (ASPR) to ensure stability of the system. The design involves a parallel feedforward compensator (PFC) which guarantees the ASPRness of the controlled system. After a disturbance the dynamical system is assumed to be in one of a finite number of configurations, corresponding to each of which exist a stabilizi...

  5. Advanced Adaptive Particle Swarm Optimization based SVC Controller for Power System Stability

    Directory of Open Access Journals (Sweden)

    Poonam Singhal

    2014-12-01

    Full Text Available The interconnected systems is continually increasing in size and extending over whole geographical regions, it is becoming increasingly more difficult to maintain synchronism between various parts of the power system. This paper work presents an advanced adaptive Particle swarm optimization technique to optimize the SVC controller parameters for enhancement of the steady state stability & overcoming the premature convergence & stagnation problems as in basic PSO algorithm & Particle swarm optimization with shrinkage factor & inertia weight approach (PSO-SFIWA. In this paper SMIB system along with PID damped SVC controller is considered for study. The generator speed deviation is used as an auxiliary signal to SVC, to generate the desired damping. This controller improves the dynamic performance of power system by reducing the steady-state error. The controller parameters are optimized using basic PSO, PSO-SFIWA & Advanced Adaptive PSO. Computational results show that Advanced Adaptive based SVC controller is able to find better quality solution as compare to conventional PSO & PSO-SFIWA Techniques.

  6. Prescribed Performance Fuzzy Adaptive Output-Feedback Control for Nonlinear Stochastic Systems

    Directory of Open Access Journals (Sweden)

    Lili Zhang

    2014-01-01

    Full Text Available A prescribed performance fuzzy adaptive output-feedback control approach is proposed for a class of single-input and single-output nonlinear stochastic systems with unmeasured states. Fuzzy logic systems are used to identify the unknown nonlinear system, and a fuzzy state observer is designed for estimating the unmeasured states. Based on the backstepping recursive design technique and the predefined performance technique, a new fuzzy adaptive output-feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin with the prescribed performance bounds. A simulation example is provided to show the effectiveness of the proposed approach.

  7. Adaptive Jacobian Fuzzy Attitude Control for Flexible Spacecraft Combined Attitude and Sun Tracking System

    Science.gov (United States)

    Chak, Yew-Chung; Varatharajoo, Renuganth

    2016-07-01

    Many spacecraft attitude control systems today use reaction wheels to deliver precise torques to achieve three-axis attitude stabilization. However, irrecoverable mechanical failure of reaction wheels could potentially lead to mission interruption or total loss. The electrically-powered Solar Array Drive Assemblies (SADA) are usually installed in the pitch axis which rotate the solar arrays to track the Sun, can produce torques to compensate for the pitch-axis wheel failure. In addition, the attitude control of a flexible spacecraft poses a difficult problem. These difficulties include the strong nonlinear coupled dynamics between the rigid hub and flexible solar arrays, and the imprecisely known system parameters, such as inertia matrix, damping ratios, and flexible mode frequencies. In order to overcome these drawbacks, the adaptive Jacobian tracking fuzzy control is proposed for the combined attitude and sun-tracking control problem of a flexible spacecraft during attitude maneuvers in this work. For the adaptation of kinematic and dynamic uncertainties, the proposed scheme uses an adaptive sliding vector based on estimated attitude velocity via approximate Jacobian matrix. The unknown nonlinearities are approximated by deriving the fuzzy models with a set of linguistic If-Then rules using the idea of sector nonlinearity and local approximation in fuzzy partition spaces. The uncertain parameters of the estimated nonlinearities and the Jacobian matrix are being adjusted online by an adaptive law to realize feedback control. The attitude of the spacecraft can be directly controlled with the Jacobian feedback control when the attitude pointing trajectory is designed with respect to the spacecraft coordinate frame itself. A significant feature of this work is that the proposed adaptive Jacobian tracking scheme will result in not only the convergence of angular position and angular velocity tracking errors, but also the convergence of estimated angular velocity to

  8. An adaptive fuzzy design for fault-tolerant control of MIMO nonlinear uncertain systems

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    This paper presents a novel control method for accommodating actuator faults in a class of multiple-input multiple-output (MIMO) nonlinear uncertain systems.The designed control scheme can tolerate both the time-varying lock-in-place and loss of effectiveness actuator faults.In each subsystem of the considered MIMO system,the controller is obtained from a backstepping procedure;an adaptive fuzzy approximator with minimal learning parameterization is employed to approximate the package of unknown nonlinear f...

  9. Adaptive Synchronization of R?ssler System Based on Dynamic Surface Control

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A synchronization scheme for R?ssler system based on Dynamic Surface Control (DSC) is proposed in this paper. The DSC method is a recursive design procedure like conventional backstepping methods. Different from the backstepping design, a first-order filter is introduced in every DSC design step. For this introduced filter, the derivative of the selected virtual control is avoided and then the drawback of "explosion of complexity" existing in backstepping design is overcome. Moreover, adaptive method is used for controller design when the system parameters are unknown. Finally, a numerical example is given to illustrate the effectiveness and performance of the proposed method.

  10. STABILITY ANALYSIS OF DECENTRALIZED ADAPTIVE BACKSTEPPING CONTROL SYSTEMS WITH ACTUATOR FAILURES

    Institute of Scientific and Technical Information of China (English)

    Wei WANG; Changyun WEN; Guanghong YANG

    2009-01-01

    In this paper, the authors analyze the stability of a class of interconnected systems with subsystem unmodeled dynamics and dynamic interactions employing decentralized adaptive controllers designed by Wen, Zhou, and Wang (2008) in the presence of actuator failures. It will be shown that the global stability of the remaining closed-loop system is still ensured and the outputs are also regulated to zero when some subsystems break down.

  11. UAV Controller Based on Adaptive Neuro-Fuzzy Inference System and PID

    Directory of Open Access Journals (Sweden)

    Ali Moltajaei Farid

    2013-01-01

    Full Text Available ANFIS is combining a neural network with a fuzzy system results in a hybrid neuro-fuzzy system, capable of reasoning and learning in an uncertain and imprecise environment. In this paper, an adaptive neuro-fuzzy inference system (ANFIS is employed to control an unmanned aircraft vehicle (UAV.  First, autopilots structure is defined, and then ANFIS controller is applied, to control UAVs lateral position. The results of ANFIS and PID lateral controllers are compared, where it shows the two controllers have similar results. ANFIS controller is capable to adaptation in nonlinear conditions, while PID has to be tuned to preserves proper control in some conditions. The simulation results generated by Matlab using Aerosim Aeronautical Simulation Block Set, which provides a complete set of tools for development of six degree-of-freedom. Nonlinear Aerosonde unmanned aerial vehicle model with ANFIS controller is simulated to verify the capability of the system. Moreover, the results are validated by FlightGear flight simulator.

  12. Adaptive Sliding Mode Robust Control for Virtual Compound-Axis Servo System

    Directory of Open Access Journals (Sweden)

    Yan Ren

    2013-01-01

    Full Text Available A structure mode of virtual compound-axis servo system is proposed to improve the tracking accuracy of the ordinary optoelectric tracking platform. It is based on the structure and principles of compound-axis servo system. A hybrid position control scheme combining the PD controller and feed-forward controller is used in subsystem to track the tracking error of the main system. This paper analyzes the influences of the equivalent disturbance in main system and proposes an adaptive sliding mode robust control method based on the improved disturbance observer. The sliding mode technique helps this disturbance observer to deal with the uncompensated disturbance in high frequency by making use of the rapid switching control value, which is based on the subtle error of disturbance estimation. Besides, the high-frequency chattering is alleviated effectively in this proposal. The effectiveness of the proposal is confirmed by experiments on optoelectric tracking platform.

  13. Adaptive inverse control of air supply flow for proton exchange membrane fuel cell systems

    Institute of Scientific and Technical Information of China (English)

    LI Chun-hua; ZHU Xin-jian; SUI Sheng; HU Wan-qi; HU Ming-ruo

    2009-01-01

    To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control (AIC) strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell (PEMFC) system in this paper.The PEMFC stack and the air supply system including a compressor and a supply manifold are modeled for the purpose of performance analysis and controller design. A recurrent fuzzy neural network (RFNN) is utilized to identify the inverse model of the controlled system and generates a suitable control input during the abrupt step change of external disturbances.Compared with the PI controller, numerical simulations are performed to validate the effectiveness and advantages of the proposed AIC strategy.

  14. Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings

    Science.gov (United States)

    Chen, Po-Chang; Huang, An-Chyau

    2005-04-01

    An adaptive sliding controller is proposed in this paper for controlling a non-autonomous quarter-car suspension system with time-varying loadings. The bound of the car-body loading is assumed to be available. Then, the reference coordinate is placed at the static position under the nominal loading so that the system dynamic equation is derived. Due to spring nonlinearities, the system property becomes asymmetric after coordinate transformation. Besides, in practical cases, system parameters are not easy to be obtained precisely for controller design. Therefore, in this paper, system uncertainties are lumped into two unknown time-varying functions. Since the variation bound of one of the unknown functions is not available, conventional adaptive schemes and robust designs are not applicable. To deal with this problem, the function approximation technique is employed to represent the unknown function as a finite combination of basis functions. The Lyapunov direct method can thus be used to find adaptive laws for updating coefficients in the approximating series and to prove stability of the closed-loop system. Since the position and velocity measurements of the unsprung mass are lumped into the unknown function, there is no need to install sensors on the axle and wheel assembly in the actual implementation. Simulation results are presented to show the performance of the proposed strategy.

  15. Adaptive modeling, identification, and control of dynamic structural systems. I. Theory

    Science.gov (United States)

    Safak, Erdal

    1989-01-01

    A concise review of the theory of adaptive modeling, identification, and control of dynamic structural systems based on discrete-time recordings is presented. Adaptive methods have four major advantages over the classical methods: (1) Removal of the noise from the signal is done over the whole frequency band; (2) time-varying characteristics of systems can be tracked; (3) systems with unknown characteristics can be controlled; and (4) a small segment of the data is needed during the computations. Included in the paper are the discrete-time representation of single-input single-output (SISO) systems, models for SISO systems with noise, the concept of stochastic approximation, recursive prediction error method (RPEM) for system identification, and the adaptive control. Guidelines for model selection and model validation and the computational aspects of the method are also discussed in the paper. The present paper is the first of two companion papers. The theory given in the paper is limited to that which is necessary to follow the examples for applications in structural dynamics presented in the second paper.

  16. Non-certainty Equivalent Adaptive Exciting Control of Multi-machine Power Systems

    Directory of Open Access Journals (Sweden)

    Xiujuan Dong

    2013-07-01

    Full Text Available Transient stability problem for multi-machine infinite bus system with the generator excitation was addressed via the non-certainty equivalent nonlinear re-parameterization method. The system need not to be linearized. The damping coefficient uncertainty was considered. A non-certainty equivalent excitation controller and a novel parameter updating law were obtained simultaneously via adaptive backstepping and Lyapunov methods to achieve stability of the error systems. Simulation results showed that the proposed controller had good transient performance.  

  17. A neural learning classifier system with self-adaptive constructivism for mobile robot control.

    Science.gov (United States)

    Hurst, Jacob; Bull, Larry

    2006-01-01

    For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

  18. Decentralized adaptive fuzzy control of time-delayed interconnected systems with unknown backlash-like hysteresis

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The problem of decentralized adaptive fuzzy control for a class of time-delayed interconnected nonlinear systems with unknown backlash-like hystersis is discussed. On the basis of the principle of variable structure control (VSC) and by using the fuzzy systems with linear adjustable parameters that are used to approximate plant unknown functions, a novel decentralized adaptive fuzzy control strategy with a supervisory controller is developed. A general method, which is modeled the backlash-like hysteresis, is proposed and removes the assumption that the boundedness of disturbance, and the slope of the backlash-like hystersis are known constants. Furthermore, the interconnection term is supposed to be pth-order polynomial in time-delayed states. In addition, the plant dynamic uncertainty and modeling errors are adaptively compensated by adjusting the parameters and gains on-line for each subsystems. By theoretical analysis, it is shown that the closed-loop fuzzy control systems are globally stable, with tracking error converging to zero. Simulation results demonstrate the effectiveness of the approach.

  19. Distributed adaptive fuzzy iterative learning control of coordination problems for higher order multi-agent systems

    Science.gov (United States)

    Li, Jinsha; Li, Junmin

    2016-07-01

    In this paper, the adaptive fuzzy iterative learning control scheme is proposed for coordination problems of Mth order (M ≥ 2) distributed multi-agent systems. Every follower agent has a higher order integrator with unknown nonlinear dynamics and input disturbance. The dynamics of the leader are a higher order nonlinear systems and only available to a portion of the follower agents. With distributed initial state learning, the unified distributed protocols combined time-domain and iteration-domain adaptive laws guarantee that the follower agents track the leader uniformly on [0, T]. Then, the proposed algorithm extends to achieve the formation control. A numerical example and a multiple robotic system are provided to demonstrate the performance of the proposed approach.

  20. Adaptive Recurrent Network Network Uncertainty Observer Based Integral Backstepping Control for a PMSM Drive System

    Directory of Open Access Journals (Sweden)

    Chih-Hong Lin

    2012-03-01

    Full Text Available The permanent magnet synchronous motor (PMSM is suitable for high-performance servo applications and has been used widely for the industrial robots, computer-numerically-controlled (CNC machine tools and elevators. The control performance of the actual PMSM drive system depends on many parameters, such as parameter variations, external load disturbance, and friction force. Their relationships are complex and the actual PMSM drive system has the properties of nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate model for the nonlinear uncertainty and time-varying characteristics of the actual PMSM drive system Therefore, an adaptive recurrent neural network uncertainty observer (ARNNUO based integral backstepping control system is developed to overcome this problem in this paper. The proposed control strategy is based on integral backstepping control combined with RNN uncertainty observer to estimate the required lumped uncertainty. An adaptive rule of the RNN uncertainty observer is employed to on-line adjust the weights of sigmoidal functions by using the gradient descent method and the backpropagation algorithm in according to Lyapunov function. This ARNNUO has the on-line learning ability to respond to the system’s nonlinear and time-varying behaviors. Experimental results are executed to show the control performance of the proposed control scheme.

  1. Adaptive Neural-Sliding Mode Control of Active Suspension System for Camera Stabilization

    Directory of Open Access Journals (Sweden)

    Feng Zhao

    2015-01-01

    Full Text Available The camera always suffers from image instability on the moving vehicle due to the unintentional vibrations caused by road roughness. This paper presents a novel adaptive neural network based on sliding mode control strategy to stabilize the image captured area of the camera. The purpose is to suppress vertical displacement of sprung mass with the application of active suspension system. Since the active suspension system has nonlinear and time varying characteristics, adaptive neural network (ANN is proposed to make the controller robustness against systematic uncertainties, which release the model-based requirement of the sliding model control, and the weighting matrix is adjusted online according to Lyapunov function. The control system consists of two loops. The outer loop is a position controller designed with sliding mode strategy, while the PID controller in the inner loop is to track the desired force. The closed loop stability and asymptotic convergence performance can be guaranteed on the basis of the Lyapunov stability theory. Finally, the simulation results show that the employed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance.

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

    Indian Academy of Sciences (India)

    Abdurahman Kadir; Xing-Yuan Wang; Yu-Zhang Zhao

    2011-06-01

    In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is proposed. The proposed AFNC is comprised of a fuzzy neural controller and a robust controller. The fuzzy neural controller including a fuzzy neural network identifier (FNNI) is the principal controller. The FNNI is used for online estimation of the controlled system dynamics by tuning the parameters of fuzzy neural network (FNN). The Gaussian function, a specific example of radial basis function, is adopted here as a membership function. So, the tuning parameters include the weighting factors in the consequent part and the means and variances of the Gaussian membership functions in the antecedent part of fuzzy implications. To tune the parameters online, the back-propagation (BP) algorithm is developed. The robust controller is used to guarantee the stability and to control the performance of the closed-loop adaptive system, which is achieved always. Finally, simulation results show that the AFNC can achieve favourable tracking performances.

  3. Robust Adaptive Control and L2 Disturbance Attenuation for Uncertain Hamiltonian Systems with Time Delay

    Directory of Open Access Journals (Sweden)

    Weiwei Sun

    2013-01-01

    Full Text Available This paper deals with the robust stabilizability and L2 disturbance attenuation for a class of time-delay Hamiltonian control systems with uncertainties and external disturbances. Firstly, the robust stability of the given systems is studied, and delay-dependent criteria are established based on the dissipative structural properties of the Hamiltonian systems and the Lyapunov-Krasovskii (L-K functional approach. Secondly, the problem of L2 disturbance attenuation is considered for the Hamiltonian systems subject to external disturbances. An adaptive control law is designed corresponding to the time-varying delay pattern involved in the systems. It is shown that the closed-loop systems under the feedback control law can guarantee the γ-dissipative inequalities be satisfied. Finally, two numerical examples are provided to illustrate the theoretical developments.

  4. FPGA Based Adaptive Neuro Fuzzy Inference Controller for Full Vehicle Nonlinear Active Suspension Systems

    Directory of Open Access Journals (Sweden)

    Ammar A. Aldair

    2010-10-01

    Full Text Available A Field Programmable Gate Array (FPGA is proposed to build an Adaptive Neuro Fuzzy Inference System (ANFIS for controlling a full vehicle nonlinear active suspension system. A Very High speed integrated circuit Hardware Description Language (VHDL has been used to implement the proposed controller. An optimal Fraction Order PIλ D µ (FOPID controller is designed for a full vehicle nonlinear active suspension system. Evolutionary Algorithm (EA has been applied to modify the five parameters of the FOPID controller (i.e. proportional constant Kp, integral constant Ki , derivative constant Kd, integral order λ and derivative order µ. The data obtained from the FOPID controller are used as a reference to design the ANFIS model as a controller for the controlled system. A hybrid approach is introduced to train the ANFIS. A Matlab Program has been used to design and simulate the proposed controller. The ANFIS control parameters obtained from the Matlab program are used to write the VHDL codes. Hardware implementation of the FPGA is dependent on the configuration file obtained from the VHDL program. The experimental results have proved the efficiency and robustness of the hardware implementation for the proposed controller. It provides a novel technique to be used to design NF controller for full vehicle nonlinear active suspension systems with hydraulic actuators.

  5. Neural feedback linearization adaptive control for affine nonlinear systems based on neural network estimator

    Directory of Open Access Journals (Sweden)

    Bahita Mohamed

    2011-01-01

    Full Text Available In this work, we introduce an adaptive neural network controller for a class of nonlinear systems. The approach uses two Radial Basis Functions, RBF networks. The first RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are unknown. The second RBF network is used for on-line estimating the control gain which is a nonlinear and unknown function of the states. The updating laws for the combined estimator and controller are derived through Lyapunov analysis. Asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, the proposed method is applied to control and stabilize the inverted pendulum system.

  6. Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

    Science.gov (United States)

    Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

    2016-01-01

    An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

  7. Identification and novel adaptive fuzzy control of nonlinear system for PEMFC stack

    Institute of Scientific and Technical Information of China (English)

    WEI Dong; XU Hong; ZHU Xin-jian

    2006-01-01

    The operating temperature of a proton exchange membrane fuel cell stack is a very important control parameter. It should be controlled within a specific range, however, most of existing PEMFC mathematical models are too complicated to be effectively applied to on-line control. In this paper, input-output data and operating experiences will be used to establish PEMFC stack model and operating temperature control system. An adaptive learning algorithm and a nearest-neighbor clustering algorithm are applied to regulate the parameters and fuzzy rules so that the model and the control system are able to obtain higher accuracy. In the end, the simulation and the experimental results are presented and compared with traditional PID and fuzzy control algorithms.

  8. A Power-Efficient Wireless System With Adaptive Supply Control for Deep Brain Stimulation.

    Science.gov (United States)

    Lee, Hyung-Min; Park, Hangue; Ghovanloo, Maysam

    2013-09-01

    A power-efficient wireless stimulating system for a head-mounted deep brain stimulator (DBS) is presented. A new adaptive rectifier generates a variable DC supply voltage from a constant AC power carrier utilizing phase control feedback, while achieving high AC-DC power conversion efficiency (PCE) through active synchronous switching. A current-controlled stimulator adopts closed-loop supply control to automatically adjust the stimulation compliance voltage by detecting stimulation site potentials through a voltage readout channel, and improve the stimulation efficiency. The stimulator also utilizes closed-loop active charge balancing to maintain the residual charge at each site within a safe limit, while receiving the stimulation parameters wirelessly from the amplitude-shift-keyed power carrier. A 4-ch wireless stimulating system prototype was fabricated in a 0.5-μm 3M2P standard CMOS process, occupying 2.25 mm². With 5 V peak AC input at 2 MHz, the adaptive rectifier provides an adjustable DC output between 2.5 V and 4.6 V at 2.8 mA loading, resulting in measured PCE of 72 ~ 87%. The adaptive supply control increases the stimulation efficiency up to 30% higher than a fixed supply voltage to 58 ~ 68%. The prototype wireless stimulating system was verified in vitro. PMID:24678126

  9. Adaptive control and synchronization of a fractional-order chaotic system

    Indian Academy of Sciences (India)

    Chunlai Li; Yaonan Tong

    2013-04-01

    In this paper, the chaotic dynamics of a three-dimensional fractional-order chaotic system is investigated. The lowest order for exhibiting chaos in the fractional-order system is obtained. Adaptive schemes are proposed for control and synchronization of the fractional-order chaotic system 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.

  10. L∞-gain adaptive fuzzy fault accommodation control design for nonlinear time-delay systems.

    Science.gov (United States)

    Wu, Huai-Ning; Qiang, Xiao-Hong; Guo, Lei

    2011-06-01

    In this paper, an adaptive fuzzy fault accommodation (FA) control design with a guaranteed L(∞)-gain performance is developed for a class of nonlinear time-delay systems with persistent bounded disturbances. Using the Lyapunov technique and the Razumikhin-type lemma, the existence condition of the L(∞) -gain adaptive fuzzy FA controllers is provided in terms of linear matrix inequalities (LMIs). In the proposed FA scheme, a fuzzy logic system is employed to approximate the unknown term in the derivative of the Lyapunov function due to the unknown fault function; a continuous-state feedback control strategy is adopted for the control design to avoid the undesirable chattering phenomenon. The resulting FA controllers can ensure that every response of the closed-loop system is uniformly ultimately bounded with a guaranteed L(∞)-gain performance in the presence of a fault. Moreover, by the existing LMI optimization technique, a suboptimal controller is obtained in the sense of minimizing an upper bound of the L(∞)-gain. Finally, the achieved simulation results on the FA control of a continuous stirred tank reactor (CSTR) show the effectiveness of the proposed design procedure.

  11. Learning from adaptive neural dynamic surface control of strict-feedback systems.

    Science.gov (United States)

    Wang, Min; Wang, Cong

    2015-06-01

    Learning plays an essential role in autonomous control systems. However, how to achieve learning in the nonstationary environment for nonlinear systems is a challenging problem. In this paper, we present learning method for a class of n th-order strict-feedback systems by adaptive dynamic surface control (DSC) technology, which achieves the human-like ability of learning by doing and doing with learned knowledge. To achieve the learning, this paper first proposes stable adaptive DSC with auxiliary first-order filters, which ensures the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in a finite time. With the help of DSC, the derivative of the filter output variable is used as the neural network (NN) input instead of traditional intermediate variables. As a result, the proposed adaptive DSC method reduces greatly the dimension of NN inputs, especially for high-order systems. After the stable DSC design, we decompose the stable closed-loop system into a series of linear time-varying perturbed subsystems. Using a recursive design, the recurrent property of NN input variables is easily verified since the complexity is overcome using DSC. Subsequently, the partial persistent excitation condition of the radial basis function NN is satisfied. By combining a state transformation, accurate approximations of the closed-loop system dynamics are recursively achieved in a local region along recurrent orbits. Then, the learning control method using the learned knowledge is proposed to achieve the closed-loop stability and the improved control performance. Simulation studies are performed to demonstrate the proposed scheme can not only reuse the learned knowledge to achieve the better control performance with the faster tracking convergence rate and the smaller tracking error but also greatly alleviate the computational burden because of reducing the number and complexity of NN input variables.

  12. Rconfigurable adaptive fuzzy fault-hiding control for greenhouse climate control system

    DEFF Research Database (Denmark)

    Hameed, Ibrahim; El-Madbouly, E I; Abdo, M I

    2016-01-01

    Modern greenhouses are equipped with different components for providing a comfortable climate for plant growth. A component malfunction may result in loss of production. Therefore, it is desirable to design a control system, which is stable, and is able to provide an acceptable degraded performance...... even in the faulty case. In this paper, an active fault tolerant control scheme to compensate for actuator and/or sensor faults in the greenhouse climate system is designed. The control system consists of a sensitive and reliable Fault Detection and Diagnosis (FDD) mechanism for different types...... of faults in presence of system disturbances and a robust reconfigurable control design based on fault-hiding principal in which the fault is hidden from the nominal controller and the fault effects are compensated. In this approach, a set of virtual actuators and virtual sensors are used to guarantee...

  13. FPGA BASED ADAPTIVE NEURO FUZZY INFERENCE CONTROLLER FOR FULL VEHICLE NONLINEAR ACTIVE SUSPENSION SYSTEMS

    Directory of Open Access Journals (Sweden)

    Weiji Wang

    2010-10-01

    Full Text Available A Field Programmable Gate Array (FPGA is proposed to build an Adaptive Neuro Fuzzy Inference System(ANFIS for controlling a full vehicle nonlinear active suspension system. A Very High speed integratedcircuit Hardware Description Language (VHDL has been used to implement the proposed controller. Anoptimal Fraction Order PIlDμ (FOPID controller is designed for a full vehicle nonlinear activesuspension system. Evolutionary Algorithm (EA has been applied to modify the five parameters of theFOPID controller (i.e. proportional constant Kp, integral constant Ki, derivative constant Kd, integralorder l and derivative order μ. The data obtained from the FOPID controller are used as a reference todesign the ANFIS model as a controller for the controlled system. A hybrid approach is introduced to trainthe ANFIS. A Matlab Program has been used to design and simulate the proposed controller. The ANFIScontrol parameters obtained from the Matlab program are used to write the VHDL codes. Hardwareimplementation of the FPGA is dependent on the configuration file obtained from the VHDL program. Theexperimental results have proved the efficiency and robustness of the hardware implementation for theproposed controller. It provides a novel technique to be used to design NF controller for full vehiclenonlinear active suspension systems with hydraulic actuators.

