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1.
本文针对一类带有未知齐次函数的非线性系统,首先基于伸缩器和饱和器的概念,将T-S型模糊逻辑系统的输入–输出进行改造而形成扩展模糊逻辑系统,然后利用扩展模糊逻辑系统给出一种带有可调伸缩因子参数的模糊自适应控制器的设计方法.由于该方法不依赖模糊规则数目,因而不仅能有效减少在线估计的参数数目,而且能够保证被控系统的状态一致终极有界.最后所给数值仿真算例说明了该设计方法的有效性.  相似文献   

2.
本文基于Takagi-Sugeno(T-S)模糊模型,研究了混沌系统的自适应同步。基于T-S模糊模型重构了混沌系统,推导了在衰减率α下,自适应同步全局渐近稳定的充分条件;同时,在驱动系统参数未知的情况下,使用自适应参数调节律,得到响应系统参数的估计值。设计的模糊控制器均由线性函数构成,结构简单,规则少,有利于实际应用中构造控制器。数值仿真结果验证了方法的有效性。  相似文献   

3.
基于模糊控制理论和滑模控制理论以及自适应控制理论,研究了一类含有外部扰动的不确定分数阶混沌系统的混合投影同步问题.提出了一种自适应模糊滑模控制的分数阶混沌系统投影同步方法.模糊逻辑系统用来逼近未知的非线性函数和外部扰动,并且对逼近误差采用了自适应控制,同时构造了一种具有较强鲁棒性的分数阶积分滑模面.应用分数阶Barbalat引理设计了自适应模糊滑模控制器和参数自适应律.最后数值仿真结果验证了所提控制方法的有效性.  相似文献   

4.
对一类非线性离散时间系统提出一种新的模糊的辨识方法。该方法在假设逼近误差界已知的情况下,基于死区函数对模糊逻辑系统中的未知参数设计自适应学习律;在逼近误差界未知的情况下,基于时变死区函数对模糊逻辑系统中的未知参数设计自适应学习律,并对时变死区进行自适应调节。证明了所设计的自适应学习律均可使辨识误差收敛到原点的一个小邻域内。仿真结果表明了该算法的有效性。  相似文献   

5.
对质心位置未知的移动机器人系统设计了基于快速终端滑模的模糊自适应路径跟踪控制方法。该方法采用模糊逻辑系统逼近控制器中的未知函数,基于李亚普诺夫稳定性分析方法对未知参数设计自适应律,并设计鲁棒控制器来补偿逼近误差。该方法不但可以保证闭环系统中的所有信号有界,而且可使跟踪误差在有限时间内收敛到原点的小邻域内。仿真结果验证了方法的有效性。  相似文献   

6.
用两种不同的方法-主动控制法和自适应控制法实现超混沌Rssler系统和超混沌Lorenz系统的异结构全状态混合投影同步,各自设计了不同的控制器,使得响应系统与驱动系统同步。当参数已知时,采用主动控制法,方法简单有效且不需要构造Lyapunov函数,实现同步的时间短;当系统参数部分未知或完全未知时,基于Lyapunov稳定性理论,给出自适应同步控制器的系统性设计过程和参数自适应律,使得系统间迅速达到同步。数值模拟验证了两种方法的有效性。  相似文献   

7.
一类严格反馈非线性系统的间接自适应模糊控制   总被引:2,自引:0,他引:2  
针对一类不确定严格反馈非线性系统,设计了间接自适应模糊控制方法.该方法用模糊逻辑系统逼近设计过程中的未知函数,基于时变宽度死区对模糊逻辑系统中的未知参数进行自适应调节,并对时变死区宽度设计了自适应律.证明了该方法能使闭环系统的所有信号有界,且可使跟踪误差收敛到原点的小邻域内.仿真算例验证了该方法的有效性.  相似文献   

8.
用两种不同的方法一主动控制法和自适应控制法实现超混沌Rossler系统和超混沌Lorenz系统的异结构全状态混合投影同步,各自设计了不同的控制器,使得响应系统与驱动系统同步.当参数已知时,采用主动控制法,方法简单有效且不需要构造Lyapunov函数,实现同步的时间短;当系统参数部分未知或完全未知时,基于Lyapunov稳定性理论,给出自适应同步控制器的系统性设计过程和参数自适应律,使得系统间迅速达到同步.数值模拟验证了两种方法的有效性.  相似文献   

9.
师五喜  郭利进  郭文成 《控制与决策》2009,24(10):1573-1575

针对一类不确定严格反馈非线性系统,设计了间接自适应模糊控制方法.该方法用模糊逻辑系统逼近设计过程中的未知函数,基于时变宽度死区对模糊逻辑系统中的未知参数进行自适应调节,并对时变死区宽度设计了自适应律.证明了该方法能使闭环系统的所有信号有界,且可使跟踪误差收敛到原点的小邻域内.仿真算例验证了该方法的有效性.

