一类永磁电动机的混沌反控制研究

研究了永磁同步电动机系统在不改变电机结构参数条件下的混沌反控制问题.该方法借鉴非线性系统模型跟踪控制的思想,利用电机系统和混沌系统状态变量之间的关系来设计控制器.根据误差的变化,控制器随时做出响应,强迫被控系统的状态变量从非混沌状态转化为混沌状态.实现了永磁同步电动机系统比较精确跟踪混沌系统的过程.本文方法中控制器参数的选取范围比较宽,为控制器设计带来很大方便.仿真结果验证了本文控制方法的有效性.     

基于跟踪的混沌反控制

为了实现连续系统的混沌反控制,研究了基于跟踪已知混沌系统的混沌反控制方法,设计了非线性控制器使连续系统跟踪混沌输入信号,从而使非混沌系统产生与混沌输入信号拓扑共轭的混沌现象。采用的方法中控制器的参数选择比较灵活,为控制器的设计带来很大方便。同时,该法无需计算被控系统的Lyapunov指数,大大减少了混沌反控制的复杂计算。通过跟踪Lorenz混沌系统和超混沌Chen系统说明了该方法的设计过程,仿真结果表明了该方法的有效性和快速性。     

利用部分状态反馈的统一混沌系统的混沌同步

通常混沌同步控制器的设计大都需要全部状态或多个输入,对此利用Lyapunov函数和一些不等式技巧,给出一种新的同步控制器设计方法.该方法仅使用一个输入一个状态反馈,或仅使用两个输入一个状态反馈设计Lorenz混沌系统和Unified混沌系统的同步控制器,实现了二者全局指数混沌同步.该控制器只需一个状态变量,结构简单,实现容易,而且所给算法减小了参数选取的保守性.算例仿真结果表明了所给方法的有效性.     

基于参数辨识的自适应时滞混沌系统同步

在同步控制器的研究中,估计系统的未知参数是实现混沌同步必须解决的关键技术,研究参数不确定情况下为了时滞混沌系统的同步.根据Lyapunov-krasovskii泛函理论,研究了一类参数不确定的多维时滞混沌系统同步问题.采用参数辨识与自适应技术,通过数学推导证明,分别设计了时滞同步控制器和参数自适应律.以三维和四维时滞混沌系统为例,通过仿真,证明系统能达到较满意的同步效果,并且未知参数能够得到较好的辨识,说明设计方法具有有效性和普适性.     

一类受迫振荡混沌系统的自适应控制

针对一类受迫振荡混沌系统,提出了一种普遍适用的自适应控制方法,给出了自适应控制器及参数自适应律的设计方法.基于Lyapunov稳定性理论,证明了系统的稳定性.仿真实验表明,本文所提方法避免了混沌系统中除受迫振荡项外的不确定参数的影响,实现了一类混沌系统的有效控制及受迫振荡项参数的准确辨识,方法具有良好的可实现性和工程应用价值.     

渐近跟踪鲁棒控制的混沌同步

对混沌系统同步控制中的控制器进行了研究,因其实际应用受限大等因素而要求系统具有较好的鲁棒性.把渐近跟踪作为系统同步的推广,从控制方法的角度设计一个混沌同步控制器,运用极点配置法求出控制器的增益参数并从控制理论上证明了该思路的可行性.通过对Lorenz系统的数值仿真试验,验证了该方法在控制混沌同步方面的有效性.为混沌控制中设计耐受性高的控制器提供了依据.     

不同阶分数阶混沌系统的同步与参数辨识

针对不确定分数阶混沌系统的同步和参数辨识问题,提出一种新的方法,即用不同阶分数阶系统来同步和参数辨识.利用主动控制和预控制量方法,基于分数阶混沌系统稳定性理论和自适应控制理论,设计控制器,实现不同阶分数阶混沌系统之间的同步和参数辨识.理论和仿真结果实现了不同阶Chen 系统间的同步和辨识,表明了该方法的有效性.     