  14. Adaptive tracking controller using BP neural networks for a class of nonlinear systems

    Institute of Scientific and Technical Information of China (English)

    刘子龙; 刘国忠; 刘洁

    2004-01-01

    An BP neural-network-based adaptive control (NNAC) design method is described whose aim is to control a class of partially unknown nonlinear systems. Making use of the online identification of BP neural networks, the results of the identification could be used into the parameters of the controller. Not only the strong robustness with respect to uncertain dynamics and nonlinearities can be obtained, but also the output tracking error between the plant output and the desired reference output can asymptotically converge to zero by Lyapunov theory in the process of this design method.And a simulation example is also presented to evaluate the effectiveness of the design.

  15. Adaptive robust maximum power point tracking control for perturbed photovoltaic systems with output voltage estimation.

    Science.gov (United States)

    Koofigar, Hamid Reza

    2016-01-01

    The problem of maximum power point tracking (MPPT) in photovoltaic (PV) systems, despite the model uncertainties and the variations in environmental circumstances, is addressed. Introducing a mathematical description, an adaptive sliding mode control (ASMC) algorithm is first developed. Unlike many previous investigations, the output voltage is not required to be sensed and the upper bound of system uncertainties and the variations of irradiance and temperature are not required to be known. Estimating the output voltage by an update law, an adaptive-based H∞ tracking algorithm is then developed for the case the perturbations are energy-bounded. The stability analysis is presented for the proposed tracking control schemes, based on the Lyapunov stability theorem. From a comparison viewpoint, some numerical and experimental studies are also presented and discussed. PMID:26606851

  16. Adaptive robust maximum power point tracking control for perturbed photovoltaic systems with output voltage estimation.

    Science.gov (United States)

    Koofigar, Hamid Reza

    2016-01-01

    The problem of maximum power point tracking (MPPT) in photovoltaic (PV) systems, despite the model uncertainties and the variations in environmental circumstances, is addressed. Introducing a mathematical description, an adaptive sliding mode control (ASMC) algorithm is first developed. Unlike many previous investigations, the output voltage is not required to be sensed and the upper bound of system uncertainties and the variations of irradiance and temperature are not required to be known. Estimating the output voltage by an update law, an adaptive-based H∞ tracking algorithm is then developed for the case the perturbations are energy-bounded. The stability analysis is presented for the proposed tracking control schemes, based on the Lyapunov stability theorem. From a comparison viewpoint, some numerical and experimental studies are also presented and discussed.

  17. Integrating Systems Health Management with Adaptive Controls for a Utility-Scale Wind Turbine

    Science.gov (United States)

    Frost, Susan A.; Goebel, Kai; Trinh, Khanh V.; Balas, Mark J.; Frost, Alan M.

    2011-01-01

    Increasing turbine up-time and reducing maintenance costs are key technology drivers for wind turbine operators. Components within wind turbines are subject to considerable stresses due to unpredictable environmental conditions resulting from rapidly changing local dynamics. Systems health management has the aim to assess the state-of-health of components within a wind turbine, to estimate remaining life, and to aid in autonomous decision-making to minimize damage. Advanced adaptive controls can provide the mechanism to enable optimized operations that also provide the enabling technology for Systems Health Management goals. The work reported herein explores the integration of condition monitoring of wind turbine blades with contingency management and adaptive controls. Results are demonstrated using a high fidelity simulator of a utility-scale wind turbine.

  18. Linear matrix inequality-based nonlinear adaptive robust control with application to unmanned aircraft systems

    Science.gov (United States)

    Kun, David William

    Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external

  19. Automated adaptive sliding mode control scheme for a class of real complicated systems

    Indian Academy of Sciences (India)

    M Shahi; A H Mazinan

    2015-02-01

    A class of real complicated systems, including chemical reactions, biological systems, information processing, laser systems, electrical circuits, information exchange, brain activities modelling, secure communication and other related ones can be presented through nonlinear and non-identical hyper-chaotic systems. The main goal of the present investigation is to synchronize two non-identical hyperchaotic master/slave systems, which are given as the models of the complicated systems, based on the realization of an efficient automated adaptive sliding mode control scheme. In the research presented here, the mentioned systems need to be dealt with through the proposed control scheme, since two non-identical systems are completely synchronized. In one such case, the whole of the chosen states of the master and slave systems should be coincided after a few time steps, as long as the effect of the external disturbance, uncertainty and unknown parameters could truly be ignored. Due to the fact that the investigated hyper-chaotic systems have taken into consideration as the representation of a number of complicated processes under mentioned external disturbance, uncertainty and unknown parameters, the traditional control approaches cannot actually be realized, in satisfactory manners.With this purpose, the proposed control scheme has been designed to cope with synchronization error, in a reasonable amount of time, in order to drive applicable hyper-chaotic systems. Consequently, the performance of the proposed control scheme is considered and verified through the numerical simulations.

  20. A Novel Adaptive Observer-Based Control Scheme for Synchronization and Suppression of a Class of Uncertain Chaotic Systems

    Institute of Scientific and Technical Information of China (English)

    WANG Jing; TAN Zhen-Yu; MA Xi-Kui; GAO Jin-Feng

    2009-01-01

    A novel adaptive observer-based control scheme is presented for synchronization and suppression of a class of uncertain chaotic system. First, an adaptive observer based on an orthogonal neural network is designed. Subsequently, the sliding mode controllers via the proposed adaptive observer are proposed for synchronization and suppression of the uncertain chaotic systems. Theoretical analysis and numerical simulation show the effectiveness of the proposed scheme.

  1. Methanol Reformer System Modeling and Control using an Adaptive Neuro-Fuzzy Inference System approach

    DEFF Research Database (Denmark)

    Justesen, Kristian Kjær; Ehmsen, Mikkel Præstholm; Andersen, John;

    2012-01-01

    with following critical burner temperatures, and fuel cell stack anode starvation which significantly can increase the degradation of the fuel cell stack. Modeling of the reformer dynamics is conducted using an adaptive neuro-fuzzy interference system approach (ANFIS) based on measurement results from...

  2. Synchronisation of high-order MIMO nonlinear systems using distributed neuro-adaptive control

    Science.gov (United States)

    Ghiti Sarand, Hassan; Karimi, Bahram

    2016-07-01

    This paper addresses synchronisation problem of high-order multi-input/multi-output (MIMO) multi-agent systems. Each agent has unknown nonlinear dynamics and is subject to uncertain external disturbances. The agents must follow a reference trajectory. An adaptive distributed controller based on relative information of neighbours of each agent is designed to solve the problem for any undirected connected communication topology. A radial basis function neural network is used to represent the controller's unknown structure. Lyapunov stability analysis is employed to guarantee stability of the overall system. By the theoretical analysis, the closed-loop control system is shown to be uniformly ultimately bounded. Finally, simulations are provided to show effectiveness of the proposed control method against uncertainty and disturbances.

  3. Dynamical Adaptive Integral Sliding Backstepping Control of Nonlinear Nontriangular Uncertain Systems

    Directory of Open Access Journals (Sweden)

    Mahmood Pervaiz

    2014-01-01

    Full Text Available We present a control strategy for nonlinear nontriangular uncertain systems. The proposed control method is a synergy between the dynamic adaptive backstepping (DAB and integral sliding mode (ISM and is referred to as DAB-ISMC. Our main objective is to find a recursive procedure to transform a nontriangular system into an implementable form that enables designing a control law which almost eliminates the reaching-phase. The proposed method further facilitates minimization of chattering which is believed to be a shortcoming of the sliding mode control. In this methodology, the ISM, as an integrated subsystem of DAB, is introduced at the final stage of backstepping. This strategy works very well to obtain a system that is robust against model imperfections, matching and unmatching uncertainties. The DAB-ISMC method is applied on a continuous stirred tank reactor (CSTR and simulation results obtained on Matlab are found to be very promising.

  4. Predicted performance benefits of an adaptive digital engine control system of an F-15 airplane

    Science.gov (United States)

    Burcham, F. W., Jr.; Myers, L. P.; Ray, R. J.

    1985-01-01

    The highly integrated digital electronic control (HIDEC) program will demonstrate and evaluate the improvements in performance and mission effectiveness that result from integrating engine-airframe control systems. Currently this is accomplished on the NASA Ames Research Center's F-15 airplane. The two control modes used to implement the systems are an integrated flightpath management mode and in integrated adaptive engine control system (ADECS) mode. The ADECS mode is a highly integrated mode in which the airplane flight conditions, the resulting inlet distortion, and the available engine stall margin are continually computed. The excess stall margin is traded for thrust. The predicted increase in engine performance due to the ADECS mode is presented in this report.

  5. A simplified adaptive neural network prescribed performance controller for uncertain MIMO feedback linearizable systems.

    Science.gov (United States)

    Theodorakopoulos, Achilles; Rovithakis, George A

    2015-03-01

    In this paper, the problem of deriving a continuous, state-feedback controller for a class of multiinput multioutput feedback linearizable systems is considered with special emphasis on controller simplification and reduction of the overall design complexity with respect to the current state of the art. The proposed scheme achieves prescribed bounds on the transient and steady-state performance of the output tracking errors despite the uncertainty in system nonlinearities. Contrary to the current state of the art, however, only a single neural network is utilized to approximate a scalar function that partly incorporates the system nonlinearities. Furthermore, the loss of model controllability problem, typically introduced owing to approximation model singularities, is avoided without attaching additional complexity to the control or adaptive law. Simulations are performed to verify and clarify the theoretical findings.

  6. 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.

  7. INDIRECT ACCELERATED ADAPTIVE FUZZY CONTROLLER

    Institute of Scientific and Technical Information of China (English)

    ZHU Liye; FANG Yuan; ZHANG Weidong

    2008-01-01

    According to a type of normal nonlinear system, an indirect adaptive fuzzy (IAF) controller has been applied to those systems where no accurate mathematical models of the systems under control are available. To satisfy with system performance, an indirect accelerated adaptive fuzzy (IAAF) controller is proposed, and its general form is presented. The general form IAAF controller ensures necessary control criteria and system's global stability using Lyapunov Theorem. It has been proved that the close-loop system error converges to a small neighborhood of equilibrium point. The optimal IAAF controller is derived to guarantee the process's shortest settling time. Simulation results indicate the IAAF controller make the system more stable, accurate, and fast.

  8. The Argonne beamline-B telescope control system: A study of adaptability

    International Nuclear Information System (INIS)

    A beam-expanding telescope to study high-precision H- particle optics and beam sensing was designed by the Accelerator Technology Division at Los Alamos National Laboratory and will be installed on beamline-B at Argonne National Laboratory. The control system for this telescope was developed in a relatively short period of time using experience gained from building the Proton Storage Ring (PSR) control system. The designers modified hardware and software to take advantage of new technology as well as to meet the requirements of the new system. This paper discusses lessons learned in the process of adapting hardware and software from an existing control system to one with rather different requirements

  9. Adaptive Neural Network Output Feedback Tracking Control for a Class of Complicated Agricultural Mechanical Systems

    Directory of Open Access Journals (Sweden)

    Hui Hu

    2015-07-01

    Full Text Available The study presents an adaptive neural network output feedback tracking control scheme for a class of complicated agricultural mechanical systems. The scheme includes a dynamic gain observer to estimate the un-measurable states of the system. The main advantages of the authors scheme are that by introducing non-separation principle design neural network controller and the observer gain are simultaneously tuned according to output tracking error, the semi-globally ultimately bounded of output tracking error and all the states in the closed-loop system can be achieved by Lyapunov approach. With the universal approximation property of NN and the simultaneous parametrisation, no Lipschitz assumption and SPR condition are employed which makes the system construct simple. Finally the simulation results are presented to demonstrate the efficiency of the control scheme.

  10. Adaptive terminal sliding mode control for high-order nonlinear dynamic systems

    Institute of Scientific and Technical Information of China (English)

    庄开宇; 苏宏业; 张克勤; 褚健

    2003-01-01

    An adaptive terminal sliding mode control (SMC) technique is proposed to deal with the tracking problem for a class of high-order nonlinear dynamic systems. It is shown that a function augmented sliding hyperplane can be used to develop a new terminal sliding mode for high-order nonlinear systems. A terminal SMC controller based on Lyapunov theory is designed to force the state variables of the closed-loop system to reach and remain on the terminal sliding mode, so that the output tracking error then converges to zero in finite time which can be set arbitrarily. An adaptive mechanism is introduced to estimate the unknown parameters of the upper bounds of system uncertainties. The estimates are then used as controller parameters so that the effects of uncertain dynamics can be eliminated. It is also shown that the stability of the closed-loop system can be guaranteed with the proposed control strategy. The simulation of a numerical example is provided to show the effectiveness of the new method.

  11. Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities.

    Science.gov (United States)

    Shahnazi, Reza

    2015-01-01

    An adaptive fuzzy output feedback controller is proposed for a class of uncertain MIMO nonlinear systems with unknown input nonlinearities. The input nonlinearities can be backlash-like hysteresis or dead-zone. Besides, the gains of unknown input nonlinearities are unknown nonlinear functions. Based on universal approximation theorem, the unknown nonlinear functions are approximated by fuzzy systems. The proposed method does not need the availability of the states and an observer based on strictly positive real (SPR) theory is designed to estimate the states. An adaptive robust structure is used to cope with fuzzy approximation error and external disturbances. The semi-global asymptotic stability of the closed-loop system is guaranteed via Lyapunov approach. The applicability of the proposed method is also shown via simulations.

  12. Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities.

    Science.gov (United States)

    Shahnazi, Reza

    2015-01-01

    An adaptive fuzzy output feedback controller is proposed for a class of uncertain MIMO nonlinear systems with unknown input nonlinearities. The input nonlinearities can be backlash-like hysteresis or dead-zone. Besides, the gains of unknown input nonlinearities are unknown nonlinear functions. Based on universal approximation theorem, the unknown nonlinear functions are approximated by fuzzy systems. The proposed method does not need the availability of the states and an observer based on strictly positive real (SPR) theory is designed to estimate the states. An adaptive robust structure is used to cope with fuzzy approximation error and external disturbances. The semi-global asymptotic stability of the closed-loop system is guaranteed via Lyapunov approach. The applicability of the proposed method is also shown via simulations. PMID:25104646

  13. INTELLIGENT CONTROL USING ADAPTIVE PID CONTROLLER

    Directory of Open Access Journals (Sweden)

    DR. P VIJAYAKUMAR

    2014-02-01

    Full Text Available In this paper an adaptive stable PID controller is briefly explained and validated by simulations and experimentation. The adaptive PID controller employs almost strict positive realness (ASPR to ensure stability of the system. The design involves a parallel feedforward compensator (PFC which guarantees the ASPRness of the controlled system. After a disturbance the dynamical system is assumed to be in one of a finite number of configurations, corresponding to each of which exist a stabilizing controller. The effectiveness of the method is tested and compared using simulations and experiments on a level control experimental setup.

  14. Adaptive Second Order Sliding Mode Control of a Fuel Cell Hybrid System for Electric Vehicle Applications

    Directory of Open Access Journals (Sweden)

    Jianxing Liu

    2015-01-01

    Full Text Available We present an adaptive-gain second order sliding mode (SOSM control applied to a hybrid power system for electric vehicle applications. The main advantage of the adaptive SOSM is that it does not require the upper bound of the uncertainty. The proposed hybrid system consists of a polymer electrolyte membrane fuel cell (PEMFC with a unidirectional DC/DC converter and a Li-ion battery stack with a bidirectional DC/DC converter, where the PEMFC is employed as the primary energy source and the battery is employed as the second energy source. One of the main limitations of the FC is its slow dynamics mainly due to the air-feed system and fuel-delivery system. Fuel starvation phenomenon will occur during fast load demand. Therefore, the second energy source is required to assist the main source to improve system perofrmance. The proposed energy management system contains two cascade control structures, which are used to regulate the fuel cell and battery currents to track the given reference currents and stabilize the DC bus voltage while satisfying the physical limitations. The proposed control strategy is evaluated for two real driving cycles, that is, Urban Dynamometer Driving Schedule (UDDS and Highway Fuel Economy Driving Schedule (HWFET.

  15. A design of LED adaptive dimming lighting system based on incremental PID controller

    Science.gov (United States)

    He, Xiangyan; Xiao, Zexin; He, Shaojia

    2010-11-01

    As a new generation energy-saving lighting source, LED is applied widely in various technology and industry fields. The requirement of its adaptive lighting technology is more and more rigorous, especially in the automatic on-line detecting system. In this paper, a closed loop feedback LED adaptive dimming lighting system based on incremental PID controller is designed, which consists of MEGA16 chip as a Micro-controller Unit (MCU), the ambient light sensor BH1750 chip with Inter-Integrated Circuit (I2C), and constant-current driving circuit. A given value of light intensity required for the on-line detecting environment need to be saved to the register of MCU. The optical intensity, detected by BH1750 chip in real time, is converted to digital signal by AD converter of the BH1750 chip, and then transmitted to MEGA16 chip through I2C serial bus. Since the variation law of light intensity in the on-line detecting environment is usually not easy to be established, incremental Proportional-Integral-Differential (PID) algorithm is applied in this system. Control variable obtained by the incremental PID determines duty cycle of Pulse-Width Modulation (PWM). Consequently, LED's forward current is adjusted by PWM, and the luminous intensity of the detection environment is stabilized by self-adaptation. The coefficients of incremental PID are obtained respectively after experiments. Compared with the traditional LED dimming system, it has advantages of anti-interference, simple construction, fast response, and high stability by the use of incremental PID algorithm and BH1750 chip with I2C serial bus. Therefore, it is suitable for the adaptive on-line detecting applications.

  16. Adaptive fuzzy output-feedback controller design for nonlinear time-delay systems with unknown control direction.

    Science.gov (United States)

    Hua, Chang-Chun; Wang, Qing-Guo; Guan, Xin-Ping

    2009-04-01

    In this paper, the robust-control problem is investigated for a class of uncertain nonlinear time-delay systems via dynamic output-feedback approach. The considered system is in the strict-feedback form with unknown control direction. A full-order observer is constructed with the gains computed via linear matrix inequality at first. Then, with the bounds of uncertain functions known, we design the dynamic output-feedback controller such that the closed-loop system is asymptotically stable. Furthermore, when the bound functions of uncertainties are not available, the adaptive fuzzy-logic system is employed to approximate the uncertain function, and the corresponding output-feedback controller is designed. It is shown that the resulting closed-loop system is stable in the sense of semiglobal uniform ultimate boundedness. Finally, simulations are done to verify the feasibility and effectiveness of the obtained theoretical results.

  17. Robust Adaptive Structural Control

    OpenAIRE

    Yang, Chi-Ming; Beck, James L.

    1995-01-01

    A new robust adaptive structural control design methodology is developed and presented which treats modeling uncertainties and limitations of control devices. Furthermore, no restriction is imposed on the structural models and the nature of the control devices so that the proposed method is very general. A simple linear single degree-of-freedom numerical example is presented to illustrate this approach.

  18. Synchronization analysis and control of three eccentric rotors in a vibrating system using adaptive sliding mode control algorithm

    Science.gov (United States)

    Kong, Xiangxi; Zhang, Xueliang; Chen, Xiaozhe; Wen, Bangchun; Wang, Bo

    2016-05-01

    In this paper, self- and controlled synchronizations of three eccentric rotors (ERs) in line driven by induction motors rotating in the same direction in a vibrating system are investigated. The vibrating system is a typical underactuated mechanical-electromagnetic coupling system. The analysis and control of the vibrating system convert to the synchronization motion problem of three ERs. Firstly, the self-synchronization motion of three ERs is analyzed according to self-synchronization theory. The criterions of synchronization and stability of self-synchronous state are obtained by using a modified average perturbation method. The significant synchronization motion of three ERs with zero phase differences cannot be implemented according to self-synchronization theory through analysis and simulations. To implement the synchronization motion of three ERs with zero phase differences, an adaptive sliding mode control (ASMC) algorithm based on a modified master-slave control strategy is employed to design the controllers. The stability of the controllers is verified by using Lyapunov theorem. The performances of the controlled synchronization system are presented by simulations to demonstrate the effectiveness of controllers. Finally, the effects of reference speed and non-zero phase differences on the controlled system are discussed to show the strong robustness of the proposed controllers. Additionally, the dynamic responses of the vibrating system in different synchronous states are analyzed.

  19. Adaptive Neural Control of Pure-Feedback Nonlinear Time-Delay Systems via Dynamic Surface Technique.

    Science.gov (United States)

    Min Wang; Xiaoping Liu; Peng Shi

    2011-12-01

    This paper is concerned with robust stabilization problem for a class of nonaffine pure-feedback systems with unknown time-delay functions and perturbed uncertainties. Novel continuous packaged functions are introduced in advance to remove unknown nonlinear terms deduced from perturbed uncertainties and unknown time-delay functions, which avoids the functions with control law to be approximated by radial basis function (RBF) neural networks. This technique combining implicit function and mean value theorems overcomes the difficulty in controlling the nonaffine pure-feedback systems. Dynamic surface control (DSC) is used to avoid "the explosion of complexity" in the backstepping design. Design difficulties from unknown time-delay functions are overcome using the function separation technique, the Lyapunov-Krasovskii functionals, and the desirable property of hyperbolic tangent functions. RBF neural networks are employed to approximate desired virtual controls and desired practical control. Under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced significantly, and semiglobal uniform ultimate boundedness of all of the signals in the closed-loop system is guaranteed. Simulation studies are given to demonstrate the effectiveness of the proposed design scheme.

  20. L1 Adaptive Speed Control of a Small Wind Energy Conversion System for Maximum Power Point Tracking

    OpenAIRE

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard; Blanke, Mogens

    2014-01-01

    This paper presents the design of an L1 adaptive controller for maximum power point tracking (MPPT) of a small variable speed Wind Energy Conversion System (WECS). The proposed controller generates the optimal torque command for the vector controlled generator side converter (GSC) based on the wind speed estimation. The proposed MPPT control algorithm has a generic structure and can be used for different generator types. In order to verify the efficacy of the proposed L1 adaptive controller f...

  1. Adaptive optimal control of unknown constrained-input systems using policy iteration and neural networks.

    Science.gov (United States)

    Modares, Hamidreza; Lewis, Frank L; Naghibi-Sistani, Mohammad-Bagher

    2013-10-01

    This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems. The proposed PI algorithm is implemented on an actor-critic structure where two neural networks (NNs) are tuned online and simultaneously to generate the optimal bounded control policy. The requirement of complete knowledge of the system dynamics is obviated by employing a novel NN identifier in conjunction with the actor and critic NNs. It is shown how the identifier weights estimation error affects the convergence of the critic NN. A novel learning rule is developed to guarantee that the identifier weights converge to small neighborhoods of their ideal values exponentially fast. To provide an easy-to-check persistence of excitation condition, the experience replay technique is used. That is, recorded past experiences are used simultaneously with current data for the adaptation of the identifier weights. Stability of the whole system consisting of the actor, critic, system state, and system identifier is guaranteed while all three networks undergo adaptation. Convergence to a near-optimal control law is also shown. The effectiveness of the proposed method is illustrated with a simulation example. PMID:24808590

  2. Adaptive Inverse Optimal Control for Rehabilitation Robot Systems Using Actor-Critic Algorithm

    Directory of Open Access Journals (Sweden)

    Fancheng Meng

    2014-01-01

    Full Text Available The higher goal of rehabilitation robot is to aid a person to achieve a desired functional task (e.g., tracking trajectory based on assisted-as-needed principle. To this goal, a new adaptive inverse optimal hybrid control (AHC combining inverse optimal control and actor-critic learning is proposed. Specifically, an uncertain nonlinear rehabilitation robot model is firstly developed that includes human motor behavior dynamics. Then, based on this model, an open-loop error system is formed; thereafter, an inverse optimal control input is designed to minimize the cost functional and a NN-based actor-critic feedforward signal is responsible for the nonlinear dynamic part contaminated by uncertainties. Finally, the AHC controller is proven (through a Lyapunov-based stability analysis to yield a global uniformly ultimately bounded stability result, and the resulting cost functional is meaningful. Simulation and experiment on rehabilitation robot demonstrate the effectiveness of the proposed control scheme.

  3. Adaptive NN State-Feedback Control for Stochastic High-Order Nonlinear Systems with Time-Varying Control Direction and Delays

    Directory of Open Access Journals (Sweden)

    Huifang Min

    2015-01-01

    and dynamic surface control technique, an adaptive NN controller is constructed to render the closed-loop system semiglobally uniformly ultimately bounded (SGUUB. Finally, a simulation example is shown to demonstrate the effectiveness of the proposed control scheme.

  4. Truncated adaptation design for decentralised neural dynamic surface control of interconnected nonlinear systems under input saturation

    Science.gov (United States)

    Gao, Shigen; Dong, Hairong; Lyu, Shihang; Ning, Bin

    2016-07-01

    This paper studies decentralised neural adaptive control of a class of interconnected nonlinear systems, each subsystem is in the presence of input saturation and external disturbance and has independent system order. Using a novel truncated adaptation design, dynamic surface control technique and minimal-learning-parameters algorithm, the proposed method circumvents the problems of 'explosion of complexity' and 'dimension curse' that exist in the traditional backstepping design. Comparing to the methodology that neural weights are online updated in the controllers, only one scalar needs to be updated in the controllers of each subsystem when dealing with unknown systematic dynamics. Radial basis function neural networks (NNs) are used in the online approximation of unknown systematic dynamics. It is proved using Lyapunov stability theory that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. The tracking errors of each subsystems, the amplitude of NN approximation residuals and external disturbances can be attenuated to arbitrarily small by tuning proper design parameters. Simulation results are given to demonstrate the effectiveness of the proposed method.

  5. Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints

    Science.gov (United States)

    Yang, Xiong; Liu, Derong; Wang, Ding

    2014-03-01

    In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.

  6. Adaptive neural networks control for camera stabilization with active suspension system

    Directory of Open Access Journals (Sweden)

    Feng Zhao

    2015-08-01

    Full Text Available The camera always suffers from image instability on the moving vehicle due to unintentional vibrations caused by road roughness. This article presents an adaptive neural network approach mixed with linear quadratic regulator control for a quarter-car active suspension system to stabilize the image captured area of the camera. An active suspension system provides extra force through the actuator which allows it to suppress vertical vibration of sprung mass. First, to deal with the road disturbance and the system uncertainties, radial basis function neural network is proposed to construct the map between the state error and the compensation component, which can correct the optimal state-feedback control law. The weights matrix of radial basis function neural network is adaptively tuned online. Then, the closed-loop stability and asymptotic convergence performance is guaranteed by Lyapunov analysis. Finally, the simulation results demonstrate that the proposed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance.

