一类不确定非线性离散系统的模糊自适应控制器设计

针对一类不确定非线性离散系统,提出一种带有自动可调伸缩因子的模糊自适应控制方法.该控制器设计方法的优点是模糊逻辑系统的逼近精度不再依赖于模糊逻辑系统的结构和规则数目,参数自适应律调节与被逼近函数的特征和逼近精度有关,因此能有效减少在线估计的参数数目,且设计方法能够保证闭环系统的所有状态半全局一致终极有界.最后,通过数值仿真算例表明所提出方法的有效性.     

基于自适应模糊逻辑系统的一类混沌系统同步控制

针对一类带有未知函数和干扰的混沌系统,进行了基于自适应模糊逻辑系统的自适应同步控制器的设计。首先基于模糊逼近原理,通过对该混沌系统中未知函数的输入输出进行采样,根据采样数据信息设计出具有参数自适应功能的Mamdani型模糊逻辑系统;然后利用该模糊逻辑系统给出一种带有参数自适应的驱动响应同步控制器设计方法;最后通过数值仿真算例表明了该方法的有效性。     

基于分变量模糊蕴涵关系的无规则模糊逻辑系统的自适应控制应用

常用的基于模糊if-then规则的模糊逻辑系统在进行控制设计应用时常会遇到规则爆炸问题,为此,提出了一种新的无规则模糊逻辑系统。首先利用从属于系统各分变量论域上开覆盖的单位分解,将模糊知识库中的专家模糊语言值信息进行整合,得到相应的分变量模糊蕴涵关系,再由模糊推理及解模糊化得到系统输出;然后,针对一类非线性不确定系统,先利用伸缩器和饱和器构造出扩展的无规则模糊逻辑系统,再设计被控系统的自适应稳定控制器;最后通过仿真算例验证了该方法的有效性。这种方法的优越性在于新的模糊逻辑系统的构造与自适应律的设计是分离的,在线估计的参数数目明显减少,有效地解决了规则爆炸问题。     

基于遗传算法的广义Takagi-Sugeno模糊逻辑系统最优参数辨识

针对Takagi-Sugeno模糊逻辑系统的隶属函数不具有自适应性且模糊规则数的确定 带有很大的人为主观性,这里引入了一类广义Takagi-Sugeno模糊逻辑系统;在模型实现上，以 广义Takagi-Sugeno模型为个体,采用简单、有效的矩阵编码方式,借助遗传算法得到一个次优 的广义Takagi-Sugeno模糊系统模型,该模型不仅能很好地逼近所要辨识的非线性系统,而且 还具有较低的复杂度.仿真结果表明了广义Takagi-Sugeno模型及其参数辨识方法的正确性和 有效性.     

非线性离散时间系统的自适应模糊补偿控制

针对一类非线性离散时间系统,提出一种自适应模糊逻辑补偿控制方案.控制律由跟踪控制律和逼近误差补偿控制律两部分组成,利用模糊逻辑系统对系统参数扰动和外界干扰进行自适应补偿,由模糊滑模控制律实现对模糊逻辑系统逼近误差的进一步补偿.所设计的控制器可保证闭环系统一致最终有界.将该控制器用于月球探测车动态转向系统中,仿真结果表明了该方法的有效性.     

一类多变量非线性系统的自适应模糊控制

对一类不确定多变量非线性系统提出了自适应模糊控制方法.该方法采用模糊逻辑系统组成的矩阵逼近控制器中的逆矩阵以避免控制器的奇异性问题,同时用误差补偿项对模糊逻辑系统的逼近误差进行补偿.证明该方法不但能使闭环系统的所有信号有界,而且通过适当调整控制器及自适应律中设计参数,可使跟踪误差收敛到原点的小邻域内.仿真结果验证了方法的有效性.     

