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Fuzzy-identification-based adaptive backstepping control using a self-organizing fuzzy system 总被引:1,自引:0,他引:1
Pin-Cheng Chen Chun-Fei Hsu Tsu-Tian Lee Chi-Hsu Wang 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2009,13(7):635-647
In this paper, a fuzzy-identification-based adaptive backstepping control (FABC) scheme is proposed. The FABC system is composed
of a backstepping controller and a robust controller. The backstepping controller, which uses a self-organizing fuzzy system
(SFS) with the structure and parameter learning phases to on-line estimate the controlled system dynamics, is the principal
controller, and the robust controller is designed to dispel the effect of approximation error introduced by the SFS. The developed
SFS automatically generates and prunes the fuzzy rules by the proposed structure adaptation algorithm and the parameters of
the fuzzy rules and membership functions tunes on-line in the Lyapunov sense. Thus, the overall closed-loop FABC system can
guarantee that the tracking error and parameter estimation error are uniformly ultimately bounded; and the tracking error
converges to a desired small neighborhood around zero. Finally, the proposed FABC system is applied to a chaotic dynamic system
to show its effectiveness. The simulation results verify that the proposed FABC system can achieve favorable tracking performance
even with unknown controlled system dynamics. 相似文献
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Magnetic levitation systems have become very important in many applications. Due to their instability and high nonlinearity, such systems pose a challenge to many researchers attempting to design high-performance and robust tracking control. This paper proposes an improved adaptive fuzzy backstepping control for systems with uncertain input nonlinear function (uncertain parameters and structure), and applies it to a magnetic levitation system, which is a typical representative of such systems. An adaptive fuzzy system is used to approximate unknown, partially known or uncertain input nonlinear functions of a magnetic levitation system. An adaptation law is obtained based on Ljapunov analysis in order to guarantee closed-loop stability and good tracking performance. Initial adaptive and control parameters have been initialized with Symbiotic Organism Search optimization algorithm, due to strong non-linearity and instability of the magnetic levitation system. The theoretical background of the proposed control method is verified with a simulation study and implementation on a laboratory experimental application. 相似文献
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In this paper,a new fuzzy adaptive control approach is developed for a class of SISO uncertain pure-feedback nonlinear systems with immeasurable states.Fuzzy logic systems are utilized to approximate the unknown nonlinear functions;and the filtered signals are introduced to circumvent algebraic loop systems encountered in the implementation of the controller,and a fuzzy state adaptive observer is designed to estimate the immeasurable states.By combining the adaptive backstepping technique,an adaptive fuzzy output feedback control scheme is developed.It is proven that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded(SGUUB),and the observer and tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Simulation studies are included to illustrate the efectiveness of the proposed approach. 相似文献
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In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlinear functions. A design scheme of the robust adaptive fuzzy controller is proposed by use of the backstepping technique. The proposed controller guarantees semi-global uniform ultimate boundedness of all the signals in the derived closed-loop system and achieves the good tracking performance. The possible controller singularity problem which may occur in some existing adaptive control schemes with feedback linearization techniques can be avoided. In addition, the number of the on-line adaptive parameters is not more than the order of the designed system. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed control scheme. 相似文献
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In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlinear functions. A design scheme of the robust adaptive fuzzy controller is proposed by use of the backstepping technique. The proposed controller guarantees semi-global uniform ultimate boundedness of all the signals in the derived closed-loop system and achieves the good tracking performance. The possible controller singularity problem which may occur in some existing adaptive control schemes with feedback linearization techniques can be avoided. In addition, the number of the on-line adaptive parameters is not more than the order of the designed system. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed control scheme. 相似文献
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动态不确定非线性系统直接自适应模糊backstepping控制 总被引:3,自引:0,他引:3
对一类单输入单输出动态不确定非线性系统,提出一种直接自适应模糊backstepping和小增益相结合的控制方法.设计中,首先用模糊逻辑系统逼近虚拟控制器:其次把自适应模糊控制和backstepping控制设计技术相结合.给出了直接自适应模糊控制设计方法.最后基于Lyapunov函数和小增益方法证明了整个闭环系统的稳定性.仿真实例进一步验证了所提方法的有效性. 相似文献
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基于自适应Backstepping设计的TCSC非线性鲁棒控制器 总被引:2,自引:2,他引:0
电力系统是强非线性的动态大系统,在运行中总要受到外部干扰和内部干扰的影响,从而对其稳定运行造成严重威胁.本文针对带有TCSC单机无穷大母线系统的三阶鲁棒模型,在考虑阻尼系数未知及系统受外部扰动的情况下,将自适应backstepping方法与非线性L2增益干扰抑制理论融合,构造出系统的存贮函数,并获得非线性自适应鲁棒控制器及参数替换律.所得控制器不仅能够保证系统状态有界,而且能够有效抑制干扰对系统输出的影响.通过对单机系统的仿真结果表明采用该方法的控制器优于传统的控制器. 相似文献
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基于扩展自适应Backstepping设计的TCSC非线性控制的新方法 总被引:1,自引:1,他引:0