  7. Low power proton exchange membrane fuel cell system identification and adaptive control

    Science.gov (United States)

    Yang, Yee-Pien; Wang, Fu-Cheng; Chang, Hsin-Ping; Ma, Ying-Wei; Weng, Biing-Jyh

    This paper proposes a systematic method of system identification and control of a proton exchange membrane (PEM) fuel cell. This fuel cell can be used for low-power communication devices involving complex electrochemical reactions of nonlinear and time-varying dynamic properties. From a system point of view, the dynamic model of PEM fuel cell is reduced to a configuration of two inputs, hydrogen and air flow rates, and two outputs, cell voltage and current. The corresponding transfer functions describe linearized subsystem dynamics with finite orders and time-varying parameters, which are expressed as discrete-time auto-regression moving-average with auxiliary input models for system identification by the recursive least square algorithm. In the experiments, a pseudo-random binary sequence of hydrogen or air flow rate is fed to a single fuel cell device to excite its dynamics. By measuring the corresponding output signals, each subsystem transfer function of reduced order is identified, while the unmodeled, higher-order dynamics and disturbances are described by the auxiliary input term. This provides a basis of adaptive control strategy to improve the fuel cell performance in terms of efficiency, as well as transient and steady state specifications. Simulation shows that adaptive controller is robust to the variation of fuel cell system dynamics, and it has proved promising from the experimental results.

  8. On-line Multiple-model Based Adaptive Control Reconfiguration for a Class of Non-linear Control Systems

    DEFF Research Database (Denmark)

    Yang, Z.; Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2000-01-01

    Based on the model-matching strategy, an adaptive control reconfiguration method for a class of nonlinear control systems is proposed by using the multiple-model scheme. Instead of requiring the nominal and faulty nonlinear systems to match each other directly in some proper sense, three sets...... of LTI models are employed to approximate the faulty, reconfigured and nominal nonlinear systems respectively with respect to the on-line information of the operating system, and a set of compensating modules are proposed and designed so as to make the local LTI model approximating to the reconfigured...... nonlinear system match the corresponding LTI model approximating to the nominal nonlinear system in some optimal sense. The compensating modules are designed by the Pseudo-Inverse Method based on the local LTI models for the nominal and faulty nonlinear systems. Moreover, these modules should update...

  9. Longitudinal Control of a Platoon of Road Vehicles Equipped with Adaptive Cruise Control System

    Directory of Open Access Journals (Sweden)

    Zeeshan Ali Memon

    2012-07-01

    Full Text Available Automotive vehicle following systems are essential for the design of automated highway system. The problem associated with the automatic vehicle following system is the string stability of the platoon of vehicles, i.e. the problem of uniform velocity and spacing errors propagation. Different control algorithm for the longitudinal control of a platoon are discussed based on different spacing policies, communication link among the vehicles of a platoon, and the performance of a platoon have been analysed in the presence of disturbance (noise and parametric uncertainties. This paper presented the PID (Proportional Integral Derivative feedback control algorithm for the longitudinal control of a platoon in the presence of noise signal and investigates the performance of platoon under the influence of sudden acceleration and braking in severe conditions. This model has been applied on 6 vehicles moving in a platoon. The platoon has been analysed to retain the uniform velocity and safe spacing among the vehicles. The limitations of PID control algorithm have been discussed and the alternate methods have been suggested. Model simulations, in comparison with the literature, are also presented.

  10. Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System

    Directory of Open Access Journals (Sweden)

    Shan Zuo

    2014-01-01

    Full Text Available In searching for methods to increase the power capacity of wind power generation system, superconducting synchronous generator (SCSG has appeared to be an attractive candidate to develop large-scale wind turbine due to its high energy density and unprecedented advantages in weight and size. In this paper, a high-temperature superconducting technology based large-scale wind turbine is considered and its physical structure and characteristics are analyzed. A simple yet effective single neuron-adaptive PID control scheme with Delta learning mechanism is proposed for the speed control of SCSG based wind power system, in which the RBF neural network (NN is employed to estimate the uncertain but continuous functions. Compared with the conventional PID control method, the simulation results of the proposed approach show a better performance in tracking the wind speed and maintaining a stable tip-speed ratio, therefore, achieving the maximum wind energy utilization.

  11. Design of a Stability Augmentation System for an Unmanned Helicopter Based on Adaptive Control Techniques

    Directory of Open Access Journals (Sweden)

    Shouzhao Sheng

    2015-09-01

    Full Text Available The task of control of unmanned helicopters is rather complicated in the presence of parametric uncertainties and measurement noises. This paper presents an adaptive model feedback control algorithm for an unmanned helicopter stability augmentation system. The proposed algorithm can achieve a guaranteed model reference tracking performance and speed up the convergence rates of adjustable parameters, even when the plant parameters vary rapidly. Moreover, the model feedback strategy in the algorithm further contributes to the improvement in the control quality of the stability augmentation system in the case of low signal to noise ratios, mainly because the model feedback path is noise free. The effectiveness and superiority of the proposed algorithm are demonstrated through a series of tests.

  12. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    Science.gov (United States)

    Nguyen, Nhan T.

    2009-01-01

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

  13. 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.

  14. Adaptive Backstepping Sliding-Mode Control of the Electronic Throttle System in Modern Automobiles

    Directory of Open Access Journals (Sweden)

    Rui Bai

    2014-01-01

    Full Text Available In modern automobiles, electronic throttle is a DC-motor-driven valve that regulates air inflow into the vehicle’s combustion system. The electronic throttle is increasingly being used in order to improve the vehicle drivability, fuel economy, and emissions. Electronic throttle system has the nonlinear dynamical characteristics with the unknown disturbance and parameters. At first, the dynamical nonlinear model of the electronic throttle is built in this paper. Based on the model and using the backstepping design technique, a new adaptive backstepping sliding-mode controller of the electronic throttle is developed. During the backstepping design process, parameter adaptive law is designed to estimate the unknown parameter, and sliding-mode control term is applied to compensate the unknown disturbance. The proposed controller can make the actual angle of the electronic throttle track its set point with the satisfactory performance. Finally, a computer simulation is performed, and simulation results verify that the proposed control method can achieve favorable tracking performance.

  15. Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources

    OpenAIRE

    Sun, Yiming

    2016-01-01

    In this work, an innovative real-time microwave control approach is proposed, to improve the temperature homogeneity under microwave heating. Multiple adaptive or intelligent control structures have been developed, including the model predictive control, neural network control and reinforcement learning control methods. Experimental results prove that these advanced control methods can effectively reduce the final temperature derivations and improve the temperature homogeneity.

  16. Output feedback adaptive control of multivariable nonlinear systems using Nussbaum gain method

    Institute of Scientific and Technical Information of China (English)

    Zhou Ying; Wu Yuqiang

    2006-01-01

    A new output feedback adaptive control scheme for multi-input and multi-output nonlinear systems with parametric uncertainty is presented based on the Nussbaum gain method and the backstepping approach. The high frequency gain matrix of the linear part of the system is not necessarily positive definite, but can be transformed into a lower or upper triangular matrix whose signs of diagonal elements are unknown. The new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. The global stability of the closed loop systems is guaranteed through this control scheme, at the same time the tracking error converges to zero.

  17. 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.

  18. Adaptive Output Feedback Sliding Mode Control for Complex Interconnected Time-Delay Systems

    Directory of Open Access Journals (Sweden)

    Van Van Huynh

    2015-01-01

    Full Text Available We extend the decentralized output feedback sliding mode control (SMC scheme to stabilize a class of complex interconnected time-delay systems. First, sufficient conditions in terms of linear matrix inequalities are derived such that the equivalent reduced-order system in the sliding mode is asymptotically stable. Second, based on a new lemma, a decentralized adaptive sliding mode controller is designed to guarantee the finite time reachability of the system states by using output feedback only. The advantage of the proposed method is that two major assumptions, which are required in most existing SMC approaches, are both released. These assumptions are (1 disturbances are bounded by a known function of outputs and (2 the sliding matrix satisfies a matrix equation that guarantees the sliding mode. Finally, a numerical example is used to demonstrate the efficacy of the method.

  19. Application of Adaptive Backstepping Sliding Mode Control in Alternative Current Servo System of Rocket Launcher%Application of Adaptive Backstepping Sliding Mode Control in Alternative Current Servo System of Rocket Launcher

    Institute of Scientific and Technical Information of China (English)

    郭亚军; 马大为; 王晓峰; 乐贵高

    2011-01-01

    An adaptive backstepping sliding mode control approach is introduced to control the pitch motion of a rocket launcher. Its control law is proposed to guarantee that the control system is ultimately bounded in a Lyapunov sense and make the servo system track the instruction of reference position globally and asymptotically. In addition, the sliding mode control can restrain the effects of parameter uncertainties and external disturbance. The functions of adaptive mechanism and sliding mode control are analyzed through the simulation in the different conditions. The simulation results illustrate that the method is applicable and robust.

  20. Adaptive Traffic Control Systems in a medium-sized Scandinavian city

    DEFF Research Database (Denmark)

    Agerholm, Niels; Olesen, Anne Vingaard

    2016-01-01

    Adaptive Traffic Control Systems (ATCS) are aimed at reducing congestion. ATCS adapt to approaching traffic to continuously optimise the traffic flows in question. ATCS have been implemented in many locations, including the Scandinavian countries, with various effects. Due to congestion problems......, ATCS were installed in the eight signalised intersections of a 1.7 km stretch of the ring road in the medium-sized Danish city of Aalborg. To measure the effect of ATCS a with/without study was carried out. GPS data from a car following the traffic, recorded transportation times for buses in service......, and GPS data from a range of cars driving on the ring road formed the basis for the study. The result of ATCS implementation was a significant 17% reduction in transportation time on the ring road in the most congested period, the afternoon peak. Less significant effects were found regarding the morning...

  1. Adaptive neural control of nonlinear MIMO systems with time-varying output constraints.

    Science.gov (United States)

    Meng, Wenchao; Yang, Qinmin; Sun, Youxian

    2015-05-01

    In this paper, adaptive neural control is investigated for a class of unknown multiple-input multiple-output nonlinear systems with time-varying asymmetric output constraints. To ensure constraint satisfaction, we employ a system transformation technique to transform the original constrained (in the sense of the output restrictions) system into an equivalent unconstrained one, whose stability is sufficient to solve the output constraint problem. It is shown that output tracking is achieved without violation of the output constraint. More specifically, we can shape the system performance arbitrarily on transient and steady-state stages with the output evolving in predefined time-varying boundaries all the time. A single neural network, whose weights are tuned online, is used in our design to approximate the unknown functions in the system dynamics, while the singularity problem of the control coefficient matrix is avoided without assumption on the prior knowledge of control input's bound. All the signals in the closed-loop system are proved to be semiglobally uniformly ultimately bounded via Lyapunov synthesis. Finally, the merits of the proposed controller are verified in the simulation environment.

  2. Memory controlled data processor. [Data collector and formatter for adaptive Intrusion Data System

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, C.S.

    1977-12-01

    The Memory Controlled Data Processor (MCDP) was designed to provide a high-speed multichannel processor and data formater for the Adaptive Intrusion Data System. It can address up to 48 analog data channels, 48 bilevel alarm data channels, and numerous miscellaneous data channels such as weather and time. A digital comparator in the MCDP can make comparisons between the data being processed and threshold limits programed for any channel. The MCDP is software oriented and has its instructions stored in a 4K core memory. 8 figures, 7 tables.

  3. An adaptive control system for off-line programming in robotic gas metal arc welding.

    OpenAIRE

    Carvalho, G. C.

    1997-01-01

    The aim of this work was to develop an integration concept for using off-line programming in robotic gas metal arc welding of thin sheet steel. Off line -welding parameter optimization and on-line monitoring and adaptive control of process stability and torch-to-workpiece relative distance were used to ensure weld consistency. The concept developed included four main aspects: a) the use of a CAD system to design the workpiece; b) the use of a welding off-line programming ...

  4. Adaptive Control of Linear Modal Systems Using Residual Mode Filters and a Simple Disturbance Estimator

    Science.gov (United States)

    Balas, Mark; Frost, Susan

    2012-01-01

    Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.

  5. Adaptive RSOV filter using the FELMS algorithm for nonlinear active noise control systems

    Science.gov (United States)

    Zhao, Haiquan; Zeng, Xiangping; He, Zhengyou; Li, Tianrui

    2013-01-01

    This paper presents a recursive second-order Volterra (RSOV) filter to solve the problems of signal saturation and other nonlinear distortions that occur in nonlinear active noise control systems (NANC) used for actual applications. Since this nonlinear filter based on an infinite impulse response (IIR) filter structure can model higher than second-order and third-order nonlinearities for systems where the nonlinearities are harmonically related, the RSOV filter is more effective in NANC systems with either a linear secondary path (LSP) or a nonlinear secondary path (NSP). Simulation results clearly show that the RSOV adaptive filter using the multichannel structure filtered-error least mean square (FELMS) algorithm can further greatly reduce the computational burdens and is more suitable to eliminate nonlinear distortions in NANC systems than a SOV filter, a bilinear filter and a third-order Volterra (TOV) filter.

  6. Adaptive iterative learning control for a class of non-linearly parameterised systems with input saturations

    Science.gov (United States)

    Zhang, Ruikun; Hou, Zhongsheng; Ji, Honghai; Yin, Chenkun

    2016-04-01

    In this paper, an adaptive iterative learning control scheme is proposed for a class of non-linearly parameterised systems with unknown time-varying parameters and input saturations. By incorporating a saturation function, a new iterative learning control mechanism is presented which includes a feedback term and a parameter updating term. Through the use of parameter separation technique, the non-linear parameters are separated from the non-linear function and then a saturated difference updating law is designed in iteration domain by combining the unknown parametric term of the local Lipschitz continuous function and the unknown time-varying gain into an unknown time-varying function. The analysis of convergence is based on a time-weighted Lyapunov-Krasovskii-like composite energy function which consists of time-weighted input, state and parameter estimation information. The proposed learning control mechanism warrants a L2[0, T] convergence of the tracking error sequence along the iteration axis. Simulation results are provided to illustrate the effectiveness of the adaptive iterative learning control scheme.

  7. Leader-following consensus of fractional-order multi-agent systems via adaptive pinning control

    Science.gov (United States)

    Yu, Zhiyong; Jiang, Haijun; Hu, Cheng; Yu, Juan

    2015-09-01

    In this paper, the leader-following consensus problem of fractional-order multi-agent systems is considered via adaptive pinning control. The dynamics of leader and all followers with linear and nonlinear functions are investigated, respectively. We assume that the node should be pinned if its in-degree is less than its out-degree in the paper. Under this assumption and based on the stability theory of fractional-order differential systems, some leader-following consensus criteria are derived, which are easily obtained by matrix inequalities. The control of each agent using local information is designed and detailed analysis of the leader-following consensus is presented. The design technique is based on algebraic graph theory and the Riccati inequality. Several simulation examples are presented to demonstrate the effectiveness of the proposed method.

  8. Observer-based Adaptive Iterative Learning Control for Nonlinear Systems with Time-varying Delays

    Institute of Scientific and Technical Information of China (English)

    Wei-Sheng Chen; Rui-Hong Li; Jing Li

    2010-01-01

    An observer-based adaptive iterative learning control (AILC) scheme is developed for a class of nonlinear systems with unknown time-varying parameters and unknown time-varying delays. The linear matrix inequality (LMI) method is employed to design the nonlinear observer. The designed controller contains a proportional-integral-derivative (PID) feedback term in time domain. The learning law of unknown constant parameter is differential-difference-type, and the learning law of unknown time-varying parameter is difference-type. It is assumed that the unknown delay-dependent uncertainty is nonlinearly parameterized. By constructing a Lyapunov-Krasovskii-like composite energy function (CEF), we prove the boundedness of all closed-loop signals and the convergence of tracking error. A simulation example is provided to illustrate the effectiveness of the control algorithm proposed in this paper.

  9. Novel Adaptive Learning Control of Linear Systems with Completely Unknown Time Delays

    Institute of Scientific and Technical Information of China (English)

    Wei-Sheng Chen

    2009-01-01

    A novel output-feedback adaptive learning control approach is developed for a class of linear time-delay systems. Three kinds of uncertainties: time delays, number of time delays, and system parameters are all assumed to be completely unknown, which is different from the previous work. The design procedure includes two steps. First, according to the given periodic desired reference output and the allowed bound of tracking error, a suitable finite Fourier series expansion (FSE) is chosen as a practical reference output to he tracked. Second, by expressing the delayed practical reference output as a known time-varying vector multiplied by an unknown constant vector, we combine three kinds of uncertainties into an unknown constant vector and then estimate the vector by designing an adaptive law. By constructing a Lyapunov-Krasovskii functional, it is proved that the system output can asymptotically track the practical reference signal An example is provided to illustrate the effectiveness of the control scheme developed in this paper.

  10. Performance enhanced design of chaos controller for the mechanical centrifugal flywheel governor system via adaptive dynamic surface control

    Science.gov (United States)

    Luo, Shaohua; Hou, Zhiwei; Zhang, Tao

    2016-09-01

    This paper addresses chaos suppression of the mechanical centrifugal flywheel governor system with output constraint and fully unknown parameters via adaptive dynamic surface control. To have a certain understanding of chaotic nature of the mechanical centrifugal flywheel governor system and subsequently design its controller, the useful tools like the phase diagrams and corresponding time histories are employed. By using tangent barrier Lyapunov function, a dynamic surface control scheme with neural network and tracking differentiator is developed to transform chaos oscillation into regular motion and the output constraint rule is not broken in whole process. Plugging second-order tracking differentiator into chaos controller tackles the "explosion of complexity" of backstepping and improves the accuracy in contrast with the first-order filter. Meanwhile, Chebyshev neural network with adaptive law whose input only depends on a subset of Chebyshev polynomials is derived to learn the behavior of unknown dynamics. The boundedness of all signals of the closed-loop system is verified in stability analysis. Finally, the results of numerical simulations illustrate effectiveness and exhibit the superior performance of the proposed scheme by comparing with the existing ADSC method.

  11. Performance enhanced design of chaos controller for the mechanical centrifugal flywheel governor system via adaptive dynamic surface control

    Directory of Open Access Journals (Sweden)

    Shaohua Luo

    2016-09-01

    Full Text Available This paper addresses chaos suppression of the mechanical centrifugal flywheel governor system with output constraint and fully unknown parameters via adaptive dynamic surface control. To have a certain understanding of chaotic nature of the mechanical centrifugal flywheel governor system and subsequently design its controller, the useful tools like the phase diagrams and corresponding time histories are employed. By using tangent barrier Lyapunov function, a dynamic surface control scheme with neural network and tracking differentiator is developed to transform chaos oscillation into regular motion and the output constraint rule is not broken in whole process. Plugging second-order tracking differentiator into chaos controller tackles the “explosion of complexity” of backstepping and improves the accuracy in contrast with the first-order filter. Meanwhile, Chebyshev neural network with adaptive law whose input only depends on a subset of Chebyshev polynomials is derived to learn the behavior of unknown dynamics. The boundedness of all signals of the closed-loop system is verified in stability analysis. Finally, the results of numerical simulations illustrate effectiveness and exhibit the superior performance of the proposed scheme by comparing with the existing ADSC method.

  12. Control of a methanol reformer system using an Adaptive Neuro‐Fuzzy Inference System approach

    DEFF Research Database (Denmark)

    Justesen, Kristian Kjær; Andersen, John; Ehmsen, Mikkel Præstholm;

    This work presents a stoichiometry control strategy for a reformed methanol fuel cell system, which uses a reformer to produce hydrogen for an HTPEM fuel cell. One such system is the Serenus H3-350 battery charger developed by the Danish company Serenegy® which this work is based on. The poster w...

  13. Adaptive control with aerospace applications

    Science.gov (United States)

    Gadient, Ross

    Robust and adaptive control techniques have a rich history of theoretical development with successful application. Despite the accomplishments made, attempts to combine the best elements of each approach into robust adaptive systems has proven challenging, particularly in the area of application to real world aerospace systems. In this research, we investigate design methods for general classes of systems that may be applied to representative aerospace dynamics. By combining robust baseline control design with augmentation designs, our work aims to leverage the advantages of each approach. This research contributes the development of robust model-based control design for two classes of dynamics: 2nd order cascaded systems, and a more general MIMO framework. We present a theoretically justified method for state limiting via augmentation of a robust baseline control design. Through the development of adaptive augmentation designs, we are able to retain system performance in the presence of uncertainties. We include an extension that combines robust baseline design with both state limiting and adaptive augmentations. In addition we develop an adaptive augmentation design approach for a class of dynamic input uncertainties. We present formal stability proofs and analyses for all proposed designs in the research. Throughout the work, we present real world aerospace applications using relevant flight dynamics and flight test results. We derive robust baseline control designs with application to both piloted and unpiloted aerospace system. Using our developed methods, we add a flight envelope protecting state limiting augmentation for piloted aircraft applications and demonstrate the efficacy of our approach via both simulation and flight test. We illustrate our adaptive augmentation designs via application to relevant fixed-wing aircraft dynamics. Both a piloted example combining the state limiting and adaptive augmentation approaches, and an unpiloted example with

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

    International Nuclear Information System (INIS)

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

  15. Adaptive Control of Active Balancing System for a Fast Speed-varying Jeffcott Rotor with Actuator Time Delay

    Institute of Scientific and Technical Information of China (English)

    HU Bing; FANG Zhi-chu

    2008-01-01

    Due to actuator time delay existing in an adaptive control of the active balancing system for a fastspeed-varying Jeffcott rotor, if an unsynchronized control force (correction imbalance) is applied to the system,it may lead to degradation in control efficiency and instability of the control system. In order to avoid theseshortcomings, a simple adaptive controller was designed for a strictly positive real rotor system with actuatortime delay, then a Lyapunov-Krasovskii functional was constructed after an appropriate transform of this sys-tem model, the stability conditions of this adaptive control system with actuator time delay were derived. Afteradding a filter function, the active balancing system for the fast speed-varying Jeffcott rotor with actuator timedelay can easily be converted to a strictly positive real system, and thus it can use the above adaptive controllersatisfying the stability conditions. Finally, numerical simulations show that the adaptive controller proposedworks very well to perform the active balancing for the fast speed-varying Jeffcott rotor with actuator timedelay.

  16. Biohybrid control of general linear systems using the adaptive filter model of cerebellum

    Directory of Open Access Journals (Sweden)

    Emma D. Wilson

    2015-07-01

    Full Text Available The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems such as the vestibulo-ocular reflex (VOR and to sensory processing problems such as the adaptive cancellation of reafferent noise. It has also been successfully applied to problems in robotics such as adaptive camera stabilisation and sensor noise cancellation. In previous applications to inverse control problems the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity control of this plant results in unstable learning and control. To be more generally useful in engineering problems it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC scheme, which stabilises the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.

  17. Adaptive control for a class of nonlinear time-delay systems preceded by unknown hysteresis

    Science.gov (United States)

    Zhang, Xiuyu; Lin, Yan

    2013-08-01

    In this article, a robust adaptive neural dynamic surface control is proposed for a class of time-delay nonlinear systems preceded by saturated hystereses. Compared with the present schemes of dealing with time delay and hystereses input, the main advantages of the proposed scheme are that the prespecified transient and steady-state performance of tracking error can be guaranteed, the computational burden can be greatly reduced and the explosion of complexity problem inherent in backstepping control can be eliminated. Moreover, the utilisation of saturated-type Prandtl-Ishlinskii model makes our scheme more applicable. It is proved that the new scheme can guarantee all the closed-loop signals semiglobally uniformly ultimate bounded. Simulation results are presented to demonstrate the validity of the proposed scheme.

  18. A Novel Fuzzy Logic Based Adaptive Super-Twisting Sliding Mode Control Algorithm for Dynamic Uncertain Systems

    Directory of Open Access Journals (Sweden)

    Abdul Kareem

    2012-07-01

    Full Text Available This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness of the proposed controller over the first order Sliding Mode Fuzzy Logic controller is illustrated by Matlab based simulations performed on a DC-DC Buck converter. Based on this comparison, the proposed controller is shown to obtain the desired transient response without causing chattering and error under steady-state conditions. The proposed controller is able to give robust performance in terms of rejection to input voltage variations and load variations.

  19. Real-Time Wavefront Control for the PALM-3000 High Order Adaptive Optics System

    Science.gov (United States)

    Truong, Tuan N.; Bouchez, Antonin H.; Dekany, Richard G.; Guiwits, Stephen R.; Roberts, Jennifer E.; Troy, Mitchell

    2008-01-01

    We present a cost-effective scalable real-time wavefront control architecture based on off-the-shelf graphics processing units hosted in an ultra-low latency, high-bandwidth interconnect PC cluster environment composed of modules written in the component-oriented language of nesC. The architecture enables full-matrix reconstruction of the wavefront at up to 2 KHz with latency under 250 us for the PALM-3000 adaptive optics systems, a state-of-the-art upgrade on the 5.1 meter Hale Telescope that consists of a 64 x 64 subaperture Shack-Hartmann wavefront sensor and a 3368 active actuator high order deformable mirror in series with a 241 active actuator tweeter DM. The architecture can easily scale up to support much larger AO systems at higher rates and lower latency.

  20. Adaptive control for a class of MIMO nonlinear time delay systems against time varying actuator failures.

    Science.gov (United States)

    Hashemi, Mahnaz; Ghaisari, Jafar; Askari, Javad

    2015-07-01

    This paper investigates an adaptive controller for a class of Multi Input Multi Output (MIMO) nonlinear systems with unknown parameters, bounded time delays and in the presence of unknown time varying actuator failures. The type of considered actuator failure is one in which some inputs may be stuck at some time varying values where the values, times and patterns of the failures are unknown. The proposed approach is constructed based on a backstepping design method. The boundedness of all the closed-loop signals is guaranteed and the tracking errors are proved to converge to a small neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark and a chemical reactor system. The simulation results show the effectiveness of the proposed method.