一类严格反馈非线性系统的间接自适应模糊控制

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．     

一类非线性系统的广义模糊双曲正切模型自适应控制器设计

针对一类非线性系统的稳定控制器设计问题, 根据广义模糊双曲正切模型的万能逼近性质, 提出一种带有可调参数的广义模糊双曲正切模型的自适应控制器设计方法. 该设计方法的优点是使得自适应律的个数不依赖于广义模糊双曲正切模型的线性基函数的输出形式, 可以有效减少在线估计的参数数目, 并且能够保证被控系统的状态一致终极有界. 最后通过数值算例表明了所提出的设计方法的有效性.

     

一类复杂控制系统分散自适应鲁棒控制器设计

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.     

一类复杂非线性系统的模糊控制

针对一类复杂非线性系统,把模糊T-S模型和自适应模糊逻辑系统结合起来,提出了一种跟踪控制方案.首先,应用模糊T-S模型对非线性系统建模,设计观测器用来观测系统状态:其次,应用基于权值、中心和宽度3个参数可调节的自适应时延模糊逻辑系统补偿器来消除建模误差和小确定性.文中证明了闭环系统满足期望的跟踪性能.示例仿真结果表明了该方案的有效性.     

Adaptive fuzzy dynamic surface control for uncertain nonlinear systems in pure-feedback form with input and state constraints using noisy measurements

This paper is concerned with the design of an adaptive fuzzy dynamic surface control for uncertain nonlinear pure-feedback systems with input and state constraints using a set of noisy measurements. The design approach is described as follows. The nonlinear uncertainties are approximated by using the fuzzy logic systems at the first stage, secondly the adaptive fuzzy dynamic surface control is introduced to remove the problem of the explosion of complexity for the derivation of the adaptive fuzzy backstepping control, thirdly a new saturation function for state constraints is proposed to design the controllers based on the Lyapunov function, fourthly the number of the adjustable parameters is reduced by using the simplified extended single input rule modules, and finally the weighted least squares estimator to take the estimates for the un-measurable states and the adjustable parameters is in a simplified structure designed. The proposed approach provides effective system performance in the simulation experiment.     

Adaptive fuzzy dynamic surface control for a class of stochastic MIMO discrete-time nonlinear pure-feedback systems with full state constraints

This paper presents the design of an adaptive fuzzy dynamic surface control for a class of stochastic MIMO discrete-time nonlinear pure-feedback systems with full state constraints using a set of noisy measurements. The design approach is described as follows. The nonlinear uncertainty is approximated by using the fuzzy logic system at the first stage, secondly the proposed adaptive fuzzy dynamic surface control is designed based on a new saturation function for full state constraints, thirdly the number of the adjustable parameters is reduced by using the simplified extended single input rule modules, and finally the simplified weighted least squares estimator is in a simplified structure designed to take the estimates for the un-measurable states and the adjustable parameters. The simulation provides that the proposed approach is effective for the improvement of the system performance.     

Adaptive control design for a class of nonlinear systems based on fuzzy logic systems with scalers and saturators

Many practical engineering applications require various types of fuzzy logic systems (FLSs) to design adaptive controllers for nonlinear systems with uncertainties. In this article, we will consider a fundamental theoretical question: is it possible to find a unified adaptive control design method suited to various types of FLSs? In order to solve this problem, we will introduce scalers and saturators at the input and output terminals of FLSs to form the extended FLSs (EFLS). The scalers and saturators have adjustable parameters. By designing the updated laws of these parameters and the estimate values of the fuzzy approximate accuracies, stable adaptive fuzzy controllers can be realised for a class of nonlinear systems with unknown homogeneous drift functions and gains. The proposed design method is only dependent on the outputs of EFLS and the above updated laws, thus increasing its adaptability. The fuzzy control scheme introduced in this article is suitable for all fuzzy systems with or without fuzzy rules. Simulations will also be used to show the validity of the method proposed in this article.     