首先针对一般的参数反馈型非线性系统提出一种扩展自适应Backstepp ing方法.该方法不仅保留系统的非线性特性和对未知参数的实时在线估计,而且突破经典的确定性等价性原理来设计参数估计器和动态反馈控制器.该方法可用于带有TCSC(thyristor controlled series compensation)的单机无穷大系统.仿真结果表明,该方法在系统响应和自适应速度方面优于传统的Backstepp ing方法. 相似文献
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A stable decentralized adaptive fuzzy sliding mode control scheme is proposed for reconfigurable modular manipulators to satisfy the concept of modular software. For the development of the decentralized control, the dynamics of reconfigurable modular manipulators is represented as a set of interconnected subsystems. A first‐order Takagi–Sugeno fuzzy logic system is introduced to approximate the unknown dynamics of subsystem by using adaptive algorithm. The effect of interconnection term and fuzzy approximation error is removed by employing an adaptive sliding mode controller. All adaptive algorithms in the subsystem controller are derived from the sense of Lyapunov stability analysis, so that resulting closed‐loop system is stable and the trajectory tracking performance is guaranteed. The simulation results are presented to show the effectiveness of the proposed decentralized control scheme. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
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A combined backstepping and small-gain approach to robust adaptive fuzzy control for strict-feedback nonlinear systems 总被引:3,自引:0,他引:3
Yansheng Yang Gang Feng Junsheng Ren 《IEEE transactions on systems, man, and cybernetics. Part A, Systems and humans : a publication of the IEEE Systems, Man, and Cybernetics Society》2004,34(3):406-420
In this paper, a robust adaptive tracking control problem is discussed for a general class of strict-feedback uncertain nonlinear systems. The systems may possess a wide class of uncertainties referred to as unstructured uncertainties, which are not linearly parameterized and do not have any prior knowledge of the bounding functions. The Takagi-Sugeno type fuzzy logic systems are used to approximate the uncertainties. A unified and systematic procedure is employed to derive two kinds of novel robust adaptive tracking controllers by use of the input-to-state stability (ISS) and by combining the backstepping technique and generalized small gain approach. One is the robust adaptive fuzzy tracking controller (RAFTC) for the system without input gain uncertainty. The other is the robust adaptive fuzzy sliding tracking controller (RAFSTC) for the system with input gain uncertainty. Both algorithms have two advantages, those are, semi-global uniform ultimate boundedness of adaptive control system in the presence of unstructured uncertainties and the adaptive mechanism with minimal learning parameterizations. Four application examples, including a pendulum system with motor, a one-link robot, a ship roll stabilization with actuator and a single-link manipulator with flexible joint, are used to demonstrate the effectiveness and performance of proposed schemes. 相似文献
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Neural Computing and Applications - This paper investigates a novel control algorithm to deal with trajectory tracking control problems of robotic manipulators based on adaptive backstepping... 相似文献
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Toshio Yoshimura 《International journal of systems science》2013,44(5):763-775
This paper presents a simplified adaptive fuzzy backstepping control for uncertain discrete-time nonlinear systems. It is assumed that the systems are described by a discrete-time equation with nonlinear uncertainties to be viewed as the modelling errors and the unknown external disturbances, and the states are observed with measurement noises. To design the simplified adaptive fuzzy backstepping control, the modelling errors are approximated by using the fuzzy inference approach based on the extended single-input rule modules, and the estimates for the unmeasurable states and the adjustable parameters are derived by using the weighted and its simplified weighted least squares estimators. It is proved that the states are ultimately bounded, and the estimation errors remain in the vicinity of zero. The effectiveness of the proposed approach is indicated through the simulation experiment of a simple numerical system. 相似文献
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Toshio Yoshimura 《International journal of systems science》2017,48(4):695-704
This paper presents a direct adaptive fuzzy backstepping control (AFBC) for multi-input multi-output uncertain discrete-time nonlinear systems. It is assumed that the systems are described by a discrete-time state equation with uncertainties to be viewed as the modelling errors and the unknown external disturbances, and the observation of the states is taken with independent measurement noises. The proposed direct AFBC is presented as follows. The proposed direct AFBC is assumed to be the fuzzy logic system by removing the explosion of complexity problem due to repeated computation of nonlinear functions at the first stage. Second, the number of the adjustable parameters is reduced by the fuzzy inference approach based on the extended single input rule modules. Third, the simplified weighted least squares estimator is constructed by reducing the computational burden of the estimation for the unmeasurable states and the adjustable parameters. The effectiveness of the proposed direct AFBC is illustrated through the simulation experiment of a simple numerical system. 相似文献
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针对欠驱动船舶在稳定航速条件下轨迹跟踪问题,提出了一种基于自适应神经网络与反步法相结合的控制算法.该算法将实际的欠驱动船舶视为模型完全未知的非线性系统,利用神经网络的函数逼近特性实现控制器中非线性部分的在线估计,采用同时调整输入层-隐层、隐层-输出层间的权值阵的方法进行神经网络权值调整.通过选取积分型Lyapunov函数证明了闭环系统的稳定性.仿真实验表明该控制策略具有良好的跟踪特性,可以实现对期望航迹的精确跟踪. 相似文献
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