  1. NATO Advanced Research Institute on Adaptive Control of Ill-Defined Systems

    CERN Document Server

    Rissland, Edwina; Arbib, Michael

    1984-01-01

    There are some types of complex systems that are built like clockwork, with well-defined parts that interact in well-defined ways, so that the action of the whole can be precisely analyzed and anticipated with accuracy and precision. Some systems are not themselves so well-defined, but they can be modeled in ways that are like trained pilots in well-built planes, or electrolyte balance in healthy humans. But there are many systems for which that is not true; and among them are many whose understanding and control we would value. For example, the model for the trained pilot above fails exactly where the pilot is being most human; that is, where he is exercising the highest levels of judgment, or where he is learning and adapting to new conditions. Again, sometimes the kinds of complexity do not lead to easily analyzable models at all; here we might include most economic systems, in all forms of societies. There are several factors that seem to contribute to systems being hard to model, understand, or control. ...

  2. Distributed adaptive output consensus control of second-order systems containing unknown non-linear control gains

    Science.gov (United States)

    Wang, Gang; Wang, Chaoli; Du, Qinghui; Cai, Xuan

    2016-10-01

    In this paper, we address the output consensus problem of tracking a desired trajectory for a group of second-order agents on a directed graph with a fixed topology. Each agent is modelled by a second-order non-linear system with unknown non-linear dynamics and unknown non-linear control gains. Only a subset of the agents is given access to the desired trajectory information directly. A distributed adaptive consensus protocol driving all agents to track the desired trajectory is presented using the backstepping technique and approximation technique of Fourier series (FSs). The FS structure is taken not only for tracking the non-linear dynamics but also the unknown portion in the controller design procedure, which can avoid virtual controllers containing the uncertain terms. Stability analysis and parameter convergence of the proposed algorithm are conducted based on the Lyapunov theory and the algebraic graph theory. It is also demonstrated that arbitrary small tracking errors can be achieved by appropriately choosing design parameters. Though the proposed work is applicable for second-order non-linear systems containing unknown non-linear control gains, the proposed controller design can be easily extended to higher-order non-linear systems containing unknown non-linear control gains. Simulation results show the effectiveness of the proposed schemes.

  3. State-of-Charge Balance Using Adaptive Droop Control for Distributed Energy Storage Systems in DC MicroGrid Applications

    DEFF Research Database (Denmark)

    Lu, Xiaonan; Sun, Kai; Guerrero, Josep M.;

    2014-01-01

    This paper presents the coordinated control of distributed energy storage systems (DESSs) in DC micro-grids. In order to balance the state-of-charge (SoC) of each energy storage unit (ESU), an SoC-based adaptive droop control method is proposed. In this decentralized control method, the droop...

  4. ADAPTIVE RESOURCE CONTROL MECHANISM THROUGH REPUTATION-BASED SCHEDULING IN HETEROGENEOUS DISTRIBUTED SYSTEMS

    Directory of Open Access Journals (Sweden)

    Masnida Hussin

    2013-01-01

    Full Text Available The service-oriented distributed systems such as Grids and Clouds are unified computing platform that connect and share heterogeneous resources including computation resource, storage resource, information resource and knowledge resource. While these systems provide a vast amount of computing power their reliability are often hard to be guaranteed. It is due to the increased complexity of processing (e.g., overhead, latency that can indirectly affect the system performance. In this study, we addressed the problem of dynamic control for resource management in distributed computing environment. Our dynamic resource control mechanism is designed based on reputation-based scheduling that aims for sustainable resource sharing. Particularly, each computational resource in the environment has its own reputation value that calculated online by considering the computing capacity and availability. The degree of resource reputation significantly helps in scheduling decisions in terms of successful execution while adaptively monitoring resource availability. Results demonstrate that our resource control mechanism significantly increases successful execution, while leading to robust resource management.

  5. Optical Communication System for Remote Monitoring and Adaptive Control of Distributed Ground Sensors Exhibiting Collective Intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Cameron, S.M.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-11-01

    Comprehensive management of the battle-space has created new requirements in information management, communication, and interoperability as they effect surveillance and situational awareness. The objective of this proposal is to expand intelligent controls theory to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and interoperative global optimization for sensor fusion and mission oversight. By using a layered hierarchal control architecture to orchestrate adaptive reconfiguration of autonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecks. In this concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a covert laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelli- gence opens up a new class of remote-sensing applications in which small single-function autono- mous observers at the local level can collectively optimize and measure large scale ground-level signals. AS the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandwidth requirements within the net. A system of the type described in this proposal will be capable of sensitively detecting, tracking, and mapping spatial distributions of measurement signatures which are non-stationary or obscured by clutter and inter- fering obstacles by virtue of adaptive reconfiguration. This methodology could be used, for example, to field an adaptive ground-penetrating radar for detection of underground structures in

  6. Adaptive Fuzzy Control for CVT Vehicle

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    On the simple continuously variable transmission (CVT) driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.

  7. Direct Adaptive Tracking Control for a Class of Pure-Feedback Stochastic Nonlinear Systems Based on Fuzzy-Approximation

    Directory of Open Access Journals (Sweden)

    Huanqing Wang

    2014-01-01

    Full Text Available The problem of fuzzy-based direct adaptive tracking control is considered for a class of pure-feedback stochastic nonlinear systems. During the controller design, fuzzy logic systems are used to approximate the packaged unknown nonlinearities, and then a novel direct adaptive controller is constructed via backstepping technique. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error eventually converges to a small neighborhood around the origin in the sense of mean quartic value. The main advantages lie in that the proposed controller structure is simpler and only one adaptive parameter needs to be updated online. Simulation results are used to illustrate the effectiveness of the proposed approach.

  8. L1 Adaptive Speed Control of a Small Wind Energy Conversion System for Maximum Power Point Tracking

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard;

    2014-01-01

    This paper presents the design of an L1 adaptive controller for maximum power point tracking (MPPT) of a small variable speed Wind Energy Conversion System (WECS). The proposed controller generates the optimal torque command for the vector controlled generator side converter (GSC) based on the wind...... speed estimation. The proposed MPPT control algorithm has a generic structure and can be used for different generator types. In order to verify the efficacy of the proposed L1 adaptive controller for the MPPT of the WECS, a full converter wind turbine with a squirrel cage induction generator (SCIG...

  9. Adaptive optics system for fast automatic control of laser beam jitters in air

    Science.gov (United States)

    Grasso, Salvatore; Acernese, Fausto; Romano, Rocco; Barone, Fabrizio

    2010-04-01

    Adaptive Optics (AO) Systems can operate fast automatic control of laser beam jitters for several applications of basic research as well as for the improvement of industrial and medical devices. We here present our theoretical and experimental research showing the opportunity of suppressing laser beam geometrical fluctuations of higher order Hermite Gauss modes in interferometric Gravitational Waves (GW) antennas. This in turn allows to significantly reduce the noise that originates from the coupling of the laser source oscillations with the interferometer asymmetries and introduces the concrete possibility of overcoming the sensitivity limit of the GW antennas actually set at 10-23 1 Hz value. We have carried out the feasibility study of a novel AO System which performs effective laser jitters suppression in the 200 Hz bandwidth. It extracts the wavefront error signals in terms of Hermite Gauss (HG) coefficients and performs the wavefront correction using the Zernike polynomials. An experimental Prototype of the AO System has been implemented and tested in our laboratory at the University of Salerno and the results we have achieved fully confirm effectiveness and robustness of the control upon first and second order laser beam geometrical fluctuations, in good accordance with GW antennas requirements. Above all, we have measured 60 dB reduction of astigmatism and defocus modes at low frequency below 1 Hz and 20 dB reduction in the 200 Hz bandwidth.

  10. Adaptive tracking control of leader-following linear multi-agent systems with external disturbances

    Science.gov (United States)

    Lin, Hanquan; Wei, Qinglai; Liu, Derong; Ma, Hongwen

    2016-10-01

    In this paper, the consensus problem for leader-following linear multi-agent systems with external disturbances is investigated. Brownian motions are used to describe exogenous disturbances. A distributed tracking controller based on Riccati inequalities with an adaptive law for adjusting coupling weights between neighbouring agents is designed for leader-following multi-agent systems under fixed and switching topologies. In traditional distributed static controllers, the coupling weights depend on the communication graph. However, coupling weights associated with the feedback gain matrix in our method are updated by state errors between neighbouring agents. We further present the stability analysis of leader-following multi-agent systems with stochastic disturbances under switching topology. Most traditional literature requires the graph to be connected all the time, while the communication graph is only assumed to be jointly connected in this paper. The design technique is based on Riccati inequalities and algebraic graph theory. Finally, simulations are given to show the validity of our method.

  11. Adaptive gain control for spike-based map communication in a neuromorphic vision system.

    Science.gov (United States)

    Meng, Yicong; Shi, Bertram E

    2008-06-01

    To support large numbers of model neurons, neuromorphic vision systems are increasingly adopting a distributed architecture, where different arrays of neurons are located on different chips or processors. Spike-based protocols are used to communicate activity between processors. The spike activity in the arrays depends on the input statistics as well as internal parameters such as time constants and gains. In this paper, we investigate strategies for automatically adapting these parameters to maintain a constant firing rate in response to changes in the input statistics. We find that under the constraint of maintaining a fixed firing rate, a strategy based upon updating the gain alone performs as well as an optimal strategy where both the gain and the time constant are allowed to vary. We discuss how to choose the time constant and propose an adaptive gain control mechanism whose operation is robust to changes in the input statistics. Our experimental results on a mobile robotic platform validate the analysis and efficacy of the proposed strategy.

  12. A Novel Fuzzy Logic Based Adaptive Super-Twisting Sliding Mode Control Algorithm for Dynamic Uncertain Systems

    Directory of Open Access Journals (Sweden)

    Abdul Kareem

    2012-08-01

    Full Text Available This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for thecontrol of dynamic uncertain systems. The proposed controller combines the advantages of Second orderSliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability androbustness of the system with the proposed controller are guaranteed. In addition, the proposed controlleris well suited for simple design and implementation. The effectiveness of the proposed controller over thefirst order Sliding Mode Fuzzy Logic controller is illustrated by Matlab based simulations performed on aDC-DC Buck converter. Based on this comparison, the proposed controller is shown to obtain the desiredtransient response without causing chattering and error under steady-state conditions. The proposedcontroller is able to give robust performance in terms of rejection to input voltage variations and loadvariations

  13. Application of self-adaptive feed-forward control in linac systems

    International Nuclear Information System (INIS)

    In this paper, the basis of the self-adaptive feed-forward RF control (SAFF) is discussed and its analytical formulation introduced. It is adopted in Beijing Free Electron Laser facility (BFEL) to control the beam loading effect of the thermionic cathode RF gun and proves to be effective. Other possible applications of SAFF in linac are also discussed

  14. On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

    Science.gov (United States)

    Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

    2016-01-01

    The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

  15. General solution to diagonal model matching control of multiple-output-delay systems and its applications in adaptive scheme

    Institute of Scientific and Technical Information of China (English)

    Yingmin Jia

    2009-01-01

    This paper mainly studies the model matching problem of multiple-output-delay systems in which the reference model is assigned to a diagonal transfer function matrix.A new model matching controller structure is first developed,and then,it is shown that the controller is feasible if and only if the sets of Diophantine equations have common solutions.The obtained controller allows a parametric representation,which shows that an adaptive scheme can be used to tolerate parameter variations in the plants.The resulting adaptive law can guarantee the global stability of the closed-loop systems and the convergence of the output error.

  16. New Adaptive Approach for Road Condition Identification in ASR Control System

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A novel tire-road adaptive model in longitude direction to formulate the dynamic characteristic between tire and road is proposed in this paper, based on this model, a new adaptive approach of road condition identification is presented to identify the model's parameters on-line in order to improve the performance of anti-slip regulation system(ASR). The optimal slip is determined by using the drive wheel's slip and longitude traction force in ASR before the slipping of the drive wheel. Co-simulation is done based on the model for JETTA GTX building with ADAMS/CAR and Matlab, and results show that the adaptive model accords with Pacejka model very well. This adaptive model has simpler form, less number of parameters and higher adaptability than usual, and the new identification approach has a small amounts of operation, which is very suitful for ASR.

  17. Adaptive Vector Control of Induction Motor

    Directory of Open Access Journals (Sweden)

    O. F. Opeiko

    2012-01-01

    Full Text Available A synthesis of adaptive PID controller has been executed for flux linkage and speed channels of a vector control system for an induction short-circuited motor. While using an imitation simulation method results of a synthesized system analysis show that the adaptive PID controller has some advantages under conditions of parametric disturbances affecting the object.

  18. Parameter identification and synchronization of an uncertain Chen chaotic system via adaptive control

    Institute of Scientific and Technical Information of China (English)

    陈士华; 赵立民; 刘杰

    2002-01-01

    A systematic design process of adaptive synchronization and parameter identification of an uncertain Chen chaotic system is provided. With this new and effective method, parameter identification and synchronization of the Chen system, with all the system parameters unknown, can be achieved simultaneously. Theoretical proof and numerical simulation demonstrate the effectiveness and feasibility of the proposed method.

  19. Intelligent Voice-Based Door Access Control System Using Adaptive-Network-based Fuzzy Inference Systems (ANFIS for Building Security

    Directory of Open Access Journals (Sweden)

    Wahyudi

    2007-01-01

    Full Text Available Secure buildings are currently protected from unauthorized access by a variety of devices. Even though there are many kinds of devices to guarantee the system safety such as PIN pads, keys both conventional and electronic, identity cards, cryptographic and dual control procedures, the people voice can also be used. The ability to verify the identity of a speaker by analyzing speech, or speaker verification, is an attractive and relatively unobtrusive means of providing security for admission into an important or secured place. An individual’s voice cannot be stolen, lost, forgotten, guessed, or impersonated with accuracy. Due to these advantages, this paper describes design and prototyping a voice-based door access control system for building security. In the proposed system, the access may be authorized simply by means of an enrolled user speaking into a microphone attached to the system. The proposed system then will decide whether to accept or reject the user’s identity claim or possibly to report insufficient confidence and request additional input before making the decision. Furthermore, intelligent system approach is used to develop authorized person models based on theirs voice. Particularly Adaptive-Network-based Fuzzy Inference Systems is used in the proposed system to identify the authorized and unauthorized people. Experimental result confirms the effectiveness of the proposed intelligent voice-based door access control system based on the false acceptance rate and false rejection rate.

  20. Adaptive Hysteresis Band Current Control (AHB) with PLL of Grid Side Converter-Based Wind Power Generation System

    DEFF Research Database (Denmark)

    Guo, Yougui; Zeng, Ping; Li, Lijuan;

    2011-01-01

    Adaptive hysteresis band current control(AHB CC) is used to control the three-phase grid currents by means of grid side converter in wind power generation system in this paper. AHB has reached the good purpose with PLL (Lock phase loop). First the mathematical models of each part are given. Then ...

  1. Direct Adaptive Fuzzy Sliding Mode Control with Variable Universe Fuzzy Switching Term for a Class of MIMO Nonlinear Systems

    Directory of Open Access Journals (Sweden)

    Guo Haigang

    2012-01-01

    Full Text Available Combining adaptive fuzzy sliding mode control with fuzzy or variable universe fuzzy switching technique, this study develops two novel direct adaptive schemes for a class of MIMO nonlinear systems with uncertainties and external disturbances. The proposed control schemes consist of fuzzy equivalent control terms, fuzzy switching control terms (in scheme one or variable universe fuzzy switching control terms (in scheme two, and compensation control terms. The compensation control terms are used to relax the assumption on fuzzy approximation error. Based on Lyapunov stability theory, the parameters update laws are adaptively tuned online and the global asymptotic stability of the closed-loop system can be guaranteed. The major contribution of this study is to develop a novel framework for designing direct adaptive fuzzy sliding mode control scheme facing model uncertainties and external disturbances. The derived schemes can effectively solve the chattering problem and the equivalent control calculation in that environment. Simulation results performed on a two-link robotic manipulator demonstrate the feasibility of the proposed control schemes.

  2. Adaptive variable structure control for large-scale time-delayed systems with unknown nonlinear dead-zone

    Institute of Scientific and Technical Information of China (English)

    Shen Qikun; Zhang Tianping

    2007-01-01

    The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adaptive, decentralized, variable structure control is proposed. The approach removes the conditions that the dead-zone slopes and boundaries are equal and symmetric, respectively. In addition, it does not require that the assumptions that all parameters of the nonlinear dead-zone model and the lumped uncertainty are known constants. The adaptive compensation terms of the approximation errors are adopted to minimize the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.

  3. Adaptive fault-tolerant control of linear time-invariant systems in the presence of actuator saturation

    Institute of Scientific and Technical Information of China (English)

    Wei GUAN; Guanghong YANG

    2009-01-01

    This paper studies the problem of designing adaptive fault-tolerant controllers for linear time-invariant systems with actuator saturation.New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compensations.Based on the on-line estimation of eventual faults,the adaptive fault-tolerant controller parameters are updating automatically to compensate the fault effects on systems.The designs are developed in the framework of linear matrix inequality (LMI) approach,which can enlarge the domain of attraction of closed-loop systems in the cases of actuator saturation and actuator failures.Two examples are given to illustrate the effectiveness of the design method.

  4. A new impedance and robust adaptive inverse control approach for a teleoperation system with varying time delay

    Institute of Scientific and Technical Information of China (English)

    Mokhtar SHA SADEGHI; Hamid Reza MOMENI

    2009-01-01

    This paper presents a new robust adaptive inverse control approach for a force-reflecting teleoperation system with varying time delay. First, an impedance control is designed for the master robot. Second, an adaptive inverse control is proposed for the slave robot. Finally, the slave side controller is modified such that the robust stability and performance are achieved. In addition, robust stability analysis has been performed and optimal behavior is ensured by using standard characteristic polynomials. It is shown that despite of presence of randomly-varying time delay, the proposed control algorithm com-pensates the position drifts efficiently. Demonstrable simulation studies confirm the effectiveness of the proposed control system and its advantages over the existing sliding mode control strategies.

  5. A new impedance and robust adaptive inverse control approach for a teleoperation system with varying time delay

    Institute of Scientific and Technical Information of China (English)

    Mokhtar; SHA; SADEGHI; Hamid; Reza; MOMENI

    2009-01-01

    This paper presents a new robust adaptive inverse control approach for a force-reflecting teleoperation system with varying time delay. First,an impedance control is designed for the master robot. Second,an adaptive inverse control is proposed for the slave robot. Finally,the slave side controller is modified such that the robust stability and performance are achieved. In addition,robust stability analysis has been performed and optimal behavior is ensured by using standard characteristic polynomials. It is shown that despite of presence of randomly-varying time delay,the proposed control algorithm compensates the position drifts efficiently. Demonstrable simulation studies confirm the effectiveness of the proposed control system and its advantages over the existing sliding mode control strategies.

  6. The Self-Adaptive Fuzzy PID Controller in Actuator Simulated Loading System

    OpenAIRE

    Chuanhui Zhang; Xiaodong Song

    2013-01-01

    This paper analyzes the structure principle of the actuator simulated loading system with variable stiffness, and establishes the simplified model. What’s more, it also does a research on the application of the self-adaptive tuning of fuzzy PID(Proportion Integration Differentiation) in actuator simulated loading system with variable stiffness. Because the loading system is connected with the steering system by a spring rod, there must be strong coupling. Besides, there are also the parametri...

  7. Adaptive vibration suppression system: An iterative control law for a piezoelectric actuator shunted by a negative capacitor

    CERN Document Server

    Kodejska, Milos; Linhart, Vaclav; Vaclavik, Jan; Sluka, Tomas

    2014-01-01

    An adaptive system for the suppression of vibration transmission using a single piezoelectric actuator shunted by a negative capacitance circuit is presented. It is known that using negative capacitance shunt, the spring constant of piezoelectric actuator can be controlled to extreme values of zero or infinity. Since the value of spring constant controls a force transmitted through an elastic element, it is possible to achieve a reduction of transmissibility of vibrations through a piezoelectric actuator by reducing its effective spring constant. The narrow frequency range and broad frequency range vibration isolation systems are analyzed, modeled, and experimentally investigated. The problem of high sensitivity of the vibration control system to varying operational conditions is resolved by applying an adaptive control to the circuit parameters of the negative capacitor. A control law that is based on the estimation of the value of effective spring constant of shunted piezoelectric actuator is presented. An ...

  8. AN ADAPTIVE OPTIMAL KALMAN FILTER FOR STOCHASTIC VIBRATION CONTROL SYSTEM WITH UNKNOWN NOISE VARIANCES

    Institute of Scientific and Technical Information of China (English)

    Li Shu; Zhuo Jiashou; Ren Qingwen

    2000-01-01

    In this paper, an optimal criterion is presented for adaptive Kalman filter in a control sys tem with unknown variances of stochastic vibration by constructing a function of noise variances and minimizing the function. We solve the model and measure variances by using DFP optimal method to guarantee the results of Kalman filter to be optimized. Finally, the control of vibration can be implemented by LQG method.

  9. Adaptive fuzzy control with smooth inverse for nonlinear systems preceded by non-symmetric dead-zone

    Science.gov (United States)

    Wang, Xingjian; Wang, Shaoping

    2016-07-01

    In this study, the adaptive output feedback control problem of a class of nonlinear systems preceded by non-symmetric dead-zone is considered. To cope with the possible control signal chattering phenomenon which is caused by non-smooth dead-zone inverse, a new smooth inverse is proposed for non-symmetric dead-zone compensation. For the systematic design procedure of the adaptive fuzzy control algorithm, we combine the backstepping technique and small-gain approach. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown system nonlinearities. The closed-loop stability is studied by using small gain theorem and the closed-loop system is proved to be semi-globally uniformly ultimately bounded. Simulation results indicate that, compared to the algorithm with the non-smooth inverse, the proposed control strategy can achieve better tracking performance and the chattering phenomenon can be avoided effectively.

  10. Local Ensemble Transform Kalman Filter: a non-stationary control law for complex adaptive optics systems on ELTs

    CERN Document Server

    Gray, Morgan; Rodionov, Sergey; Bertino, Laurent; Bocquet, Marc; Fusco, Thierry

    2013-01-01

    We propose a new algorithm for an adaptive optics system control law which allows to reduce the computational burden in the case of an Extremely Large Telescope (ELT) and to deal with non-stationary behaviors of the turbulence. This approach, using Ensemble Transform Kalman Filter and localizations by domain decomposition is called the local ETKF: the pupil of the telescope is split up into various local domains and calculations for the update estimate of the turbulent phase on each domain are performed independently. This data assimilation scheme enables parallel computation of markedly less data during this update step. This adapts the Kalman Filter to large scale systems with a non-stationary turbulence model when the explicit storage and manipulation of extremely large covariance matrices are impossible. First simulation results are given in order to assess the theoretical analysis and to demonstrate the potentiality of this new control law for complex adaptive optics systems on ELTs.

  11. Fuzzy Adaptive Repetitive Control for Periodic Disturbance with Its Application to High Performance Permanent Magnet Synchronous Motor Speed Servo Systems

    Directory of Open Access Journals (Sweden)

    Junxiao Wang

    2016-09-01

    Full Text Available For reducing the steady state speed ripple, especially in high performance speed servo system applications, the steady state precision is more and more important for real servo systems. This paper investigates the steady state speed ripple periodic disturbance problem for a permanent magnet synchronous motor (PMSM servo system; a fuzzy adaptive repetitive controller is designed in the speed loop based on repetitive control and fuzzy information theory for reducing periodic disturbance. Firstly, the various sources of the PMSM speed ripple problem are described and analyzed. Then, the mathematical model of PMSM is given. Subsequently, a fuzzy adaptive repetitive controller based on repetitive control and fuzzy logic control is designed for the PMSM speed servo system. In addition, the system stability analysis is also deduced. Finally, the simulation and experiment implementation are respectively based on the MATLAB/Simulink and TMS320F2808 of Texas instrument company, DSP (digital signal processor hardware platform. Comparing to the proportional integral (PI controller, simulation and experimental results show that the proposed fuzzy adaptive repetitive controller has better periodic disturbance rejection ability and higher steady state precision.

  12. Effect of adaptive cruise control systems on mixed traffic flow near an on-ramp

    Science.gov (United States)

    Davis, L. C.

    2007-06-01

    Mixed traffic flow consisting of vehicles equipped with adaptive cruise control (ACC) and manually driven vehicles is analyzed using car-following simulations. Simulations of merging from an on-ramp onto a freeway reported in the literature have not thus far demonstrated a substantial positive impact of ACC. In this paper cooperative merging for ACC vehicles is proposed to improve throughput and increase distance traveled in a fixed time. In such a system an ACC vehicle senses not only the preceding vehicle in the same lane but also the vehicle immediately in front in the other lane. Prior to reaching the merge region, the ACC vehicle adjusts its velocity to ensure that a safe gap for merging is obtained. If on-ramp demand is moderate, cooperative merging produces significant improvement in throughput (20%) and increases up to 3.6 km in distance traveled in 600 s for 50% ACC mixed flow relative to the flow of all-manual vehicles. For large demand, it is shown that autonomous merging with cooperation in the flow of all ACC vehicles leads to throughput limited only by the downstream capacity, which is determined by speed limit and headway time.

  13. An adaptive control strategy of converter based DG to maintain protection coordination in distribution system

    DEFF Research Database (Denmark)

    Su, Chi; Liu, Zhou; Chen, Zhe;

    2014-01-01

    of network protection devices. As a protection measure commonly used in distribution network, recloser-fuse coordination could suffer from this impact. Research work has been conducted to deal with this problem by modifying the control strategy of the DG converters during faults. These solutions generally...... reduce the current output from the converters during faults so as to mitigate the influence on protection coordination. However, converter current reduction may not be necessary for all types of faults. This paper proposes a converter control strategy with adaptivity to different fault types and also non......-fault voltage drop events. This control strategy is validated by simulations in DIgSILENT PowerFactory....

  14. Adaptive neural tracking control of a class of MIMO pure-feedback time-delay nonlinear systems with input saturation

    Science.gov (United States)

    Yang, Yang; Yue, Dong; Yuan, Deming

    2016-11-01

    Considering interconnections among subsystems, we propose an adaptive neural tracking control scheme for a class of multiple-input-multiple-output (MIMO) non-affine pure-feedback time-delay nonlinear systems with input saturation. Neural networks (NNs) are employed to approximate unknown functions in the design procedure, and the separation technology is introduced here to tackle the problem induced from unknown time-delay items. The adaptive neural tracking control scheme is constructed by combining Lyapunov-Krasovskii functionals, NNs, the auxiliary system, the implicit function theory and the mean value theorem along with the dynamic surface control technique. Also, it is proven that the strategy guarantees tracking errors converge to a small neighbourhood around the origin by appropriate choice of design parameters and all signals in the closed-loop system uniformly ultimately bounded. Numerical simulation results are presented to demonstrate the effectiveness of the proposed control strategy.