Chen混沌系统的一种自适应同步方法

混沌系统的研究在国内外正在广泛的开展,如何使得对混沌系统的控制达到良好的控制效果构成了问题的关键.由于Chen混沌系统具有的参数不确定性,以至于常规的控制方法很难实现对Chen混沌系统的控制,讨论了一种参数可调节的自适应同步设计方法.设计出了可以使两个同结构的Chen系统状态渐近同步的自适应控制器,其参数调节律由Lyapunov稳定性理论来确定.最后进行数字仿真,仿真结果表明了这种方法的有效性和实用性.     

不确定混沌系统用分数阶系统同步与参数辨识

针对不确定整数阶混沌系统的同步和参数辨识问题,提出一种新的策略即用分数阶混沌系统来同步整数阶混沌系统并实现不确定参数的辨识。首先引入预控制量并利用主动控制构造同步误差方程,然后用分数阶混沌系统稳定性理论和自适应控制理论,设计同步控制器及参数的自适应率,最终实现整数阶混沌系统用分数阶混沌系统同步和参数辨识。数值仿真实现参数不确定整数阶Lorenz系统用分数阶Lorenz系统进行同步和参数辨识仿真,结果表明提出方法的有效性。     

基于参数自适应方法的统一混沌系统的同步控制

采用参数自适应控制方法，根据Lyapunov稳定性原理，通过构造适当的控制函数和设计参数的自适应控制律，分别实现了系统在不同确定参数和相同不确定参数两种情况下的统一混沌系统的同步导出在这两种情况下的统一混沌系统能实现同步的充分条件.相同不确定参数情况下的同步系统控制器结构更简单、同步性能更优．数值仿真证明了该方法的有效性．     

带扰动和未知参数混沌系统变量函数向量同步

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。     

含有非线性不确定参数的电液系统滑模自适应控制

针对含有非线性不确定参数的电液控制系统, 提出了一种滑模自适应控制方法. 该控制方法主要是为了解决由于初始控制容积的不确定性而引起的, 非线性不确定参数自适应律设计的难题. 其主要特点为, 通过定义一个新型的特Lyapunov 函数, 进而构建系统的自适应控制器及参数自适应律, 并结合滑模控制方法及一种简单的鲁棒设计方法, 给出整个电液系统的滑模自适应控制器, 及所有不确定参数的自适应律. 试验结果表明, 采用该控制方法能够取得良好的性能, 尤其可以补偿非线性不确定参数对系统的影响.     

An optimal adaptive robust PID controller subject to fuzzy rules and sliding modes for MIMO uncertain chaotic systems

In this paper, an optimal adaptive robust PID controller based on fuzzy rules and sliding modes is introduced to present a general scheme to control MIMO uncertain chaotic nonlinear systems. In this control scheme, the gains of the PID controller are updated by using an adaptive mechanism, fuzzy rules, the gradient search method, and the chain rule of differentiation in order to minimize the sliding surfaces of sliding mode control. More precisely, sliding mode control is used as a supervisory controller to provide sufficient control inputs and guarantee the stability of the control approach. To ascertain the parameters of the proposed controller and avoid trial and error, the multi-objective genetic algorithm is employed to augment the performance of proposed controller. The chaotic system of a Duffing-Holmes oscillator and an industrial robotic manipulator are the case studies to evaluate the performance of the proposed control approach. The obtained results of this study regarding both systems are compared with the outcomes of two notable studies in the literature. The results and analysis prove the efficiency of the proposed controller with regard to MIMO uncertain systems having challenging external disturbances in terms of stability, minimum tracking error and optimal control inputs.     

Graphical Robust PID Tuning Based on Uncertain Systems for Disturbance Rejection Satisfying Multiple Objectives

Tuning parameters of the PID controller which satisfying certain requirements is the key goal in uncertain systems. However, most studies ignored the disturbance rejection performance of the controller. This study investigated a novel graphical design method of improving disturbance rejection performance for uncertain system. The proposed method evaluates the disturbance rejection performance by analyzing reference to disturbance ratio (RDR). At the same time, the parameters of the controller which can stabilize the system and meet the robustness specification for the uncertain system are determined by specifications-oriented Kharitonov region (SOKR). Thus, the intersection region satisfying multiple objectives can be found by using this graphical method. Examples are given to demonstrate the flexibility and effectiveness of the proposed method.     