  相似文献   

10.
研究了带有扰动和未知参数的混沌系统状态变量函数向量同步问题。分别针对驱动系统和响应系统设计出状态变量函数向量,利用自适应反馈原理和Lyapunov定理,构造出控制器,可以保证两状态变量函数向量同步。仿真结果表明该方法的有效性。  相似文献   

11.
In this paper, the projective synchronization problem of two fractional-order different chaotic (or hyperchaotic) systems with both uncertain dynamics and external disturbances is considered. More particularly, a fuzzy adaptive control system is investigated for achieving an appropriate projective synchronization of unknown fractional-order chaotic systems. The adaptive fuzzy logic systems are used to approximate some uncertain nonlinear functions appearing in the system model. These latter are augmented by a robust control term to compensate for the unavoidable fuzzy approximation errors and external disturbances as well as residual error due to the use of the so-called e-modification in the adaptive laws. A Lyapunov approach is adopted for the design of the parameter adaptation laws and the proof of the corresponding stability as well as the asymptotic convergence of the underlying synchronization errors towards zero. The effectiveness of the proposed synchronization system is illustrated through numerical experiment results.  相似文献   

12.
The problems on chaos control and hybrid projective synchronization for a class of new chaotic systems are considered. First, new 4D chaotic systems are proposed by introducing an additional state into a 3D quadratic chaotic system and the states of the systems corresponding to the different ranges of parameter b are exhibited. Second, a single scalar adaptive feedback controller for chaos control of the systems is presented. Third, hybrid projective synchronization (HPS) of two of the chaotic systems with parameters in different conditions are investigated by presenting adaptive feedback control strategies with adaptive parameter update laws and considering controller simplification to achieve complete synchronization. Finally, numerical simulations are demonstrated to verify the effectiveness of the strategies.  相似文献   

13.
Da Lin  Xingyuan Wang 《Neurocomputing》2011,74(12-13):2241-2249
This paper proposes a self-organizing adaptive fuzzy neural control (SAFNC) for the synchronization of uncertain chaotic systems with random-varying parameters. The proposed SAFNC system is composed of a computation controller and a robust controller. The computation controller containing a self-organizing fuzzy neural network (SOFNN) identifier is the principle controller. The SOFNN identifier is used to online estimate the compound uncertainties with the structure and parameter learning phases of fuzzy neural network (FNN), simultaneously. The structure-learning phase consists of the growing of membership functions, the splitting of fuzzy rules and the pruning of fuzzy rules, and thus the SOFNN identifier can avoid the time-consuming trial-and-error tuning procedure for determining the network structure of fuzzy neural network. The robust controller is used to attenuate the effects of the approximation error so that the synchronization of chaotic systems is achieved.All the parameter learning algorithms are derived based on the Lyapunov stability theorem to ensure network convergence as well as stable synchronization performance. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper.  相似文献   

14.
针对一类具有未知不确定性,且状态不可测的非线性系统,考虑了输入端的饱和非对称扇区非线性特性影响,提出了系统模型未知情形下基于自适应模糊观测器的跟踪控制方案,采用Lyapunov-Krasovskii函数给出了滑模控制器参数和模糊逻辑的自适应调整律.所提方法不仅可保证闭环跟踪系统的稳定性,还削弱了传统方法对模型结构的依赖...  相似文献   

15.
In this paper, a fuzzy adaptive variable-structure controller is investigated for a class of uncertain multi-input multi-output (MIMO) chaotic systems with both sector nonlinearities and dead-zones. A suitable adaptive fuzzy system is used to reasonably approximate the uncertain functions. A Lyapunov approach is employed to derive the parameter adaptation laws and prove the boundedness of all signals of the closed-loop system as well as the exponential convergence of the closed-loop errors to an adjustable region. The proposed controller can be applied to the systems with or without sector nonlinearities and/or dead-zones in the input. The effectiveness of the proposed fuzzy adaptive controller is illustrated throughout simulation results.  相似文献   

16.
考虑LuGre 摩擦的伺服系统自适应模糊控制   总被引:1,自引:0,他引:1  
针对摩擦非线性的存在会使伺服系统控制精度难以提高的问题,建立了考虑动态LuGre摩擦的伺服系统数学模型,在系统参数和负载转矩未知的情况下设计了自适应模糊控制器,用自适应模糊逻辑系统在线逼近包含LuGre摩擦在内的非线性环节,从而实现了伺服系统高精度的位置跟踪。利用Lyapunov函数证明了闭环系统的稳定性。仿真结果表明,该控制器能有效地补偿摩擦非线性的影响,并对负载转矩变化具有较强的鲁棒性。  相似文献   

17.
基于模糊逻辑系统具有充分利用语言信息和逼近连续函数性质的思想,分析研究了一类非线性不确定复杂系统的自适应控制问题.利用系统的数学模型和模糊逻辑系统对不确定性的输出信息,设计出了复杂系统的分散自适应鲁棒控制器和模糊逻辑系统参数估计的自适应律,在较弱的假设条件下,证明了这种控制器使被控系统的状态及参数估计误差一致终极有界.仿真实例表明,所提出的方法是有效的.  相似文献   

18.
This paper presents a robust adaptive fuzzy control algorithm for controlling unknown chaotic systems. The control approach encompasses a fuzzy system and a robust controller. The fuzzy system is designed to mimic an ideal controller, based on sliding-mode control. The robust controller is designed to compensate for the difference between the fuzzy controller and the ideal controller. The parameters of the fuzzy system, as well as uncertainty bound of the robust controller, are tuned adaptively. The adaptive laws are derived in the Lyapunov sense to guarantee the stability of the controlled system. Numerical simulations show the effectiveness of the proposed approach.  相似文献   

19.
An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach.  相似文献   

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