  15. Robust adaptive control for a class of uncertain non-affine nonlinear systems using affine-type neural networks

    Science.gov (United States)

    Zhao, Shitie; Gao, Xianwen

    2016-08-01

    A robust adaptive control is proposed for a class of single-input single-output non-affine nonlinear systems. In order to approximate the unknown nonlinear function, a novel affine-type neural network is used, and then to compensate the approximation error and external disturbance a robust control term is employed. By Lyapunov stability analysis for the closed-loop system, it is proved that tracking errors asymptotically converge to zero. Moreover, an observer is designed to estimate the system states because all the states may not be available for measurements. Furthermore, the adaptation laws of neural networks and the robust controller are given out based on the Lyapunov stability theory. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed control method.

  16. PLC Based Adaptive PID Control of Non Linear Liquid Tank System using Online Estimation of Linear Parameters by Difference Equations

    Directory of Open Access Journals (Sweden)

    Kesavan.E

    2013-04-01

    Full Text Available This paper suggests an idea to design an adaptive PID controller for Non-linear liquid tank System and is implemented in PLC. Online estimation of linear parameters (Time constant and Gain brings an exact model of the process to take perfect control action. Based on these estimated values, the controller parameters will be well tuned by internal model control. Internal model control is an unremarkably used technique and provides well tuned controller in order to have a good controlling process. PLC with its ability to have both continues control for PID Control and digital control for fault diagnosis which ascertains faults in the system and provides alerts about the status of the entire process.

  17. Maximum Power Point Tracking Using Adaptive Fuzzy Logic control for Photovoltaic System

    Directory of Open Access Journals (Sweden)

    Anass Ait Laachir

    2015-01-01

    Full Text Available This work presents an intelligent approach to the improvement and optimization of control performance of a photovoltaic system with maximum power point tracking based on fuzzy logic control. This control was compared with the conventional control based on Perturb &Observe algorithm. The results obtained in Matlab/Simulink under different conditions show a marked improvement in the performance of fuzzy control MPPT of the PV system.

  18. Identifier-based adaptive neural dynamic surface control for uncertain DC-DC buck converter system with input constraint

    Science.gov (United States)

    Chen, Qiang; Ren, Xuemei; Oliver, Jesus Angel

    2012-04-01

    In this paper, an identifier-based adaptive neural dynamic surface control (IANDSC) is proposed for the uncertain DC-DC buck converter system with input constraint. Based on the analysis of the effect of input constraint in the buck converter, the neural network compensator is employed to ensure the controller output within the permissible range. Subsequently, the constrained adaptive control scheme combined with the neural network compensator is developed for the buck converter with uncertain load current. In this scheme, a newly presented finite-time identifier is utilized to accelerate the parameter tuning process and to heighten the accuracy of parameter estimation. By utilizing the adaptive dynamic surface control (ADSC) technique, the problem of "explosion of complexity" inherently in the traditional adaptive backstepping design can be overcome. The proposed control law can guarantee the uniformly ultimate boundedness of all signals in the closed-loop system via Lyapunov synthesis. Numerical simulations are provided to illustrate the effectiveness of the proposed control method.

  19. Hyperchaos control and adaptive synchronization with uncertain parameter for fractional-order Mathieu–van der Pol systems

    Indian Academy of Sciences (India)

    Kumar Vishal; Saurabh K Agrawal; Subir Das

    2016-01-01

    In this paper, we have discussed the local stability of the Mathieu–van der Pol hyperchaotic system with the fractional-order derivative. The fractional Routh–Hurwitz stability conditions were provided and were used to discuss the stability. Feedback control method was used to control chaos in the Mathieu–van der Pol system with fractional-order derivative and after controlling the chaotic behaviour of the system the synchronization between the fractional-order hyperchaotic Mathieu–van der Pol system and controlled system was introduced. In this study, modified adaptive control methods with uncertain parameters at various equilibrium points were used. Also the analysis of control time with respect to different fractional-order derivatives is the key feature of this paper. Numerical simulation results achieved using Adams–Boshforth–Moulton method show that the method is effective and reliable.

  20. Motion synchronization of dual-cylinder pneumatic servo systems with integration of adaptive robust control and cross-coupling approach

    Institute of Scientific and Technical Information of China (English)

    De-yuan MENG; Guo-liang TAO; Ai-min LI; Wei LI

    2014-01-01

    We investigate motion synchronization of dual-cylinder pneumatic servo systems and develop an adaptive robust synchronization controller. The proposed controller incorporates the cross-coupling technology into the integrated direct/indirect adaptive robust control (DIARC) architecture by feeding back the coupled position errors, which are formed by the trajectory tracking errors of two cylinders and the synchronization error between them. The controller employs an online recursive least squares estimation algorithm to obtain accurate estimates of model parameters for reducing the extent of parametric uncertainties, and uses a robust control law to attenuate the effects of parameter estimation errors, unmodeled dynamics, and disturbances. Therefore, asymptotic convergence to zero of both trajectory tracking and synchronization errors can be guaranteed. Experimental results verify the effectiveness of the proposed controller.

  1. In-Flight Suppression of a De-Stabilized F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

    Science.gov (United States)

    Wall, John; VanZwieten, Tannen; Giiligan Eric; Miller, Chris; Hanson, Curtis; Orr, Jeb

    2015-01-01

    Adaptive Augmenting Control (AAC) has been developed for NASA's Space Launch System (SLS) family of launch vehicles and implemented as a baseline part of its flight control system (FCS). To raise the technical readiness level of the SLS AAC algorithm, the Launch Vehicle Adaptive Control (LVAC) flight test program was conducted in which the SLS FCS prototype software was employed to control the pitch axis of Dryden's specially outfitted F/A-18, the Full Scale Advanced Systems Test Bed (FAST). This presentation focuses on a set of special test cases which demonstrate the successful mitigation of the unstable coupling of an F/A-18 airframe structural mode with the SLS FCS.

  2. Online adaptive policy learning algorithm for H∞ state feedback control of unknown affine nonlinear discrete-time systems.

    Science.gov (United States)

    Zhang, Huaguang; Qin, Chunbin; Jiang, Bin; Luo, Yanhong

    2014-12-01

    The problem of H∞ state feedback control of affine nonlinear discrete-time systems with unknown dynamics is investigated in this paper. An online adaptive policy learning algorithm (APLA) based on adaptive dynamic programming (ADP) is proposed for learning in real-time the solution to the Hamilton-Jacobi-Isaacs (HJI) equation, which appears in the H∞ control problem. In the proposed algorithm, three neural networks (NNs) are utilized to find suitable approximations of the optimal value function and the saddle point feedback control and disturbance policies. Novel weight updating laws are given to tune the critic, actor, and disturbance NNs simultaneously by using data generated in real-time along the system trajectories. Considering NN approximation errors, we provide the stability analysis of the proposed algorithm with Lyapunov approach. Moreover, the need of the system input dynamics for the proposed algorithm is relaxed by using a NN identification scheme. Finally, simulation examples show the effectiveness of the proposed algorithm. PMID:25095274

  3. Adaptive Fuzzy Tracking Control for Uncertain Nonlinear Time-Delay Systems with Unknown Dead-Zone Input

    Directory of Open Access Journals (Sweden)

    Chiang-Cheng Chiang

    2013-01-01

    Full Text Available The tracking control problem of uncertain nonlinear time-delay systems with unknown dead-zone input is tackled by a robust adaptive fuzzy control scheme. Because the nonlinear gain function and the uncertainties of the controlled system including matched and unmatched uncertainties are supposed to be unknown, fuzzy logic systems are employed to approximate the nonlinear gain function and the upper bounded functions of these uncertainties. Moreover, the upper bound of the uncertainty caused by the fuzzy modeling error is also estimated. According to these learning fuzzy models and some feasible adaptive laws, a robust adaptive fuzzy tracking controller is developed in this paper without constructing the dead-zone inverse. Based on the Lyapunov stability theorem, the proposed controller not only guarantees that the robust stability of the whole closed-loop system in the presence of uncertainties and unknown dead-zone input can be achieved, but it also obtains that the output tracking error can converge to a neighborhood of zero exponentially. Some simulation results are provided to demonstrate the effectiveness and performance of the proposed approach.

  4. Adaptive Control of Rigid Body Satellite

    Institute of Scientific and Technical Information of China (English)

    Thawar T. Arif

    2008-01-01

    The minimal controller synthesis (MCS) is an extension of the hyperstable model reference adaptive control algorithm. The aim of minimal controller synthesis is to achieve excellent closed-loop control despite the presence of plant parameter variations, external disturbances, dynamic coupling within the plant and plant nonlinearities. The minimal controller synthesis algorithm was successfully applied to the problem of decentralized adaptive schemes. The decentralized minimal controller synthesis adaptive control strategy for controlling the attitude of a rigid body satellite is adopted in this paper. A model reference adaptive control strategy which uses one single three-axis slew is proposed for the purpose of controlling the attitude of a rigid body satellite. The simulation results are excellent and show that the controlled system is robust against disturbances.

  5. Dynamics and Control of Adaptive Shells with Curvature Transformations

    OpenAIRE

    H.S. Tzou; Bao, Y

    1995-01-01

    Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencie...

  6. Adaptive Inverse Optimal Control of a Novel Fractional-Order Four-Wing Hyperchaotic System with Uncertain Parameter and Circuitry Implementation

    OpenAIRE

    Chaojun Wu; Gangquan Si; Yanbin Zhang; Ningning Yang

    2015-01-01

    An efficient approach of inverse optimal control and adaptive control is developed for global asymptotic stabilization of a novel fractional-order four-wing hyperchaotic system with uncertain parameter. Based on the inverse optimal control methodology and fractional-order stability theory, a control Lyapunov function (CLF) is constructed and an adaptive state feedback controller is designed to achieve inverse optimal control of a novel fractional-order hyperchaotic system with four-wing attra...

  7. Knowledge-based adaptive neural control of drum level in a boiler system

    Science.gov (United States)

    Tripathi, Nishith; Tran, Michael; VanLandingham, Hugh

    1995-11-01

    A boiler system is an integral component of a thermal power plant, and control of the water level in the drum of the boiler system is a critical operational consideration. For the drum level control, a 3-element proportional-integral-derivative (PID) control is a popular conventional approach. This scheme works satisfactorily in the absence of any process disturbances. However, when there are significant process disturbances, the 3-element PID control scheme does not perform well because of lack of knowledge of proper controller gains to cope with such disturbances. Inevitably over time and use, PID controllers get detuned. Hence, there is good motivation to investigate alternatives to this control scheme. Multivariable control of drum boiler systems has been studied by many researchers. However, these approaches assume some process model equations (to a more or less extent) to design a controller. This paper presents a model-free approach in the sense that no plant equations are assumed. Only data is used to gain knowledge about the process, and the performance of the existing PID control scheme is observed. Based on this process knowledge, an intelligent control technique is developed, (artificial) neural network control (NNC). The technique proposed in this paper was tested on a process simulator. This paper shows that an intelligent control scheme such as NNC gives better performance in rejecting process disturbances when compared to 3-element PID control scheme.

  8. Life in the Fast Lane: The Evolution of an Adaptive Vehicle Control System

    OpenAIRE

    Jochem, Todd; Pomerleau, Dean

    1996-01-01

    Giving robots the ability to operate in the real world has been, and continues to be, one of the most difficult tasks in AI research. Since 1987, researchers at Carnegie Mellon University have been investigating one such task. Their research has been focused on using adaptive, vision-based systems to increase the driving performance of the Navlab line of on-road mobile robots. This research has led to the development of a neural network system that can learn to drive on many road types simply...

  9. Adaptive Neuro Fuzzy Inference Controller for Full Vehicle Nonlinear Active Suspension Systems

    Directory of Open Access Journals (Sweden)

    A. Aldair

    2010-12-01

    Full Text Available The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence Neuro-Fuzzy (NF technique to design a robust controller to meet the control objectives. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The approach of the proposed controller is to minimize the vibrations on each corner of vehicle by supplying control forces to suspension system when travelling on rough road. The other purpose for using the NF controller for vehicle model is to reduce the body inclinations that are made during intensive manoeuvres including braking and cornering. A full vehicle nonlinear active suspension system is introduced and tested. The robustness of the proposed controller is being assessed by comparing with an optimal Fractional Order PIλ Dμ (FOPID controller. The results show that the intelligent NF controller has improved the dynamic response measured by decreasing the cost function.

  10. Dynamic optimization and adaptive controller design

    Science.gov (United States)

    Inamdar, S. R.

    2010-10-01

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

  11. Nonlinear, Adaptive and Fault-tolerant Control for Electro-hydraulic Servo Systems

    DEFF Research Database (Denmark)

    Choux, Martin

    Fluid power systems have been in use since 1795 with the rst hydraulic press patented by Joseph Bramah and today form the basis of many industries. Electro hydraulic servo systems are uid power systems controlled in closed-loop. They transform reference input signals into a set of movements...... numerous attractive properties, hydraulic systems are always subject to potential leakages in their components, friction variation in their hydraulic actuators and deciency in their sensors. These violations of normal behaviour reduce the system performances and can lead to system failure......-tolerant control for a representative electro hydraulic servo controlled motion system. The thesis extends existing models of hydraulic systems by considering more detailed dynamics in the servo valve and in the friction inside the hydraulic cylinder. It identies the model parameters using experimental data from...

  12. Wavelet Neural Network Observer Based Adaptive Tracking Control for a Class of Uncertain Nonlinear Delayed Systems Using Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Manish Sharma

    2012-03-01

    Full Text Available This paper is concerned with the observer designing problem for a class of uncertain delayed nonlinear systems using reinforcement learning. Reinforcement learning is used via two Wavelet Neural networks (WNN, critic WNN and action WNN, which are combined to form an adaptive WNN controller. The “strategic” utility function is approximated by the critic WNN and is minimized by the action WNN. Adaptation laws are developed for the online tuning of wavelets parameters. By Lyapunov approach, the uniformly ultimate boundedness of the closed-loop tracking error is verified. Finally, a simulation example is shown to verify the effectiveness and performance of the proposed method.

  13. Digital adaptive control laws for VTOL aircraft

    Science.gov (United States)

    Hartmann, G. L.; Stein, G.

    1979-01-01

    Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.

  14. Nonlinear, Adaptive and Fault-tolerant Control for Electro-hydraulic Servo Systems

    OpenAIRE

    Choux, Martin; Blanke, Mogens; Hovland, Geir

    2011-01-01

    Fluid power systems have been in use since 1795 with the rst hydraulic press patented by Joseph Bramah and today form the basis of many industries. Electro hydraulic servo systems are uid power systems controlled in closed-loop. They transform reference input signals into a set of movements in hydraulic actuators (cylinders or motors) by the means of hydraulic uid under pressure. With the development of computing power and control techniques during the last few decades, they are used increasi...

  15. IMITATING THE MODEL OF THE FREQUENCY CONVERTER - INDUCTION MOTOR OF A PUMP WATER SYSTEM WITH ADAPTIVE CONTROL ALGORITHM

    Directory of Open Access Journals (Sweden)

    Taranov D. M.

    2015-06-01

    Full Text Available This article presents main water supply systems and justifies the choice of direct flow of water supply system in the application of regulation of electric drive for pumps, which doesn’t have any tanks to create pressures required for fire-governmental purposes. This avoids interruption in the supply of reserve while water freezing. In the article the substantiation of the necessity of implementation of adaptive algorithm in modern-WIDE frequency converters by a substantiation of the number of stages of ratio control of voltage-frequency mains. It was revealed that the number of degrees of regulation of 10-12 gives optimum. Modern frequency converters allow you to change the regulation law, establishing 3-5 points of regulation. Therefore, the introduction of adaptive algorithm will reduce the power consumption of the electric drive of the pump of the water supply system. The article shows the simulation model of the "the converter frequency-induction motor," plots of the stator current of mains frequency and active power, surface speed and phase current when changing the voltage and frequency of the mains. These dependences confirm to have applicability of adaptive algorithm in the regulation of modern frequency converters with the skalar administration. Simulation model confirms the sub-physical experiments on a real motor and frequency converter with adaptive control algorithm. As a result of the selection of the parameters, we obtain the voltage reduction of the phase current, and reduce electricity consumption by 5-7%

  16. Study on Fuzzy Adaptive Fractional Order PIλDμ Control for Maglev Guiding System

    Science.gov (United States)

    Hu, Qing; Hu, Yuwei

    The mathematical model of the linear elevator maglev guiding system is analyzed in this paper. For the linear elevator needs strong stability and robustness to run, the integer order PID was expanded to the fractional order, in order to improve the steady state precision, rapidity and robustness of the system, enhance the accuracy of the parameter in fractional order PIλDμ controller, the fuzzy control is combined with the fractional order PIλDμ control, using the fuzzy logic achieves the parameters online adjustment. The simulations reveal that the system has faster response speed, higher tracking precision, and has stronger robustness to the disturbance.

  17. Adaptive Control with SSNN of UPFC System for the Compensation of Active and Reactive Power

    Directory of Open Access Journals (Sweden)

    A. Bouanane

    2013-06-01

    Full Text Available The focus of this study is the effectiveness of the controller’s Unified Power Flow Controller UPFC with the choice of a control strategy. This Unified Power Flow Controller (UPFC is used to control the power flow in the transmission systems by controlling the impedance, voltage magnitude and phase angle. This controller offers advantages in terms of static and dynamic operation of the power system. It also brings in new challenges in power electronics and power system design. To evaluate the performance and robustness of the system, we proposed a hybrid control combining the concept of identification neural networks with conventional regulators and with the changes in characteristics of the transmission line in order to improve the stability of the electrical power network. With its unique capability to control simultaneously real and reactive power flows on a transmission line as well as to regulate voltage at the bus where it is connected, this device creates a tremendous quality impact on power system stability. The result which has been obtained from using MATLAB and SIMULINK software showed a good agreement with the simulation result.

  18. A prediction-based self-adaptive feed-forward control system for thermionic cathode microwave electron gun

    International Nuclear Information System (INIS)

    Beijing Free Electron Laser Facility (BFEL) adopts a thermionic cathode microwave electron gun as its RF linac injector. For relatively long macro-pulse operation, the back-bombardment effect deteriorates the characteristics of the accelerated electron beam. So the authors developed a prediction-based self-adaptive feed-forward control system to compensate for the beam-loading. The system is operational and some experimental results have been obtained, which suggests that the system is effective to improve the beam quality, and that it's capable of dealing with complicated systems whose response is time-variable, non-linear and of long delay

  19. Implementation of an Intelligent Adaptive Controller for an Electrohydraulic Servo System Based on a Brain Mechanism of Emotional Learning

    Directory of Open Access Journals (Sweden)

    Ali Sadeghieh

    2012-09-01

    Full Text Available In this paper, an experimental analysis of identification and an online intelligent adaptive position tracking control based on an emotional learning model of the human brain (BELBIC for an electrohydraulic servo (EHS system is presented. A mathematical model of the system is derived and the parameters of the model are identified. The BELBIC is designed based upon this dynamic model and utilized to control the real laboratorial EHS system. The experimental results are compared to those obtained from an optimal PID controller to prove that classic linear controllers fail to achieve good tracking of the desired output, especially when the hydraulic actuator operates at various frequencies and pressures. The results demonstrate an excellent improvement in control action, without any increase in control effort, for the proposed approach. Finally, it can be concluded from the experimental results that the BELBIC is able to respond quickly to any disturbance and variation in the system parameters, showing a high degree of adaptability and robustness due to its online learning ability.

  20. Application of Genetic Control with Adaptive Scaling Scheme to Signal Acquisition in Global Navigation Satellite System Receiver

    Directory of Open Access Journals (Sweden)

    Ho-Nien Shou

    2012-02-01

    Full Text Available This paper presents a genetic-based control scheme that not only utilizes evolutionary characteristics to find the signal acquisition parameters, but also employs an adaptive scheme to control the search space and avoid the genetic control converging to local optimal value so as to acquire the desired signal precisely and rapidly. Simulations and experiment results show that the proposed method can improve the precision of signal parameters and take less signal acquisition time than traditional serial search methods for global navigation satellite system (GNSS signals.

  1. Knowledge-based Adaptive Tracking Control of Electro-hydraulic Actuator Systems

    DEFF Research Database (Denmark)

    Hansen, Poul Erik

    1997-01-01

    The paper deal with intelligent motion control and electro-hydraulic actuator systems for multiaxis machynes and robots.The research results are from the IMCIA research Programme supported by the Danish Technical Research Council, STVF.......The paper deal with intelligent motion control and electro-hydraulic actuator systems for multiaxis machynes and robots.The research results are from the IMCIA research Programme supported by the Danish Technical Research Council, STVF....

  2. Model and Sensor Based Nonlinear Adaptive Flight Control with Online System Identification

    NARCIS (Netherlands)

    Sun, L.G.

    2014-01-01

    Consensus exists that many loss-of-control (LOC) in flight accidents caused by severe aircraft damage or system failure could be prevented if flight performance could be recovered using the valid and remaining control authorities. However, the safe maneuverability of a post-failure aircraft will ine

  3. A Novel Robust Adaptive Fuzzy Controller

    Institute of Scientific and Technical Information of China (English)

    LIU Xiao-hua; WANG Xiu-hong; FEN En-min

    2002-01-01

    For a class of continuous-time nonlinear system, a novel robust adaptive fuzzy controller is proposed by using of Lyapunov method. It is proven that the control algorithm is globally stable, the output tracking-error can convergence to a domain of zero under the assumptions. As a result, the system controlled has stronger robustness for disturbance and modeling error.

  4. In-Flight Suppression of an Unstable F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

    Science.gov (United States)

    VanZwieten, Tannen S.; Gilligan, Eric T.; Wall, John H.; Miller, Christopher J.; Hanson, Curtis E.; Orr, Jeb S.

    2015-01-01

    NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off-nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using post-flight frequency-domain reconstruction, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

  5. In-Flight Suppression of a Destabilized F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

    Science.gov (United States)

    Wall, John H.; VanZwieten, Tannen S.; Gilligan, Eric T.; Miller, Christopher J.; Hanson, Curtis E.; Orr, Jeb S.

    2015-01-01

    NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using frequency-domain reconstruction of flight data, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

  6. Analysis, adaptive control and synchronization of a novel 4-D hyperchaotic hyperjerk system and its SPICE implementation

    Directory of Open Access Journals (Sweden)

    Vaidyanathan Sundarapandian

    2015-03-01

    Full Text Available A hyperjerk system is a dynamical system, which is modelled by an nth order ordinary differential equation with n ⩾ 4 describing the time evolution of a single scalar variable. Equivalently, using a chain of integrators, a hyperjerk system can be modelled as a system of n first order ordinary differential equations with n ⩾ 4. In this research work, a 4-D novel hyperchaotic hyperjerk system has been proposed, and its qualitative properties have been detailed. The Lyapunov exponents of the novel hyperjerk system are obtained as L1 = 0.1448, L2 = 0.0328, L3 = 0 and L4 = −1.1294. The Kaplan-Yorke dimension of the novel hyperjerk system is obtained as DKY= 3.1573. Next, an adaptive backstepping controller is designed to stabilize the novel hyperjerk chaotic system with three unknown parameters. Moreover, an adaptive backstepping controller is designed to achieve global hyperchaos synchronization of the identical novel hyperjerk systems with three unknown parameters. Finally, an electronic circuit realization of the novel jerk chaotic system using SPICE is presented in detail to confirm the feasibility of the theoretical hyperjerk model.

  7. Chaotic satellite attitude control by adaptive approach

    Science.gov (United States)

    Wei, Wei; Wang, Jing; Zuo, Min; Liu, Zaiwen; Du, Junping

    2014-06-01

    In this article, chaos control of satellite attitude motion is considered. Adaptive control based on dynamic compensation is utilised to suppress the chaotic behaviour. Control approaches with three control inputs and with only one control input are proposed. Since the adaptive control employed is based on dynamic compensation, faithful model of the system is of no necessity. Sinusoidal disturbance and parameter uncertainties are considered to evaluate the robustness of the closed-loop system. Both of the approaches are confirmed by theoretical and numerical results.

  8. Adaptable Embedded Systems

    CERN Document Server

    Lisbôa, Carlos; Carro, Luigi

    2013-01-01

    As embedded systems become more complex, designers face a number of challenges at different levels: they need to boost performance, while keeping energy consumption as low as possible, they need to reuse existent software code, and at the same time they need to take advantage of the extra logic available in the chip, represented by multiple processors working together.  This book describes several strategies to achieve such different and interrelated goals, by the use of adaptability. Coverage includes reconfigurable systems, dynamic optimization techniques such as binary translation and trace reuse, new memory architectures including homogeneous and heterogeneous multiprocessor systems, communication issues and NOCs, fault tolerance against fabrication defects and soft errors, and finally, how one can combine several of these techniques together to achieve higher levels of performance and adaptability.  The discussion also includes how to employ specialized software to improve this new adaptive system, and...

  9. An Adaptive Coordinated Control for an Offshore Wind Farm Connected VSC Based Multi-Terminal DC Transmission System

    Science.gov (United States)

    Kumar, M. Ajay; Srikanth, N. V.

    2014-11-01

    The voltage source converter (VSC) based multiterminal high voltage direct current (MTDC) transmission system is an interesting technical option to integrate offshore wind farms with the onshore grid due to its unique performance characteristics and reduced power loss via extruded DC cables. In order to enhance the reliability and stability of the MTDC system, an adaptive neuro fuzzy inference system (ANFIS) based coordinated control design has been addressed in this paper. A four terminal VSC-MTDC system which consists of an offshore wind farm and oil platform is implemented in MATLAB/ SimPowerSystems software. The proposed model is tested under different fault scenarios along with the converter outage and simulation results show that the novel coordinated control design has great dynamic stabilities and also the VSC-MTDC system can supply AC voltage of good quality to offshore loads during the disturbances.