Intelligent adaptive control for MIMO uncertain nonlinear systems

This paper investigates an intelligent adaptive control system for multiple-input–multiple-output (MIMO) uncertain nonlinear systems. This control system is comprised of a recurrent-cerebellar-model-articulation-controller (RCMAC) and an auxiliary compensation controller. RCMAC is utilized to approximate a perfect controller, and the parameters of RCMAC are on-line tuned by the derived adaptive laws based on a Lyapunov function. The auxiliary compensation controller is designed to suppress the influence of residual approximation error between the perfect controller and RCMAC. Finally, two MIMO uncertain nonlinear systems, a mass–spring–damper mechanical system and a Chua’s chaotic circuit, are performed to verify the effectiveness of the proposed control scheme. The simulation results confirm that the proposed intelligent adaptive control system can achieve favorable tracking performance with desired robustness.     

Development of PI training algorithms for neuro-wavelet control on the synchronization of uncertain chaotic systems

This paper investigates a neuro-wavelet control (NWC) system to address the problem of synchronization control of uncertain chaotic systems. In this NWC system, a wavelet neural network (WNN) controller is the principal tracking controller designed to mimic the perfect control law and an auxiliary compensation controller is used to recover the residual approximation error so that the favorable synchronization can be achieved. Moreover, the proportional-integral (PI) training algorithms of the control system are derived from the Lyapunov stability theorem, which are utilized to update the adjustable parameters of WNN controller on-line for further assuring system stability and obtaining a fast convergence. In addition, to relax the requirement of unknown uncertainty bound, a bound estimation law is derived to estimate the uncertainty bound. Finally, some numerical simulations are presented to illustrate the effectiveness of the proposed control strategy. The simulation results demonstrate that the proposed NWC with PI training algorithms can synchronize the chaotic systems more accurately than the other control strategies.     

Robust Control System Design for an Uncertain Nonlinear System Using Minimax LQG Design Method

A systematic approach to design a nonlinear controller using minimax linear quadratic Gaussian regulator (LQG) control is proposed for a class of multi‐input multi‐output nonlinear uncertain systems. In this approach, a robust feedback linearization method and a notion of uncertain diffeomorphism are used to obtain an uncertain linearized model for the corresponding uncertain nonlinear system. A robust minimax LQG controller is then proposed for reference command tracking and stabilization of the nonlinear system in the presence of uncertain parameters. The uncertainties are assumed to satisfy a certain integral quadratic constraint condition. In this method, conventional feedback linearization is used to cancel nominal nonlinear terms and the uncertain nonlinear terms are linearized in a robust way. To demonstrate the effectiveness of the proposed approach, a minimax LQG‐based robust controller is designed for a nonlinear uncertain model of an air‐breathing hypersonic flight vehicle (AHFV) with flexibility and input coupling. Here, the problem of constructing a guaranteed cost controller which minimizes a guaranteed cost bound has been considered and the tracking of velocity and altitude is achieved under inertial and aerodynamic uncertainties.     

基于非线性参数的电液伺服系统滑模控制

针对在电液伺服系统跟踪控制中存在非线性不确定参数和外界扰动的问题,提出了一种基于积分微分器的滑模Lyapunov函数的控制方法。首先,在只有位移信号测量输出的情况下,采用高阶积分链式微分器对其速度和加速度信息进行预估。系统存在非线性不确定参数,利用微分器对状态和不确定项的实时估计,设计出积分滑模控制器,实现自适应规律以及对电液伺服系统中不确定扰动的抑制。搭建电液伺服系统AMESim模型并与Matlab构成联合仿真平台,对控制器进行仿真。仿真表明,该控制器具有良好的对非线性不确定参数变化的补偿能力和跟踪性能。