  10. Neural adaptive control of nonlinear multivariable systems with application to a class of inverted pendulums.

    Science.gov (United States)

    He, Shouling

    2002-10-01

    In this paper multilayer neural networks (MNNs) are used to control the balancing of a class of inverted pendulums. Unlike normal inverted pendulums, the pendulum discussed here has two degrees of rotational freedom and the base-point moves randomly in three-dimensional space. The goal is to apply control torques to keep the pendulum in a prescribed position in spite of the random movement at the base-point. Since the inclusion of the base-point motion leads to a non-autonomous dynamic system with time-varying parametric excitation, the design of the control system is a challenging task. A feedback control algorithm is proposed that utilizes a set of neural networks to compensate for the effect of the system's nonlinearities. The weight parameters of neural networks updated on-line, according to a learning algorithm that guarantees the Lyapunov stability of the control system. Furthermore, since the base-point movement is considered unmeasurable, a neural inverse model is employed to estimate it from only measured state variables. The estimate is then utilized within the main control algorithm to produce compensating control signals. The examination of the proposed control system, through simulations, demonstrates the promise of the methodology and exhibits positive aspects, which cannot be achieved by the previously developed techniques on the same problem. These aspects include fast, yet well-maintained damped responses with reasonable control torques and no requirement for knowledge of the model or the model parameters. The work presented here can benefit practical problems such as the study of stable locomotion of human upper body and bipedal robots. PMID:12424811

  11. Preliminary evaluation and comparison of atmospheric turbulence rejection performance for infinite and receding horizon control in adaptive optics systems

    Science.gov (United States)

    Konnik, Mikhail V.; De Dona, Jose

    2014-07-01

    Model-based optimal control such as Linear Quadratic Gaussian (LQG) control has been attracting considerable attention for adaptive optics systems. The ability of LQG to handle the complex dynamics of deformable mirrors and its relatively simple implementation makes LQG attractive for large adaptive optics systems. However, LQG has its own share of drawbacks, such as suboptimal handling of constraints on actuators movements and possible numerical problems in case of fast sampling rate discretization of the corresponding matrices. Unlike LQG, the Receding Horizon Control (RHC) technique provides control signals for a deformable mirror that are optimal within the prescribed constraints. This is achieved by reformulating the control problem as an online optimization problem that is solved at each sampling instance. In the unconstrained case, RHC produces the same control signals as LQG. However, when the control signals reach the constraints of actuator's allowable movement in a deformable mirror, RHC finds the control signals that are optimal within those constraints, rather than just clipping the unconstrained optimum as commonly done in LQG control. The article discusses the consequences of high-gain LQG control operation in the case when the constraints on the actuator's movement are reached. It is shown that clipping / saturating the control signals is not only suboptimal, but may be hazardous for the surface of a deformable mirror. The results of numerical simulations indicate that high-gain LQG control can lead to abrupt changes and spikes in the control signal when saturation occurs. The article further discusses a possible link between high-gain LQG and the waffle mode in the closed-loop operation of astronomical adaptive optics systems. Performance evaluation of Receding Horizon Control in terms of atmospheric disturbance rejection and a comparison with Linear Quadratic Gaussian control are performed. The results of the numerical simulations suggest that the

  12. Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults

    Science.gov (United States)

    Zhao, Lin; Jia, Yingmin

    2016-06-01

    In this paper, a distributed output feedback consensus tracking control scheme is proposed for second-order multi-agent systems in the presence of uncertain nonlinear dynamics, external disturbances, input constraints, and partial loss of control effectiveness. The proposed controllers incorporate reduced-order filters to account for the unmeasured states, and the neural networks technique is implemented to approximate the uncertain nonlinear dynamics in the synthesis of control algorithms. In order to compensate the partial loss of actuator effectiveness faults, fault-tolerant parts are included in controllers. Using the Lyapunov approach and graph theory, it is proved that the controllers guarantee a group of agents that simultaneously track a common time-varying state of leader, even when the state of leader is available only to a subset of the members of a group. Simulation results are provided to demonstrate the effectiveness of the proposed consensus tracking method.

  13. Sequential Adaptive RBF-Fuzzy Variable Structure Control Applied to Robotics Systems

    Directory of Open Access Journals (Sweden)

    Mohammed Salem

    2014-08-01

    Full Text Available In this paper, we present a combination of sequential trained radial basis function networks and fuzzy techniques to enhance the variable structure controllers dedicated to robotics systems. In this aim, four RBFs networks were used to estimate the model based part parameters (Inertia, Centrifugal and Coriolis, Gravity and Friction matrices of a variable structure controller so to respond to model variation and disturbances, a sequential online training algorithm based on Growing-Pruning "GAP" strategy and Kalman filter was implemented. To eliminate the chattering effect, the corrective control of the VS control was computed by a fuzzy controller. Simulations are carried out to control three degrees of freedom SCARA robot manipulator where the obtained results show good disturbance rejection and chattering elimination.

  14. Adaptive sliding mode back-stepping pitch angle control of a variable-displacement pump controlled pitch system for wind turbines.

    Science.gov (United States)

    Yin, Xiu-xing; Lin, Yong-gang; Li, Wei; Liu, Hong-wei; Gu, Ya-jing

    2015-09-01

    A variable-displacement pump controlled pitch system is proposed to mitigate generator power and flap-wise load fluctuations for wind turbines. The pitch system mainly consists of a variable-displacement hydraulic pump, a fixed-displacement hydraulic motor and a gear set. The hydraulic motor can be accurately regulated by controlling the pump displacement and fluid flows to change the pitch angle through the gear set. The detailed mathematical representation and dynamic characteristics of the proposed pitch system are thoroughly analyzed. An adaptive sliding mode pump displacement controller and a back-stepping stroke piston controller are designed for the proposed pitch system such that the resulting pitch angle tracks its desired value regardless of external disturbances and uncertainties. The effectiveness and control efficiency of the proposed pitch system and controllers have been verified by using realistic dataset of a 750 kW research wind turbine.

  15. Adaptive sliding mode back-stepping pitch angle control of a variable-displacement pump controlled pitch system for wind turbines.

    Science.gov (United States)

    Yin, Xiu-xing; Lin, Yong-gang; Li, Wei; Liu, Hong-wei; Gu, Ya-jing

    2015-09-01

    A variable-displacement pump controlled pitch system is proposed to mitigate generator power and flap-wise load fluctuations for wind turbines. The pitch system mainly consists of a variable-displacement hydraulic pump, a fixed-displacement hydraulic motor and a gear set. The hydraulic motor can be accurately regulated by controlling the pump displacement and fluid flows to change the pitch angle through the gear set. The detailed mathematical representation and dynamic characteristics of the proposed pitch system are thoroughly analyzed. An adaptive sliding mode pump displacement controller and a back-stepping stroke piston controller are designed for the proposed pitch system such that the resulting pitch angle tracks its desired value regardless of external disturbances and uncertainties. The effectiveness and control efficiency of the proposed pitch system and controllers have been verified by using realistic dataset of a 750 kW research wind turbine. PMID:26303957

  16. Adaptive Traffic Route Control in QoS Provisioning for Cognitive Radio Technology with Heterogeneous Wireless Systems

    Science.gov (United States)

    Yamamoto, Toshiaki; Ueda, Tetsuro; Obana, Sadao

    As one of the dynamic spectrum access technologies, “cognitive radio technology,” which aims to improve the spectrum efficiency, has been studied. In cognitive radio networks, each node recognizes radio conditions, and according to them, optimizes its wireless communication routes. Cognitive radio systems integrate the heterogeneous wireless systems not only by switching over them but also aggregating and utilizing them simultaneously. The adaptive control of switchover use and concurrent use of various wireless systems will offer a stable and flexible wireless communication. In this paper, we propose the adaptive traffic route control scheme that provides high quality of service (QoS) for cognitive radio technology, and examine the performance of the proposed scheme through the field trials and computer simulations. The results of field trials show that the adaptive route control according to the radio conditions improves the user IP throughput by more than 20% and reduce the one-way delay to less than 1/6 with the concurrent use of IEEE802.16 and IEEE802.11 wireless media. Moreover, the simulation results assuming hundreds of mobile terminals reveal that the number of users receiving the required QoS of voice over IP (VoIP) service and the total network throughput of FTP users increase by more than twice at the same time with the proposed algorithm. The proposed adaptive traffic route control scheme can enhance the performances of the cognitive radio technologies by providing the appropriate communication routes for various applications to satisfy their required QoS.

  17. Adaptive Neural Stabilizing Controller for a Class of Mismatched Uncertain Nonlinear Systems by State and Output Feedback.

    Science.gov (United States)

    Arefi, Mohammad Mehdi; Jahed-Motlagh, Mohammad Reza; Karimi, Hamid Reza

    2015-08-01

    In this paper, first, an adaptive neural network (NN) state-feedback controller for a class of nonlinear systems with mismatched uncertainties is proposed. By using a radial basis function NN (RBFNN), a bound of unknown nonlinear functions is approximated so that no information about the upper bound of mismatched uncertainties is required. Then, an observer-based adaptive controller based on RBFNN is designed to stabilize uncertain nonlinear systems with immeasurable states. The state-feedback and observer-based controllers are based on Lyapunov and strictly positive real-Lyapunov stability theory, respectively, and it is shown that the asymptotic convergence of the closed-loop system to zero is achieved while maintaining bounded states at the same time. The presented methods are more general than the previous approaches, handling systems with no restriction on the dimension of the system and the number of inputs. Simulation results confirm the effectiveness of the proposed methods in the stabilization of mismatched nonlinear systems. PMID:25265641

  18. Spatio-angular Minimum-variance Tomographic Controller for Multi-Object Adaptive Optics systems

    CERN Document Server

    Correia, Carlos M; Veran, Jean-Pierre; Andersen, David; Lardiere, Olivier; Bradley, Colin

    2015-01-01

    Multi-object astronomical adaptive-optics (MOAO) is now a mature wide-field observation mode to enlarge the adaptive-optics-corrected field in a few specific locations over tens of arc-minutes. The work-scope provided by open-loop tomography and pupil conjugation is amenable to a spatio-angular Linear-Quadratic Gaussian (SA-LQG) formulation aiming to provide enhanced correction across the field with improved performance over static reconstruction methods and less stringent computational complexity scaling laws. Starting from our previous work [1], we use stochastic time-progression models coupled to approximate sparse measurement operators to outline a suitable SA-LQG formulation capable of delivering near optimal correction. Under the spatio-angular framework the wave-fronts are never explicitly estimated in the volume,providing considerable computational savings on 10m-class telescopes and beyond. We find that for Raven, a 10m-class MOAO system with two science channels, the SA-LQG improves the limiting mag...

  19. Sensorless Adaptive Output Feedback Control of Wind Energy Systems with PMS Generators

    OpenAIRE

    El Magri, Abdelmounime; Giri, Fouad; Besancon, Gildas; Elfadili, Abderrahim; Dugard, Luc; Chaoui, Fatima Zara

    2013-01-01

    International audience; This paper addresses the problem of controlling wind energy conversion (WEC) systems involving permanent magnet synchronous generator (PMSG) fed by IGBT-based buck-to-buck rectifier-inverter. The prime control objective is to maximize wind energy extraction which cannot be achieved without letting the wind turbine rotor operate in variable-speed mode. Interestingly, the present study features the achievement of the above energetic goal without resorting to sensors of w...

  20. STUDYING COMPLEX ADAPTIVE SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    John H. Holland

    2006-01-01

    Complex adaptive systems (cas) - systems that involve many components that adapt or learn as they interact - are at the heart of important contemporary problems. The study of cas poses unique challenges: Some of our most powerful mathematical tools, particularly methods involving fixed points, attractors, and the like, are of limited help in understanding the development of cas. This paper suggests ways to modify research methods and tools, with an emphasis on the role of computer-based models, to increase our understanding of cas.

  1. Extended State Observer Based Adaptive Back-Stepping Sliding Mode Control of Electronic Throttle in Transportation Cyber-Physical Systems

    Directory of Open Access Journals (Sweden)

    Yongfu Li

    2015-01-01

    Full Text Available Considering the high accuracy requirement of information exchange via vehicle-to-vehicle (V2V communications, an extended state observer (ESO is designed to estimate the opening angle change of an electronic throttle (ET, wherein the emphasis is placed on the nonlinear uncertainties of stick-slip friction and spring in the system as well as the existence of external disturbance. In addition, a back-stepping sliding mode controller incorporating an adaptive control law is presented, and the stability and robustness of the system are analyzed using Lyapunov technique. Finally, numerical experiments are conducted using simulation. The results show that, compared with back-stepping control (BSC, the proposed controller achieves superior performance in terms of the steady-state error and rising time.

  2. Neuro-fuzzy controller of low head hydropower plants using adaptive-network based fuzzy inference system

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M.B. [Inst. Nikola Tesla, Belgrade (Yugoslavia). Dept. of Power Systems; Calovic, M.S. [Univ. of Belgrade (Yugoslavia). Dept. of Electrical Engineering; Vesovic, B.V. [Inst. Mihajlo Pupin, Belgrade (Yugoslavia). Dept. of Automatic Control; Sobajic, D.J. [Electric Power Research Inst., Palo Alto, CA (United States)

    1997-12-01

    This paper presents an attempt of nonlinear, multivariable control of low-head hydropower plants, by using adaptive-network based fuzzy inference system (ANFIS). The new design technique enhances fuzzy controllers with self-learning capability for achieving prescribed control objectives in a near optimal manner. The controller has flexibility for accepting more sensory information, with the main goal to improve the generator unit transients, by adjusting the exciter input, the wicket gate and runner blade positions. The developed ANFIS controller whose control signals are adjusted by using incomplete on-line measurements, can offer better damping effects to generator oscillations over a wide range of operating conditions, than conventional controllers. Digital simulations of hydropower plant equipped with low-head Kaplan turbine are performed and the comparisons of conventional excitation-governor control, state-feedback optimal control and ANFIS based output feedback control are presented. To demonstrate the effectiveness of the proposed control scheme and the robustness of the acquired neuro-fuzzy controller, the controller has been implemented on a complex high-order non-linear hydrogenerator model.

  3. Multiple models adaptive feedforward decoupling controller

    Institute of Scientific and Technical Information of China (English)

    Wang Xin; Li Shaoyuan; Wang Zhongjie

    2005-01-01

    When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one free-running adaptive model and one re-initialized adaptive model. The fixed models are used to provide initial control to the process. The re-initialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The free-running adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steady-state error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.

  4. Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

    Science.gov (United States)

    Fan, Quan-Yong; Yang, Guang-Hong

    2016-01-01

    This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method. PMID:26357411

  5. Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural Networks

    Directory of Open Access Journals (Sweden)

    Elaheh Saeedi

    2014-07-01

    Full Text Available In this paper, a decentralized adaptive controller with using wavelet neural network is used for a class of large-scale nonlinear systems with time- delay unknown nonlinear non- affine subsystems. The entered interruptions in subsystems are considered nonlinear with time delay, this is closer the reality, compared with the case in which the delay is not considered for interruptions. In this paper, the output weights of wavelet neural network and the other parameters of wavelet are adjusted online. The stability of close loop system is guaranteed with using the Lyapanov- Krasovskii method. Moreover the stability of close loop systems, guaranteed tracking error is converging to neighborhood zero and also all of the signals in the close loop system are bounded. Finally, the proposed method, simulated and applied for the control of two inverted pendulums that connected by a spring and the computer results, show that the efficiency of suggested method in this paper.

  6. Cooperative fuzzy adaptive output feedback control for synchronisation of nonlinear multi-agent systems under directed graphs

    Science.gov (United States)

    Wang, W.; Wang, D.; Peng, Z. H.

    2015-12-01

    This paper considers the leader-following synchronisation problem of nonlinear multi-agent systems with unmeasurable states and a dynamic leader whose input is not available to any follower. Each follower is governed by a nonlinear system with unknown dynamics. Two distributed fuzzy adaptive protocols, based on local and neighbourhood observers, respectively, are proposed to guarantee that the states of all followers synchronise to that of the leader, under the condition that the communication graph among the followers contains a directed spanning tree. Based on Lyapunov stability theory, the synchronisation errors are guaranteed to be cooperatively uniformly ultimately bounded. Two examples are provided to show the effectiveness of the proposed controllers.

  7. Complex adaptive systems ecology

    DEFF Research Database (Denmark)

    Sommerlund, Julie

    2003-01-01

    In the following, I will analyze two articles called Complex Adaptive Systems EcologyI & II (Molin & Molin, 1997 & 2000). The CASE-articles are some of the more quirkyarticles that have come out of the Molecular Microbial Ecology Group - a groupwhere I am currently making observational studies...

  8. Highly Flexible Multimode Digital Signal Processing Systems Using Adaptable Components and Controllers

    Directory of Open Access Journals (Sweden)

    Kumar Vinu Vijay

    2006-01-01

    Full Text Available Multimode systems have emerged as an area- and power-efficient platform for implementing multiple timewise mutually exclusive digital signal processing (DSP applications in a single hardware space. This paper presents a design methodology for integrating flexible components and controllers into primarily fixed logic multimode DSP systems, thereby increasing their overall efficiency and implementation capabilities. The components are built using a technique called small-scale reconfigurability (SSR that provides the necessary flexibility for both intermode and intramode reconfigurabilities, without the penalties associated with general-purpose reconfigurable logic. Using this methodology, area and power consumption are reduced beyond what is provided by current multimode systems, without sacrificing performance. The results show an average of 7% reduction in datapath component area, 26% reduction in register area, 36% reduction in interconnect MUX cost, and 68% reduction in the number of controller signals, with an average 38% increase in component utilization for a set of benchmark 32-bit DSP applications.

  9. Modelling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.System conceptsIn Chapters 1 and 2 an overview of the problem formulation is presented. It is suggested that there

  10. Adaptive Sliding Mode Control for Hydraulic Drives

    DEFF Research Database (Denmark)

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

    2013-01-01

    This paper presents a new adaptive sliding mode controller generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD’s). The proposed control scheme requires limited knowledge on system parameters, and employs only piston- and valve spool position feedback...

  11. Simple adaptive tracking control for mobile robots

    Science.gov (United States)

    Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton

    2014-12-01

    The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.

  12. 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...

  13. Adaptive Control Algorithms, Analysis and Applications

    OpenAIRE

    Landau, Ioan; Lozano, Rogelio; M'Saad, Mohammed; Karimi, Alireza

    2011-01-01

    Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the ...

  14. Adaptive Cruise Control and Driver Modeling

    OpenAIRE

    Bengtsson, Johan

    2001-01-01

    Many vehicle manufacturers have lately introduced advance driver support in some of their automobiles. One of those new features is Adaptive Cruise Control DACCE, which extends the conventional cruise control system to control of relative speed and distance to other vehicles. In order to design an ACC controller it is suitable to have a model of driver behavior. The approach in the thesis is to use system identification methodology to obtain dynamic models of driver behavior useful for ACC ap...

  15. An Adaptive Sliding Mode Tracking Controller Using BP Neural Networks for a Class of Large-scale Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A new type controller, BP neural-networks-based sliding mode controller is developed for a class of large-scale nonlinear systems with unknown bounds of high-order interconnections in this paper. It is shown that decentralized BP neural networks are used to adaptively learn the uncertainty bounds of interconnected subsystems in the Lyapunov sense, and the outputs of the decentralized BP neural networks are then used as the parameters of the sliding mode controller to compensate for the effects of subsystems uncertainties. Using this scheme, not only strong robustness with respect to uncertainty dynamics and nonlinearities can be obtained, but also the output tracking error between the actual output of each subsystem and the corresponding desired reference output can asymptotically converge to zero. A simulation example is presented to support the validity of the proposed BP neural-networks-based sliding mode controller.

  16. Adaptive Fuzzy Attitude Control of Flexible Satellite

    Institute of Scientific and Technical Information of China (English)

    GUAN Ping; LIU Xiang-dong; CHEN Jia-bin

    2005-01-01

    The adaptive fuzzy control is applied in the attitude stabilization of flexible satellite. The detailed design procedure of the adaptive fuzzy control system is presented. Two T-S models are used as both controller and identifier. The parameters of the controller could be modified according to the information of the identifier. Simulation results show that the method can effectively cope with the uncertainty of flexible satellite by on-line learning and thus posses the good robustness. With the proposed method, the precise attitude control is accomplished.

  17. Self-Adaptive Strategy Based on Fuzzy Control Systems for Improving Performance in Wireless Sensors Networks

    Directory of Open Access Journals (Sweden)

    Vicente Hernández Díaz

    2015-09-01

    Full Text Available The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT and Cyber-Physical Systems (CPS are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container, and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

  18. Self-Adaptive Strategy Based on Fuzzy Control Systems for Improving Performance in Wireless Sensors Networks.

    Science.gov (United States)

    Hernández Díaz, Vicente; Martínez, José-Fernán; Lucas Martínez, Néstor; del Toro, Raúl M

    2015-09-18

    The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

  19. Self-Adaptive Strategy Based on Fuzzy Control Systems for Improving Performance in Wireless Sensors Networks.

    Science.gov (United States)

    Hernández Díaz, Vicente; Martínez, José-Fernán; Lucas Martínez, Néstor; del Toro, Raúl M

    2015-01-01

    The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries. PMID:26393612

  20. L1 adaptive control with sliding-mode based adaptive law

    Institute of Scientific and Technical Information of China (English)

    Jie LUO; Chengyu CAO

    2015-01-01

    This paper presents an adaptive control scheme with an integration of sliding mode control into the L1 adaptive control architecture, which provides good tracking performance as well as robustness against matched uncertainties. Sliding mode control is used as an adaptive law in the L1 adaptive control architecture, which is considered as a virtual control of error dynamics between estimated states and real states. Low-pass filtering mechanism in the control law design prevents a discontinuous signal in the adaptive law from appearing in actual control signal while maintaining control accuracy. By using sliding mode control as a virtual control of error dynamics and introducing the low-pass filtered control signal, the chattering effect is eliminated. The performance bounds between the close-loop adaptive system and the closed-loop reference system are characterized in this paper. Numerical simulation is provided to demonstrate the performance of the presented adaptive control scheme.

  1. Design, dynamics and control of an Adaptive Singularity-Free Control Moment Gyroscope actuator for microspacecraft Attitude Determination and Control System

    Science.gov (United States)

    Viswanathan, Sasi Prabhakaran

    Design, dynamics, control and implementation of a novel spacecraft attitude control actuator called the "Adaptive Singularity-free Control Moment Gyroscope" (ASCMG) is presented in this dissertation. In order to construct a comprehensive attitude dynamics model of a spacecraft with internal actuators, the dynamics of a spacecraft with an ASCMG, is obtained in the framework of geometric mechanics using the principles of variational mechanics. The resulting dynamics is general and complete model, as it relaxes the simplifying assumptions made in prior literature on Control Moment Gyroscopes (CMGs) and it also addresses the adaptive parameters in the dynamics formulation. The simplifying assumptions include perfect axisymmetry of the rotor and gimbal structures, perfect alignment of the centers of mass of the gimbal and the rotor etc. These set of simplifying assumptions imposed on the design and dynamics of CMGs leads to adverse effects on their performance and results in high manufacturing cost. The dynamics so obtained shows the complex nonlinear coupling between the internal degrees of freedom associated with an ASCMG and the spacecraft bus's attitude motion. By default, the general ASCMG cluster can function as a Variable Speed Control Moment Gyroscope, and reduced to function in CMG mode by spinning the rotor at constant speed, and it is shown that even when operated in CMG mode, the cluster can be free from kinematic singularities. This dynamics model is then extended to include the effects of multiple ASCMGs placed in the spacecraft bus, and sufficient conditions for non-singular ASCMG cluster configurations are obtained to operate the cluster both in VSCMG and CMG modes. The general dynamics model of the ASCMG is then reduced to that of conventional VSCMGs and CMGs by imposing the standard set of simplifying assumptions used in prior literature. The adverse effects of the simplifying assumptions that lead to the complexities in conventional CMG design, and

  2. Adaptive Neuro-Fuzzy Inference Systems as a Strategy for Predicting and Controling the Energy Produced from Renewable Sources

    Directory of Open Access Journals (Sweden)

    Otilia Elena Dragomir

    2015-11-01

    Full Text Available The challenge for our paper consists in controlling the performance of the future state of a microgrid with energy produced from renewable energy sources. The added value of this proposal consists in identifying the most used criteria, related to each modeling step, able to lead us to an optimal neural network forecasting tool. In order to underline the effects of users’ decision making on the forecasting performance, in the second part of the article, two Adaptive Neuro-Fuzzy Inference System (ANFIS models are tested and evaluated. Several scenarios are built by changing: the prediction time horizon (Scenario 1 and the shape of membership functions (Scenario 2.

  3. Adaptive control based on fast online algebraic identification and GPI control for magnetic levitation systems with time-varying input gain

    Science.gov (United States)

    Morales, R.; Sira-Ramírez, H.; Feliu, V.

    2014-08-01

    This paper considers the position tracking problem of a voltage-controlled magnetic levitation system (MLS) in the presence of modelling errors caused by uncertainties in the system's physical parameters. An adaptive control based on fast online algebraic parameter estimation and generalised proportional integral (GPI) output feedback control is considered as a control scheme candidate. The GPI controller guarantees an asymptotically exponentially stable behaviour of the controlled ball position and the possibilities of carrying out rest-to-rest trajectory tracking tasks. The nature of the control input gain in an MLS is that of a state-dependent time-varying gain, reflecting the nonlinear character of the magnetic force with regard to the distance and the properties of the metallic ball. The system gain has therefore been locally approximated using a periodically updated time polynomial function (of second degree), where the coefficients of the polynomial are estimated during a very short period of time. This estimation is achieved using the recently introduced algebraic online parameter estimation approach. The stability of the closed-loop system is demonstrated under the assumption that no external factors cause changes in the parameter during the time interval in which the stability is analysed. Finally, experimental results are presented for the controlled MLS demonstrating the excellent stabilisation and position tracking performance of the control system designed in the presence of significant nonlinearities and uncertainties of the underlying system.

  4. Robust adaptive neural network control with supervisory controller

    Institute of Scientific and Technical Information of China (English)

    张天平; 梅建东

    2004-01-01

    The problem of direct adaptive neural network control for a class of uncertain nonlinear systems with unknown constant control gain is studied in this paper. Based on the supervisory control strategy and the approximation capability of multilayer neural networks (MNNs), a novel design scheme of direct adaptive neural network controller is proposed.The adaptive law of the adjustable parameter vector and the matrix of weights in the neural networks and the gain of sliding mode control term to adaptively compensate for the residual and the approximation error of MNNs is determined by using a Lyapunov method. The approach does not require the optimal approximation error to be square-integrable or the supremum of the optimal approximation error to be known. By theoretical analysis, the closed-loop control system is proven to be globally stable in the sense that all signals involved are bounded, with tracking error converging to zero.Simulation results demonstrate the effectiveness of the approach.

  5. Adaptive Neuro-Fuzzy Inference System for Classification of Background EEG Signals from ESES Patients and Controls

    Directory of Open Access Journals (Sweden)

    Zhixian Yang

    2014-01-01

    Full Text Available Background electroencephalography (EEG, recorded with scalp electrodes, in children with electrical status epilepticus during slow-wave sleep (ESES syndrome and control subjects has been analyzed. We considered 10 ESES patients, all right-handed and aged 3–9 years. The 10 control individuals had the same characteristics of the ESES ones but presented a normal EEG. Recordings were undertaken in the awake and relaxed states with their eyes open. The complexity of background EEG was evaluated using the permutation entropy (PE and sample entropy (SampEn in combination with the ANOVA test. It can be seen that the entropy measures of EEG are significantly different between the ESES patients and normal control subjects. Then, a classification framework based on entropy measures and adaptive neuro-fuzzy inference system (ANFIS classifier is proposed to distinguish ESES and normal EEG signals. The results are promising and a classification accuracy of about 89% is achieved.

  6. Adaptive neuro-fuzzy inference system for classification of background EEG signals from ESES patients and controls.

    Science.gov (United States)

    Yang, Zhixian; Wang, Yinghua; Ouyang, Gaoxiang

    2014-01-01

    Background electroencephalography (EEG), recorded with scalp electrodes, in children with electrical status epilepticus during slow-wave sleep (ESES) syndrome and control subjects has been analyzed. We considered 10 ESES patients, all right-handed and aged 3-9 years. The 10 control individuals had the same characteristics of the ESES ones but presented a normal EEG. Recordings were undertaken in the awake and relaxed states with their eyes open. The complexity of background EEG was evaluated using the permutation entropy (PE) and sample entropy (SampEn) in combination with the ANOVA test. It can be seen that the entropy measures of EEG are significantly different between the ESES patients and normal control subjects. Then, a classification framework based on entropy measures and adaptive neuro-fuzzy inference system (ANFIS) classifier is proposed to distinguish ESES and normal EEG signals. The results are promising and a classification accuracy of about 89% is achieved. PMID:24790547

  7. Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

    Science.gov (United States)

    Marzbanrad, Javad; Tahbaz-zadeh Moghaddam, Iman

    2016-09-01

    The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.

  8. Adaptive change in corporate control practices.

    Science.gov (United States)

    Alexander, J A

    1991-03-01

    Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes.

  9. Adaptive change in corporate control practices.

    Science.gov (United States)

    Alexander, J A

    1991-03-01

    Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes. PMID:10110017

  10. Adaptive backstepping control for levitation system with load uncertainties and external disturbances

    Institute of Scientific and Technical Information of China (English)

    李金辉; 李杰; 余佩; 王连春

    2014-01-01

    To explore the precise dynamic response of the levitation system with active controller, a maglev guide way-electromagnet-air spring-cabin coupled model is derived firstly. Based on the mathematical model, it shows that the inherent nonlinearity, inner coupling, misalignments between the sensors and actuators, load uncertainties and external disturbances are the main issues that should be solved in engineering. Under the assumptions that the loads and external disturbance are measurable, the backstepping module controller developed in this work can tackle the above problems effectively. In reality, the load is uncertain due to the additions of luggage and passengers, which will degrade the dynamic performance. A load estimation algorithm is introduced to track the actual load asymptotically and eliminate its influence by tuning the parameters of controller online. Furthermore, considering the external disturbances generated by crosswind, pulling motor and air springs, the extended state observer is employed to estimate and suppress the external disturbance. Finally, results of numerical simulations illustrating closed-loop performance are provided.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-15

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

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

    Directory of Open Access Journals (Sweden)

    Fengxia Xu

    2014-01-01

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

  13. Self Adaptive Air Turbine for Wave Energy Conversion Using Shutter Valve and OWC Heoght Control System

    Energy Technology Data Exchange (ETDEWEB)

    Di Bella, Francis A

    2014-09-29

    An oscillating water column (OWC) is one of the most technically viable options for converting wave energy into useful electric power. The OWC system uses the wave energy to “push or pull” air through a high-speed turbine, as illustrated in Figure 1. The turbine is typically a bi-directional turbine, such as a Wells turbine or an advanced Dennis-Auld turbine, as developed by Oceanlinx Ltd. (Oceanlinx), a major developer of OWC systems and a major collaborator with Concepts NREC (CN) in Phase II of this STTR effort. Prior to awarding the STTR to CN, work was underway by CN and Oceanlinx to produce a mechanical linkage mechanism that can be cost-effectively manufactured, and can articulate turbine blades to improve wave energy capture. The articulation is controlled by monitoring the chamber pressure. Funding has been made available from the U.S. Department of Energy (DOE) to CN (DOE DE-FG-08GO18171) to co-share the development of a blade articulation mechanism for the purpose of increasing energy recovery. However, articulating the blades is only one of the many effective design improvements that can be made to the composite subsystems that constitute the turbine generator system.

  14. Reference model decomposition in direct adaptive control

    OpenAIRE

    Butler, H.; Honderd, G.; Amerongen, van, W.E.

    1991-01-01

    This paper introduces the method of reference model decomposition as a way to improve the robustness of model reference adaptive control systems (MRACs) with respect to unmodelled dynamics with a known structure. Such unmodelled dynamics occur when some of the nominal plant dynamics are purposely neglected in the controller design with the aim of keeping the controller order low. One of the effects of such undermodelling of the controller is a violation of the perfect model-matching condition...

  15. Adaptive, dynamic, and resilient systems

    CERN Document Server

    Suri, Niranjan

    2015-01-01

    As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r

  16. Transient stability enhancement of wind farms connected to a multi-machine power system by using an adaptive ANN-controlled SMES

    International Nuclear Information System (INIS)

    Highlights: • We present an ANN-controlled SMES in this paper. • The objective is to enhance transient stability of WF connected to power system. • The control strategy depends on a PWM VSC and DC–DC converter. • The effectiveness of proposed controller is compared with PI controller. • The validity of the proposed system is verified by simulation results. - Abstract: This paper presents a novel adaptive artificial neural network (ANN)-controlled superconducting magnetic energy storage (SMES) system to enhance the transient stability of wind farms connected to a multi-machine power system during network disturbances. The control strategy of SMES depends mainly on a sinusoidal pulse width modulation (PWM) voltage source converter (VSC) and an adaptive ANN-controlled DC–DC converter using insulated gate bipolar transistors (IGBTs). The effectiveness of the proposed adaptive ANN-controlled SMES is then compared with that of proportional-integral (PI)-controlled SMES optimized by response surface methodology and genetic algorithm (RSM–GA) considering both of symmetrical and unsymmetrical faults. For realistic responses, real wind speed data and two-mass drive train model of wind turbine generator system is considered in the analyses. The validity of the proposed system is verified by the simulation results which are performed using the laboratory standard dynamic power system simulator PSCAD/EMTDC. Notably, the proposed adaptive ANN-controlled SMES enhances the transient stability of wind farms connected to a multi-machine power system

  17. An asymptotically optimal nonparametric adaptive controller

    Institute of Scientific and Technical Information of China (English)

    郭雷; 谢亮亮

    2000-01-01

    For discrete-time nonlinear stochastic systems with unknown nonparametric structure, a kernel estimation-based nonparametric adaptive controller is constructed based on truncated certainty equivalence principle. Global stability and asymptotic optimality of the closed-loop systems are established without resorting to any external excitations.

  18. Adaptive passive equivalence of uncertain Lü system

    Institute of Scientific and Technical Information of China (English)

    Qi Dong-Lian

    2006-01-01

    An adaptive passive strategy for controlling uncertain Lü system is proposed. Since the uncertain Lü system is minimum phase and the uncertain parameters are from a bounded compact set, the essential conditions are studied by which uncertain Lü system could be equivalent to a passive system, and the adaptive control law is given. Using passive theory, the uncertain Lü system could be globally asymptotically stabilized at different equilibria by the smooth state feedback.

  19. Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay.

    Science.gov (United States)

    Hwang, Chih-Lyang; Jan, Chau

    2016-02-01

    At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e -modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.

  20. An adaptive method with weight matrix as a function of the state to design the rotatory flexible system control law

    Science.gov (United States)

    Souza, Luiz C. G.; Bigot, P.

    2016-10-01

    One of the most well-known techniques of optimal control is the theory of Linear Quadratic Regulator (LQR). This method was originally applied only to linear systems but has been generalized for non-linear systems: the State Dependent Riccati Equation (SDRE) technique. One of the advantages of SDRE is that the weight matrix selection is the same as in LQR. The difference is that weights are not necessarily constant: they can be state dependent. Then, it gives an additional flexibility to design the control law. Many are applications of SDRE for simulation or real time control but generally SDRE weights are chosen constant so no advantage of this flexibility is taken. This work serves to show through simulation that state dependent weights matrix can improve SDRE control performance. The system is a non-linear flexible rotatory beam. In a brief first part SDRE theory will be explained and the non-linear model detailed. Then, influence of SDRE weight matrix associated with the state Q will be analyzed to get some insight in order to assume a state dependent law. Finally, these laws are tested and compared to constant weight matrix Q. Based on simulation results; one concludes showing the benefits of using an adaptive weight Q rather than a constant one.

  1. The real-time control system for the CANARY multi-object adaptive optics on-sky demonstrator

    Science.gov (United States)

    Dipper, N. A.; Basden, A.; Looker, N. E.; Gendron, E.; Geng, D.; Gratadour, D.; Hubert, Z.; Vidal, F.; Myers, R. M.; Rousset, G.; Sevin, A.; Younger, E. J.

    2010-07-01

    CANARY is a Multi-Object Adaptive Optics (MOAO) system designed to demonstrate the AO aspects of proposed EELT instruments such as the multi-object spectrograph EAGLE. The first phase of Canary will be executed on the 4.2m William Herschel Telescope in 2010. We describe here the AO Real-time Control System (RTCS) for Canary. This is based on a distributed architecture of components interconnected by a fast serial fabric (sFPDP). The hardware used is a hybrid of FPGA and CPU technology. The middleware used for system data telemetry and control is based on CORBA and the publish/subscribe pattern. The system is designed to be easily modified and extended for the later, higher order, phases of CANARY. In order to provide the increase in computational power required in higher order systems, the current CPU technology can be readily replaced by acceleration hardware based on FPGA or GPU technologies. The Canary RTCS thus provides a test-bed for these new technologies that will be required for E-ELT instruments. These design concepts can be developed to provide an RTCS for E-ELT instruments and are in line with those under consideration by ESO for the E-ELT AO systems to which instruments such as EAGLE will be required to interface.

  2. Adaptive Piezoelectric Absorber for Active Vibration Control

    Directory of Open Access Journals (Sweden)

    Sven Herold

    2016-02-01

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

  3. Indirect Adaptive Fuzzy Output Feedback Control with Supervisory Controller for Uncertain Nonlinear Systems%非线性系统的间接自适应模糊输出反馈监督控制

    Institute of Scientific and Technical Information of China (English)

    佟绍成; 柴天佑

    2005-01-01

    In this paper, an indirect adaptive fuzzy output feedback controller with supervisory mode for a class of unknown nonlinear systems is developed. The proposed approach does not need the availability of the state variables, moreover, a supervisory controller is appended to the adaptive fuzzy controller to force the state to be within the constraint set. Therefore, if the adaptive fuzzy controller cannot maintain the stability, the supervisory controller starts to work to guarantee stability. On the other hand, if the adaptive fuzzy controller works well, the supervisory controller will be de-activated. The overall adaptive fuzzy control scheme guarantees the stability of the whole closed-loop systems. The simulation results confirm the effectiveness of the proposed method.

  4. Hybrid adaptive control of a dragonfly model

    Science.gov (United States)

    Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro

    2012-02-01

    Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.

  5. Thermal room modelling adapted to the test of HVAC control systems; Modele de zone adapte aux essais de regulateurs de systemes de chauffage et de climatisation

    Energy Technology Data Exchange (ETDEWEB)

    Riederer, P.

    2002-01-15

    Room models, currently used for controller tests, assume the room air to be perfectly mixed. A new room model is developed, assuming non-homogeneous room conditions and distinguishing between different sensor positions. From measurement in real test rooms and detailed CFD simulations, a list of convective phenomena is obtained that has to be considered in the development of a model for a room equipped with different HVAC systems. The zonal modelling approach that divides the room air into several sub-volumes is chosen, since it is able to represent the important convective phenomena imposed on the HVAC system. The convective room model is divided into two parts: a zonal model, representing the air at the occupant zone and a second model, providing the conditions at typical sensor positions. Using this approach, the comfort conditions at the occupant zone can be evaluated as well as the impact of different sensor positions. The model is validated for a test room equipped with different HVAC systems. Sensitivity analysis is carried out on the main parameters of the model. Performance assessment and energy consumption are then compared for different sensor positions in a room equipped with different HVAC systems. The results are also compared with those obtained when a well-mixed model is used. A main conclusion of these tests is, that the differences obtained, when changing the position of the controller's sensor, is a function of the HVAC system and controller type. The differences are generally small in terms of thermal comfort but significant in terms of overall energy consumption. For different HVAC systems the cases are listed, in which the use of a simplified model is not recommended. (author)

  6. ADAPTIVE REGULATION OF HIGH ORDER NONHOLONOMIC SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The problem of adaptive regulation of a class of high-order parametric nonholonomic systems in chained-form was discussed. Using adding a power integrator technique and state scaling with discontinuous projection technique, a discontinuous adaptive dynamic controller was constructed. The controller guarantees the estimated value of unknown parameter is in the prescribed extent.

  7. Adaptive Data Processing Technique for Lidar-Assisted Control to Bridge the Gap between Lidar Systems and Wind Turbines: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Schlipf, David; Raach, Steffen; Haizmann, Florian; Cheng, Po Wen; Fleming, Paul; Scholbrock, Andrew, Krishnamurthy, Raghu; Boquet, Mathieu

    2015-12-14

    This paper presents first steps toward an adaptive lidar data processing technique crucial for lidar-assisted control in wind turbines. The prediction time and the quality of the wind preview from lidar measurements depend on several factors and are not constant. If the data processing is not continually adjusted, the benefit of lidar-assisted control cannot be fully exploited, or can even result in harmful control action. An online analysis of the lidar and turbine data are necessary to continually reassess the prediction time and lidar data quality. In this work, a structured process to develop an analysis tool for the prediction time and a new hardware setup for lidar-assisted control are presented. The tool consists of an online estimation of the rotor effective wind speed from lidar and turbine data and the implementation of an online cross correlation to determine the time shift between both signals. Further, initial results from an ongoing campaign in which this system was employed for providing lidar preview for feed-forward pitch control are presented.

  8. Robust Adaptive Control In Hilbert Space

    Science.gov (United States)

    Wen, John Ting-Yung; Balas, Mark J.

    1990-01-01

    Paper discusses generalization of scheme for adaptive control of finite-dimensional system to infinite-dimensional Hilbert space. Approach involves generalization of command-generator tracker (CGT) theory. Does not require reference model to be same order as that of plant, and knowledge of order of plant not needed. Suitable for application to high-order systems, main emphasis on adjustment of low-order feedback-gain matrix. Analysis particularly relevant to control of large, flexible structures.

  9. Adaptive neural network control for coordinated motion of a dual-arm space robot system with uncertain parameters

    Institute of Scientific and Technical Information of China (English)

    GUO Yi-shen; CHEN Li

    2008-01-01

    Control of coordinated motion between the base attitude and the arm joints of a free-floating dual-arm space robot with uncertain parameters is discussed.By combining the relation of system linear momentum conversation with the Lagrangian approach,the dynamic equation of a robot is established.Based on the above results,the free-floating dual-arm space robot system is modeled with RBF neural networks,the GL matrix and its product operator.With all uncertain inertial system parameters,an adaptive RBF neural network control scheme is developed for coordinated motion between the base attitude and the arm joints.The proposed scheme does not need linear parameterization of the dynamic equation of the system and any accurate prior-knowledge of the actual inertial parameters.Also it does not need to train the neural network offline so that it would present real-time and online applications.A planar free-floating dual-arm space robot is simulated to show feasibility of the proposed scheme.

  10. 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.

  11. An adaptive neuro fuzzy inference system controlled space cector pulse width modulation based HVDC light transmission system under AC fault conditions

    Science.gov (United States)

    Ajay Kumar, M.; Srikanth, N.

    2014-03-01

    In HVDC Light transmission systems, converter control is one of the major fields of present day research works. In this paper, fuzzy logic controller is utilized for controlling both the converters of the space vector pulse width modulation (SVPWM) based HVDC Light transmission systems. Due to its complexity in the rule base formation, an intelligent controller known as adaptive neuro fuzzy inference system (ANFIS) controller is also introduced in this paper. The proposed ANFIS controller changes the PI gains automatically for different operating conditions. A hybrid learning method which combines and exploits the best features of both the back propagation algorithm and least square estimation method is used to train the 5-layer ANFIS controller. The performance of the proposed ANFIS controller is compared and validated with the fuzzy logic controller and also with the fixed gain conventional PI controller. The simulations are carried out in the MATLAB/SIMULINK environment. The results reveal that the proposed ANFIS controller is reducing power fluctuations at both the converters. It also improves the dynamic performance of the test power system effectively when tested for various ac fault conditions.

  12. 一类带有未知控制方向的非线性系统的适应镇定问题%A Control of Uncertain Nonlinear Systems with Unknown Control Direction Via Adaptive Backstepping

    Institute of Scientific and Technical Information of China (English)

    郑兆顺

    2007-01-01

    The adaptive stabilization problem of nonlinear systems are studied. For a class of uncertain nonlinear systems with unknown control direction, we proposed a robust adaptive backstepping scheme with σ-modification by introducing Nussbaum function and Backstepping methods, and proved that all the signals of the closed-loop systems are bounded.

  13. Self-adaptive strategy based on fuzzy control systems for improving performance in wireless sensors networks

    OpenAIRE

    Vicente Hernández Díaz; José-Fernán Martínez; Néstor Lucas Martínez; del Toro, Raúl M.

    2015-01-01

    The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in differe...

  14. Improvement of Adaptive Cruise Control Performance

    Directory of Open Access Journals (Sweden)

    Nakagami Takashi

    2010-01-01

    Full Text Available This paper describes the Adaptive Cruise Control system (ACC, a system which reduces the driving burden on the driver. The ACC system primarily supports four driving modes on the road and controls the acceleration and deceleration of the vehicle in order to maintain a set speed or to avoid a crash. This paper proposes more accurate methods of detecting the preceding vehicle by radar while cornering, with consideration for the vehicle sideslip angle, and also of controlling the distance between vehicles. By making full use of the proposed identification logic for preceding vehicles and path estimation logic, an improvement in driving stability was achieved.

  15. ADAPTIVE CONTROL METHOD IN GUN-CONTROL SYSTEMS%火炮稳定器的自适应控制方法研究

    Institute of Scientific and Technical Information of China (English)

    王新; 李霆; 潘宏侠

    2001-01-01

    本文提出设计火炮稳定系统控制器的一种新方法,应用自适应控制的基本原理,采用最小方差控制与极点配置组合的控制算法。该算法简单、计算量小、易于实现计算机实时控制,有利于提高行进间火炮武器系统的射击精度。仿真试验表明,这种方法的控制效果十分明显。%A new method is put forward for the design of controllers in gun-control systems. Based on the adaptive control principle, a new algorithm is proposed adopting the least variance control and the pole assignment method. It is simple and easily realizable in gun-control systems, and it is useful in improving the shoot precision of a marching gun. The results of computer simulation demonstrate that the method is efficient to the control system.

  16. Droop Control with Improved Disturbance Adaption for PV System with Two Power Conversion Stages

    DEFF Research Database (Denmark)

    Liu, Hongpeng; Loh, Poh Chiang; Wang, Xiongfei;

    2016-01-01

    Droop control has commonly been used with distributed generators for relating their terminal parameters with power generation. The generators have also been assumed to have enough capacities for supplying the required power. This is however not always true, especially with renewable sources with ...

  17. Stochastic optimal control and estimation methods adapted to the noise characteristics of the sensorimotor system.

    Science.gov (United States)

    Todorov, Emanuel

    2005-05-01

    Optimality principles of biological movement are conceptually appealing and straightforward to formulate. Testing them empirically, however, requires the solution to stochastic optimal control and estimation problems for reasonably realistic models of the motor task and the sensorimotor periphery. Recent studies have highlighted the importance of incorporating biologically plausible noise into such models. Here we extend the linear-quadratic-gaussian framework--currently the only framework where such problems can be solved efficiently--to include control-dependent, state-dependent, and internal noise. Under this extended noise model, we derive a coordinate-descent algorithm guaranteed to converge to a feedback control law and a nonadaptive linear estimator optimal with respect to each other. Numerical simulations indicate that convergence is exponential, local minima do not exist, and the restriction to nonadaptive linear estimators has negligible effects in the control problems of interest. The application of the algorithm is illustrated in the context of reaching movements. A Matlab implementation is available at www.cogsci.ucsd.edu/~todorov.

  18. Adaptive Control of Flexible Structures Using Residual Mode Filters

    Science.gov (United States)

    Balas, Mark J.; Frost, Susan

    2010-01-01

    Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.

  19. 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.

  20. Nonlinear Direct Robust Adaptive Control Using Lyapunov Method

    Directory of Open Access Journals (Sweden)

    Chunbo Xiu

    2013-07-01

    Full Text Available    The problem of robust adaptive stabilization of a class of multi-input nonlinear systems with arbitrary unknown parameters and unknown structure of bounded variation have been considered. By employing the direct adaptive and control Lyapunov function method, a robust adaptive controller is designed to complete the globally adaptive stability of the system states. By employing our result, a kind of nonlinear system is analyzed, the concrete form of the control law is given and the meaningful quadratic control Lyapunov function for the system is constructed. Simulation of parallel manipulator is provided to illustrate the effectiveness of the proposed method.

  1. Bayesian nonparametric adaptive control using Gaussian processes.

    Science.gov (United States)

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

    2015-03-01

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

  2. Observer-Based Adaptive Iterative Learning Control for a Class of Nonlinear Time Delay Systems with Input Saturation

    Directory of Open Access Journals (Sweden)

    Jian-ming Wei

    2015-01-01

    Full Text Available This paper presents an adaptive iterative learning control scheme for the output tracking of a class of nonlinear systems with unknown time-varying delays and input saturation nonlinearity. An observer is presented to estimate the states and linear matrix inequality (LMI method is employed for observer design. The assumption of identical initial condition for ILC is relaxed by introducing boundary layer function. The possible singularity problem is avoided by introducing hyperbolic tangent function. The uncertainties with time-varying delays are compensated for by the combination of appropriate Lyapunov-Krasovskii functional and Young’s inequality. Both time-varying and time-invariant radial basis function neural networks are employed to deal with system uncertainties. On the basis of a property of hyperbolic tangent function, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function in two cases, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.

  3. Durham adaptive optics real-time controller.

    Science.gov (United States)

    Basden, Alastair; Geng, Deli; Myers, Richard; Younger, Eddy

    2010-11-10

    The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shelf hardware. It is powerful enough to be used as the real-time controller for all currently planned 8 m class telescope AO systems. Here we give details of this controller and the concepts behind it, and report on performance, including latency and jitter, which is less than 10 μs for small AO systems.

  4. Case Study: Test Results of a Tool and Method for In-Flight, Adaptive Control System Verification on a NASA F-15 Flight Research Aircraft

    Science.gov (United States)

    Jacklin, Stephen A.; Schumann, Johann; Guenther, Kurt; Bosworth, John

    2006-01-01

    Adaptive control technologies that incorporate learning algorithms have been proposed to enable autonomous flight control and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments [1-2]. At the present time, however, it is unknown how adaptive algorithms can be routinely verified, validated, and certified for use in safety-critical applications. Rigorous methods for adaptive software verification end validation must be developed to ensure that. the control software functions as required and is highly safe and reliable. A large gap appears to exist between the point at which control system designers feel the verification process is complete, and when FAA certification officials agree it is complete. Certification of adaptive flight control software verification is complicated by the use of learning algorithms (e.g., neural networks) and degrees of system non-determinism. Of course, analytical efforts must be made in the verification process to place guarantees on learning algorithm stability, rate of convergence, and convergence accuracy. However, to satisfy FAA certification requirements, it must be demonstrated that the adaptive flight control system is also able to fail and still allow the aircraft to be flown safely or to land, while at the same time providing a means of crew notification of the (impending) failure. It was for this purpose that the NASA Ames Confidence Tool was developed [3]. This paper presents the Confidence Tool as a means of providing in-flight software assurance monitoring of an adaptive flight control system. The paper will present the data obtained from flight testing the tool on a specially modified F-15 aircraft designed to simulate loss of flight control faces.

  5. An Adaptive Memory Interface Controller for Improving Bandwidth Utilization of Hybrid and Reconfigurable Systems

    Energy Technology Data Exchange (ETDEWEB)

    Castellana, Vito G.; Tumeo, Antonino; Ferrandi, Fabrizio

    2014-05-30

    Emerging applications such as data mining, bioinformatics, knowledge discovery, social network analysis are irregular. They use data structures based on pointers or linked lists, such as graphs, unbalanced trees or unstructures grids, which generates unpredictable memory accesses. These data structures usually are large, but difficult to partition. These applications mostly are memory bandwidth bounded and have high synchronization intensity. However, they also have large amounts of inherent dynamic parallelism, because they potentially perform a task for each one of the element they are exploring. Several efforts are looking at accelerating these applications on hybrid architectures, which integrate general purpose processors with reconfigurable devices. Some solutions, which demonstrated significant speedups, include custom-hand tuned accelerators or even full processor architectures on the reconfigurable logic. In this paper we present an approach for the automatic synthesis of accelerators from C, targeted at irregular applications. In contrast to typical High Level Synthesis paradigms, which construct a centralized Finite State Machine, our approach generates dynamically scheduled hardware components. While parallelism exploitation in typical HLS-generated accelerators is usually bound within a single execution flow, our solution allows concurrently running multiple execution flow, thus also exploiting the coarser grain task parallelism of irregular applications. Our approach supports multiple, multi-ported and distributed memories, and atomic memory operations. Its main objective is parallelizing as many memory operations as possible, independently from their execution time, to maximize the memory bandwidth utilization. This significantly differs from current HLS flows, which usually consider a single memory port and require precise scheduling of memory operations. A key innovation of our approach is the generation of a memory interface controller, which

  6. L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

    Science.gov (United States)

    Griffin, Brian Joseph; Burken, John J.; Xargay, Enric

    2010-01-01

    This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.

  7. 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 ...

  8. STEADY ESTIMATION ALGORITHMS OF THE DYNAMIC SYSTEMS CONDITION ON THE BASIS OF CONCEPTS OF THE ADAPTIVE FILTRATION AND CONTROL

    Directory of Open Access Journals (Sweden)

    H.Z. Igamberdiyev

    2014-07-01

    Full Text Available Dynamic systems condition estimation regularization algorithms in the conditions of signals and hindrances statistical characteristics aprioristic uncertainty are offered. Regular iterative algorithms of strengthening matrix factor elements of the Kalman filter, allowing to adapt the filter to changing hindrance-alarm conditions are developed. Steady adaptive estimation algorithms of a condition vector in the aprioristic uncertainty conditions of covariance matrixes of object noise and the measurements hindrances providing a certain roughness of filtration process in relation to changing statistical characteristics of signals information parameters are offered. Offered practical realization results of the dynamic systems condition estimation algorithms are given at the adaptive management systems synthesis problems solution by technological processes of granulation drying of an ammophos pulp and receiving ammonia.

  9. Adaptive robust controller based on integral sliding mode concept

    Science.gov (United States)

    Taleb, M.; Plestan, F.

    2016-09-01

    This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.

  10. 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...

  11. 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....

  12. Chaos control for the output-constrained system by using adaptive dynamic surface technology and application to the brushless DC motor

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Shaohua, E-mail: hua66com@163.com [The Jiangsu Key Laboratory of Advanced Manufacturing Technology, Huaiyin Institute of Technology, Huai’an 223003 (China); School of Automation, Chongqing University, Chongqing 400044 (China); Hou, Zhiwei; Chen, Zhong [The Jiangsu Key Laboratory of Advanced Manufacturing Technology, Huaiyin Institute of Technology, Huai’an 223003 (China)

    2015-12-15

    In this paper, chaos control is proposed for the output- constrained system with uncertain control gain and time delay and is applied to the brushless DC motor. Using the dynamic surface technology, the controller overcomes the repetitive differentiation of backstepping and boundedness hypothesis of pre-determined control gain by incorporating radial basis function neural network and adaptive technology. The tangent barrier Lyapunov function is employed for time-delay chaotic system to prevent constraint violation. It is proved that the proposed control approach can guarantee asymptotically stable in the sense of uniformly ultimate boundedness without constraint violation. Finally, the effectiveness of the proposed approach is demonstrated on the brushless DC motor example.

  13. Chaos control for the output-constrained system by using adaptive dynamic surface technology and application to the brushless DC motor

    International Nuclear Information System (INIS)

    In this paper, chaos control is proposed for the output- constrained system with uncertain control gain and time delay and is applied to the brushless DC motor. Using the dynamic surface technology, the controller overcomes the repetitive differentiation of backstepping and boundedness hypothesis of pre-determined control gain by incorporating radial basis function neural network and adaptive technology. The tangent barrier Lyapunov function is employed for time-delay chaotic system to prevent constraint violation. It is proved that the proposed control approach can guarantee asymptotically stable in the sense of uniformly ultimate boundedness without constraint violation. Finally, the effectiveness of the proposed approach is demonstrated on the brushless DC motor example

  14. Linear Perturbation Adaptive Control of Hydraulically Driven Manipulators

    DEFF Research Database (Denmark)

    Andersen, T.O.; Hansen, M.R.; Conrad, Finn

    2004-01-01

    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 con...... joint behaves as an independent second-order system with fixed dynamics.......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...... 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...

  15. 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.

  16. 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.

  17. Excitation and Adaptation in Bacteria–a Model Signal Transduction System that Controls Taxis and Spatial Pattern Formation

    Directory of Open Access Journals (Sweden)

    Chuan Xue

    2013-04-01

    Full Text Available The machinery for transduction of chemotactic stimuli in the bacterium E. coli is one of the most completely characterized signal transduction systems, and because of its relative simplicity, quantitative analysis of this system is possible. Here we discuss models which reproduce many of the important behaviors of the system. The important characteristics of the signal transduction system are excitation and adaptation, and the latter implies that the transduction system can function as a “derivative sensor” with respect to the ligand concentration in that the DC component of a signal is ultimately ignored if it is not too large. This temporal sensing mechanism provides the bacterium with a memory of its passage through spatially- or temporally-varying signal fields, and adaptation is essential for successful chemotaxis. We also discuss some of the spatial patterns observed in populations and indicate how cell-level behavior can be embedded in population-level descriptions.

  18. Adaptive control based on retrospective cost optimization

    Science.gov (United States)

    Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)

    2012-01-01

    A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.

  19. The Reduced-order Design of Robust Adaptive Backstepping Controller

    Institute of Scientific and Technical Information of China (English)

    WUZhao-Jing; XIEXue-Jun; ZHANGSi-Ying

    2005-01-01

    For a class of systems with unmodeled dynamics, robust adaptive stabilization problem is considered in this paper. Firstly, by a series of coordinate changes, the original system is reparameterized. Then, by introducing a reduced-order observer, an error system is obtained. Based on the system, a reduced-order adaptive backstepping controller design scheme is given. It is proved that all the signals in the adaptive control system are globally uniformly bounded, and the regulation error converges to zero asymptotically. Due to the order deduction of the controller, the design scheme in this paper has more practical values. A simulation example further demonstrates the efficiency of the control scheme.

  20. Adaptive fuzzy controllers based on variable universe

    Institute of Scientific and Technical Information of China (English)

    李洪兴

    1999-01-01

    Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation functions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contraction-expansion factor is discussed. At last, three models of adaptive fuzzy control based on variable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.

  1. Modeling Power Systems as Complex Adaptive Systems

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  2. 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.

  3. Adaptive, predictive controller for optimal process control

    Energy Technology Data Exchange (ETDEWEB)

    Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.

    1995-12-01

    One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.

  4. Tracking with asymptotic sliding mode and adaptive input delay effect compensation of nonlinearly perturbed delayed systems applied to traffic feedback control

    Science.gov (United States)

    Mirkin, Boris; Haddad, Jack; Shtessel, Yuri

    2016-09-01

    Asymptotical sliding mode-model reference adaptive control design for a class of systems with parametric uncertainty, unknown nonlinear perturbation and external disturbance, and with known input and state delays is proposed. To overcome the difficulty to directly predict the plant state under uncertainties, a control design is based on a developed decomposition procedure, where a 'generalised error' in conjunction with auxiliary linear dynamic blocks with adjustable gains is introduced and the sliding variable is formed on the basis of this error. The effect of such a decomposition is to pull the input delay out of first step of the design procedure. As a result, similarly to the classical Smith predictor, the adaptive control architecture based only on the lumped-delays, i.e. without conventional in such cases difficult-implemented distributed-delay blocks. Two new adaptive control schemes are proposed. A linearisation-based control design is constructed for feedback control of an urban traffic region model with uncertain dynamics. Simulation results demonstrate the effectiveness of the developed adaptive control method.

  5. Adaptive protection algorithm and system

    Science.gov (United States)

    Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

    2009-04-28

    An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

  6. Wavelet Adaptive Reduced Order Observer Based Tracking Control for a Class of Uncertain Time Delay Nonlinear Systems Subjected to Actuator Saturation

    Directory of Open Access Journals (Sweden)

    Ajay Verma

    2012-11-01

    Full Text Available This Paper investigates the mean to design the reduced order observer and observer based controllers for a class of delayed uncertain nonlinear system subjected to actuator saturation. A new design approach of wavelet based adaptive reduced order observer is proposed. The proposed wavelet adaptive reduced order observer performs the task of identification of unknown system dynamics in addition to the reconstruction of states of the system. Wavelet neural network (WNN is used to approximate the uncertainties present in the system as well as to identify and compensate the nonlinearities introduced in the system due to actuator saturation. Using the feedback control, based on reconstructed states, the behavior of closed loop system is investigated. In addition robust control terms are also designed to attenuate the approximation error due to WNN. Adaptation laws are developed for the online tuning of the wavelet parameters and the stability of the overall systems is assured by using the Lyapunov- Krasovskii functional. A numerical example is provided to verify the effectiveness of theoretical development.

  7. Adaptive Clutch Engaging Process Control for Automatic Mechanical Transmission

    Institute of Scientific and Technical Information of China (English)

    LIU Hai-ou; CHEN Hui-yan; DING Hua-rong; HE Zhong-bo

    2005-01-01

    Based on detail analysis of clutch engaging process control targets and adaptive demands, a control strategy which is based on speed signal, different from that of based on main clutch displacement signal, is put forward. It considers both jerk and slipping work which are the most commonly used quality evaluating indexes of vehicle starting phase. The adaptive control system and its reference model are discussed profoundly.Taking the adaptability to different starting gears and different road conditions as examples, some proving field test records are shown to illustrate the main clutch adaptive control strategy at starting phase. Proving field test gives acceptable results.

  8. Improvement of adaptive fuzzy control for a photovoltaic/wind/diesel generating system; Taiyoko/furyoku/diesel hatsuden system no saitekigata fuzzy seigyo no kairyo

    Energy Technology Data Exchange (ETDEWEB)

    Nagaike, H.; Kenmoku, Y.; Sakakibara, T. [Toyohashi University of Technology, Aichi (Japan); Nakagawa, S. [Maizuru National College of Technology, Kyoto (Japan); Kawamoto, T. [Shizuoka University, Shizuoka (Japan).Faculty of Engineering

    1996-10-27

    The photovoltaic/wind/diesel generating system that uses a storage battery as auxiliary power has been proposed to supply power from the system to the independent area. In this system, it is important to generate no insufficient power from the viewpoint of effective energy utilization and minimize the fuel consumption of a diesel generator. Authors have proposed the adaptive fuzzy control that changes the shape of the membership function of input variables according to the parameter indicating the system state. However, a parameter was rapidly changed in the conventional method. This badly influences the control. Therefore, the way to determine the parameter that indicates the state of this system was improved. Assume that an input value is set to the average value between a certain point of time and the {Delta}t time as the method for determining a parameter. If the {Delta}t value is lower, the change in a membership function is more effective. As a result, a greater fuel reduction effect was obtained. 4 refs., 8 figs., 1 tab.

  9. An SRWNN-based approach on developing a self-learning and self-evolving adaptive control system for motion platforms

    Science.gov (United States)

    Onur Ari, Evrim; Kocaoglan, Erol

    2016-02-01

    In this paper, a self-recurrent wavelet neural network (SRWNN)-based indirect adaptive control architecture is modified for performing speed control of a motion platform. The transient behaviour of the original learning algorithm has been improved by modifying the learning rate updates. The contribution of the proposed modification has been verified via both simulations and experiments. Moreover, the performance of the proposed architecture is compared with robust RST designs performed on a similar benchmark system, to show that via adaptive nonlinear control, it is possible to obtain a fast step response without degrading the robustness of a multi-body mechanical system. Finally, the architecture is further improved so as to possess structural learning for populating the SRWNNs automatically, rather than employing static network structures, and simulation results are provided to show the performance of the proposed structural learning algorithm.

  10. Neuro-Adaptive Control of Robot Manipulator Using RBFN

    Energy Technology Data Exchange (ETDEWEB)

    Kim, J. D. [Cowell SysNet, Seoul (Korea); Lee, M. J.; Choi, Y. K.; Kim, S. S. [Pusan National University, Pusan (Korea)

    2001-01-01

    This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the parameters of RBFN is developed based on the Lyapunov stability theory to guarantee the stability of the overall control system. The filtered tracking error between the system output and the desired output is shown to be UUB(uniformly ultimately bounded). To evaluate the performance of the controller, the proposed method is applied to the trajectory control of the two-link manipulator. (author). 18 refs., 14 figs., 2 tabs.

  11. Design of an adaptive finite-time controller for synchronization of two identical/different non-autonomous chaotic flywheel governor systems

    International Nuclear Information System (INIS)

    The centrifugal flywheel governor (CFG) is a mechanical device that automatically controls the speed of an engine and avoids the damage caused by sudden change of load torque. It has been shown that this system exhibits very rich and complex dynamics such as chaos. This paper investigates the problem of robust finite-time synchronization of non-autonomous chaotic CFGs. The effects of unknown parameters, model uncertainties and external disturbances are fully taken into account. First, it is assumed that the parameters of both master and slave CFGs have the same value and a suitable adaptive finite-time controller is designed. Second, two CFGs are synchronized with the parameters of different values via a robust adaptive finite-time control approach. Finally, some numerical simulations are used to demonstrate the effectiveness and robustness of the proposed finite-time controllers. (general)

  12. Design of an adaptive finite-time controller for synchronization of two identical/different non-autonomous chaotic flywheel governor systems

    Institute of Scientific and Technical Information of China (English)

    Mohammad Pourmahmood Aghababa

    2012-01-01

    The centrifugal flywheel governor (CFG) is a mechanical device that automatically controls the speed of an engine and avoids the damage caused by sudden change of load torque. It has been shown that this system exhibits very rich and complex dynamics such as chaos.This paper investigates the problem of robust finite-time synchronization of non-autonomous chaotic CFGs.The effects of unknown parameters,model uncertainties and external disturbances are fully taken into account.First,it is assumed that the parameters of both master and slave CFGs have the same value and a suitable adaptive finite-time controller is designed.Second,two CFGs are synchronized with the parameters of different values via a robust adaptive finite-time control approach.Finally,some numerical simulations are used to demonstrate the effectiveness and robustness of the proposed finite-time controllers.

  13. An Adaptive Controller Design for Magnetic Levitation Ball System%磁悬浮球系统的自适应控制器设计

    Institute of Scientific and Technical Information of China (English)

    刘宁

    2011-01-01

    For a magnetic levitation ball system, a design method for an adaptive controller based on the linearized model and Backstepping scheme is proposed in this paper. The adaptive controller has some significant advantages such as the simple structure, easy to be realized and convenient to obtain the control input. Finally, the simulation results show the effectiveness of the proposed controller.%本文以磁悬浮球系统为研究对象,基于该系统的线性化模型,通过Backstepping设计方法设计了一类自适应控制器,所设计的控制器具有结构简单易于实现,控制输入易于得到等优点,仿真实验验证了该控制器的有效性.

  14. Quantitative Adaptation Analytics for Assessing Dynamic Systems of Systems.

    Energy Technology Data Exchange (ETDEWEB)

    Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.; Le, Hai D.; Kao, Gio K; Melander, Darryl J.; Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Robert Charles,

    2015-01-01

    Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

  15. Dynamics and Control of Adaptive Shells with Curvature Transformations

    Directory of Open Access Journals (Sweden)

    H.S. Tzou

    1995-01-01

    Full Text Available Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencies and controlled damping ratios are evaluated. The curvature change of the adaptive shell starts from an open shallow shell (30° and ends with a deep cylindrical shell (360°. Dynamic characteristics and control effectiveness (via the proportional velocity feedback of this series of shells are investigated and compared at every 30° curvature change. Analytical solutions suggest that the lower modes are sensitive to curvature changes and the higher modes are relatively insensitive.

  16. DESIGN PATTERNS FOR SELF ADAPTIVE SYSTEMS ENGINEERING

    Directory of Open Access Journals (Sweden)

    Yousef Abuseta

    2015-07-01

    Full Text Available Self adaptation has been proposed to overcome the complexity of today's software systems which results from the uncertainty issue. Aspects of uncertainty include changing systems goals, changing resource availability and dynamic operating conditions. Feedback control loops have been recognized as vital elements for engineering self-adaptive systems. However, despite their importance, there is still a lack of systematic way of the design of the interactions between the different components comprising one particular feedback control loop as well as the interactions between components from different control loops . Most existing approaches are either domain specific or too abstract to be useful. In addition, the issue of multiple control loops is often neglected and consequently self adaptive systems are often designed around a single loop. In this paper we propose a set of design patterns for modeling and designing self adaptive software systems based on MAPE-K. Control loop of IBM architecture blueprint which takes into account the multiple control loops issue. A case study is presented to illustrate the applicability of the proposed design patterns.

  17. Adaptive security systems -- Combining expert systems with adaptive technologies

    Energy Technology Data Exchange (ETDEWEB)

    Argo, P.; Loveland, R.; Anderson, K. [and others

    1997-09-01

    The Adaptive Multisensor Integrated Security System (AMISS) uses a variety of computational intelligence techniques to reason from raw sensor data through an array of processing layers to arrive at an assessment for alarm/alert conditions based on human behavior within a secure facility. In this paper, the authors give an overview of the system and briefly describe some of the major components of the system. This system is currently under development and testing in a realistic facility setting.

  18. Adaptive security systems -- Combining expert systems with adaptive technologies

    International Nuclear Information System (INIS)

    The Adaptive Multisensor Integrated Security System (AMISS) uses a variety of computational intelligence techniques to reason from raw sensor data through an array of processing layers to arrive at an assessment for alarm/alert conditions based on human behavior within a secure facility. In this paper, the authors give an overview of the system and briefly describe some of the major components of the system. This system is currently under development and testing in a realistic facility setting

  19. Backstepping design of missile guidance and control based on adaptive fuzzy sliding mode control

    OpenAIRE

    Ran Maopeng; Wang Qing; Hou Delong; Dong Chaoyang

    2014-01-01

    This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of...

  20. SOFC temperature evaluation based on an adaptive fuzzy controller

    Institute of Scientific and Technical Information of China (English)

    Xiao-juan WU; Xin-jian ZHU; Guang-yi CAO; Heng-yong TU

    2008-01-01

    The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.

  1. STOCHASTIC ADAPTIVE SWITCHING CONTROL BASED ON MULTIPLE MODELS

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yanxia; GUO Lei

    2002-01-01

    It is well known that the transient behaviors of the traditional adaptive control may be very poor in general, and that the adaptive control designed based on switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances. In this paper, we shall prove that for a typical class of linear systems disturbed by random noises, the multiple model based least-squares (LS)adaptive switching control is stable and convergent, and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators. Moreover,the mixed case combining adaptive models with fixed models is also considered.

  2. 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.

  3. Vibration Control of Flexible Spacecraft Using Adaptive Controller

    OpenAIRE

    George, V. I.; B. Ganesh Kamath; I. Thirunavukkarasu; Ciji Pearl Kurian

    2012-01-01

    The aim is to develop vibration control of flexible spacecraft by adaptive controller. A case study will be carried out which simulates planar motion of flexible spacecraft as a coupled hybrid dynamics of rigid body motion and the flexible arm vibration. The notch filter and adaptive vibration controller, which updates filter and controller parameters continuously from the sensor measurement, are implemented in the real time control. The least mean square algorithm using the adaptive notch fi...

  4. ADAPTIVE SYSTEMS THEORY: SOME BASIC CONCEPTS, METHODS AND RESULTS

    Institute of Scientific and Technical Information of China (English)

    GUO Lei

    2003-01-01

    The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertainties in both the system's structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some "critical values" and establishing some "Impossibility Theorems" for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.

  5. Adaptive ophthalmologic system

    Science.gov (United States)

    Olivier, Scot S.; Thompson, Charles A.; Bauman, Brian J.; Jones, Steve M.; Gavel, Don T.; Awwal, Abdul A.; Eisenbies, Stephen K.; Haney, Steven J.

    2007-03-27

    A system for improving vision that can diagnose monochromatic aberrations within a subject's eyes, apply the wavefront correction, and then enable the patient to view the results of the correction. The system utilizes a laser for producing a beam of light; a corrector; a wavefront sensor; a testing unit; an optic device for directing the beam of light to the corrector, to the retina, from the retina to the wavefront sensor, and to the testing unit; and a computer operatively connected to the wavefront sensor and the corrector.

  6. Adaptive coordinated control of engine speed and battery charging voltage

    Institute of Scientific and Technical Information of China (English)

    Jiangyan ZHANG; Xiaohong JIAO

    2008-01-01

    In this paper, the control problem of auxiliary power unit (APU) for hybrid electric vehicles is investigated. An adaptive controller is provided to achieve the coordinated control between the engine speed and the battery charging voltage. The proposed adaptive coordinated control laws for the throttle angle of the engine and the voltage of the power-converter can guarantee not only the asymptotic tracking performance of the engine speed and the regulation of the battery charging voltage, but also the robust stability of the closed loop system under external load changes. Simulation results are given to verify the performance of the proposed adaptive controller.

  7. 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.

  8. 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.

  9. Flexible Satellite Attitude Control via Adaptive Fuzzy Linearization

    Institute of Scientific and Technical Information of China (English)

    GUAN Ping; LIU Xiang-dong; CHEN Jia-bin; LIU Xiao-he

    2005-01-01

    The adaptive fuzzy control is combined with input-output linearization control to constitute the hybrid controller. The control method is then applied to the attitude maneuver control of the flexible satellite.The basic control structure is given. The rules of the controller parameter selection, which guarantee the attitude stabilization of the satellite with parameter uncertainties, have been analyzed. Simulation results show that the precise attitude control is accomplished in spite of the uncertainty in the system.

  10. Adaptive Neural Control for a Class of Low-triangular-structured Nonlinear Systems with H-∞Performance Analysis

    Institute of Scientific and Technical Information of China (English)

    WANG Hui-feng; DU Hong-bin

    2008-01-01

    In this paper,a neural-network-based variable structure control scheme is presented for a class of nonlinear systems with a general low triangular structure.The proposed variable structure controller is proved to be C1,thus can be applied for backstepping design,which has extended the scope of previous nonlinear systems in the form of strict-feedback and pure-feedback.With the help of neural network approximator,H-oo performance analysis of stability is given.The effectiveness of proposed control law is verified via simulation.

  11. Complex and Adaptive Dynamical Systems A Primer

    CERN Document Server

    Gros, Claudius

    2011-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  12. Chaos control for the output-constrained system by using adaptive dynamic surface technology and application to the brushless DC motor

    Directory of Open Access Journals (Sweden)

    Shaohua Luo

    2015-12-01

    Full Text Available In this paper, chaos control is proposed for the output- constrained system with uncertain control gain and time delay and is applied to the brushless DC motor. Using the dynamic surface technology, the controller overcomes the repetitive differentiation of backstepping and boundedness hypothesis of pre-determined control gain by incorporating radial basis function neural network and adaptive technology. The tangent barrier Lyapunov function is employed for time-delay chaotic system to prevent constraint violation. It is proved that the proposed control approach can guarantee asymptotically stable in the sense of uniformly ultimate boundedness without constraint violation. Finally, the effectiveness of the proposed approach is demonstrated on the brushless DC motor example.

  13. Adaptive Neural Network-Based Event-Triggered Control of Single-Input Single-Output Nonlinear Discrete-Time Systems.

    Science.gov (United States)

    Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

    2016-01-01

    This paper presents a novel adaptive neural network (NN) control of single-input and single-output uncertain nonlinear discrete-time systems under event sampled NN inputs. In this control scheme, the feedback signals are transmitted, and the NN weights are tuned in an aperiodic manner at the event sampled instants. After reviewing the NN approximation property with event sampled inputs, an adaptive state estimator (SE), consisting of linearly parameterized NNs, is utilized to approximate the unknown system dynamics in an event sampled context. The SE is viewed as a model and its approximated dynamics and the state vector, during any two events, are utilized for the event-triggered controller design. An adaptive event-trigger condition is derived by using both the estimated NN weights and a dead-zone operator to determine the event sampling instants. This condition both facilitates the NN approximation and reduces the transmission of feedback signals. The ultimate boundedness of both the NN weight estimation error and the system state vector is demonstrated through the Lyapunov approach. As expected, during an initial online learning phase, events are observed more frequently. Over time with the convergence of the NN weights, the inter-event times increase, thereby lowering the number of triggered events. These claims are illustrated through the simulation results.

  14. 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.

  15. Adaptive nonlinear control for a research reactor

    International Nuclear Information System (INIS)

    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)

  16. Neural Network Inverse Adaptive Controller Based on Davidon Least Square

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    General neural network inverse adaptive controller haa two flaws: the first is the slow convergence speed; the second is the invalidation to the non-minimum phase system.These defects limit the scope in which the neural network inverse adaptive controller is used.We employ Davidon least squares in training the multi-layer feedforward neural network used in approximating the inverse model of plant to expedite the convergence,and then through constructing the pseudo-plant,a neural network inverse adaptive controller is put forward which is still effective to the nonlinear non-minimum phase system.The simulation results show the validity of this scheme.

  17. Hyperchaos, adaptive control and synchronization of a novel 5-D hyperchaotic system with three positive Lyapunov exponents and its SPICE implementation

    Directory of Open Access Journals (Sweden)

    Vaidyanathan Sundarapandian

    2014-12-01

    Full Text Available In this research work, a twelve-term novel 5-D hyperchaotic Lorenz system with three quadratic nonlinearities has been derived by adding a feedback control to a ten-term 4-D hyperchaotic Lorenz system (Jia, 2007 with three quadratic nonlinearities. The 4-D hyperchaotic Lorenz system (Jia, 2007 has the Lyapunov exponents L1 = 0.3684,L2 = 0.2174,L3 = 0 and L4 =−12.9513, and the Kaplan-Yorke dimension of this 4-D system is found as DKY =3.0452. The 5-D novel hyperchaotic Lorenz system proposed in this work has the Lyapunov exponents L1 = 0.4195,L2 = 0.2430,L3 = 0.0145,L4 = 0 and L5 = −13.0405, and the Kaplan-Yorke dimension of this 5-D system is found as DKY =4.0159. Thus, the novel 5-D hyperchaotic Lorenz system has a maximal Lyapunov exponent (MLE, which is greater than the maximal Lyapunov exponent (MLE of the 4-D hyperchaotic Lorenz system. The 5-D novel hyperchaotic Lorenz system has a unique equilibrium point at the origin, which is a saddle-point and hence unstable. Next, an adaptive controller is designed to stabilize the novel 5-D hyperchaotic Lorenz system with unknown system parameters. Moreover, an adaptive controller is designed to achieve global hyperchaos synchronization of the identical novel 5-D hyperchaotic Lorenz systems with unknown system parameters. Finally, an electronic circuit realization of the novel 5-D hyperchaotic Lorenz system using SPICE is described in detail to confirm the feasibility of the theoretical model.

  18. High Efficiency Lighting with Integrated Adaptive Control (HELIAC) Project

    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...

  19. High Efficiency Lighting with Integrated Adaptive Control (HELIAC) Project

    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...

  20. 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.