Analysis of stability and robust stability of polynomial fuzzy model-based control systems using a sum-of-squares approach

The well known Takagi–Sugeno (T–S) fuzzy model can be extended in different ways including the polynomial fuzzy model, whose consequent parts are polynomial sub-systems. Compared with the traditional T–S fuzzy model, the polynomial fuzzy model can represent a nonlinear system more accurately with a smaller number of fuzzy logic rules. It is worth emphasizing that the stability analysis and controller design of polynomial fuzzy model-based (PFMB) control systems are not based on the linear matrix inequalities but the recently developed sum-of-squares decompositions. In this paper, based on an existing result for traditional fuzzy control systems, we propose a new stability condition for the stability analysis of PFMB control systems. Furthermore, the stability of PFMB control systems with parameter uncertainties is investigated. The popular inverted pendulum and an unstable nonlinear system are employed to demonstrate the quality of the proposed stability conditions.     

Adaptive fuzzy control with compressors and limiters for a class of uncertain nonlinear systems

This paper proposes a novel adaptive fuzzy control design for a class of nonlinear uncertain systems. The definition of compressor and limiter with adjustable parameters is introduced at beginning, and then updated laws of parameters of the compressor and estimate values of fuzzy approximation accuracies are utilized to synthesize stable adaptive controllers. The most advantage of designing adaptive fuzzy controller is neglectful of the logic structure of fuzzy logic systems, which make designer focus on parameters of the compressor, limiter and fuzzy approximation accuracies. This adaptive fuzzy control method can not only reduce the number of on-line updated parameters but also guarantee states of the closed-loop system to be uniformly ultimately bounded (UUB). Simulation results demonstrate the effectiveness of the control scheme in this paper.     

基于跟踪误差调节的非线性自适应模糊预测控制

将模糊逻辑系统引入预测控制，对一类非线性离散系统提出了直接自适应模糊预测控制的方法，此方法首先建立被控对象的预测模型;然后基于此模型直接利用模糊逻辑系统设计预测控制器，并基于跟踪误差对控制器参数中的未知向量进行自适应调整;最后证明了此方法可使跟踪误差收敛到原点的一个小邻域内。     

多输入–多输出非线性系统的特征模型及在挠性卫星姿态控制中的应用

研究多输入–多输出（MIMO）高阶非仿射非线性系统的特征建模问题.首先证明了MIMO高阶非仿射非线性系统的特征模型可用二阶时变差分方程组描述,并给出了特征模型的建模误差.然后设计了基于特征模型的自适应模糊广义预测控制器,利用Lyapunov方法分析了闭环系统的稳定性.由于控制结构中使用了分层模糊逻辑系统,从而极大减少了模糊规则和可调参数的个数,提高了控制的实时性.通过对挠性卫星姿态控制的仿真研究验证了所给控制方案的有效性,可实现高精度的姿态控制,且该方法具有较强的鲁棒性.     

Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation

In this paper, a novel direct adaptive fuzzy control approach is presented for uncertain nonlinear systems in the presence of input saturation. Fuzzy logic systems are directly used to tackle unknown nonlinear functions, and the adaptive fuzzy tracking controller is constructed by using the backstepping recursive design techniques. To overcome the problem of input saturation, a new auxiliary design system and Nussbaum gain functions are incorporated into the control scheme, respectively. It is proved 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 tracking error converges to a small neighborhood of the origin. A simulation example is included to illustrate the effectiveness of the proposed approach. Two key advantages of the scheme are that (i) the direct adaptive fuzzy control method is proposed for uncertain nonlinear system with input saturation by using Nussbaum function technique and (ii) The number of the online adaptive learning parameters is reduced.     

Adaptive fuzzy tracking control of nonlinear time-delay systems with unknown virtual control coefficients

In this paper, a novel adaptive fuzzy control scheme is proposed for a class of uncertain single-input and single-output (SISO) nonlinear time-delay systems with the lower triangular form. Fuzzy logic systems are used to approximate unknown nonlinear functions, then the adaptive fuzzy tracking controller is constructed by combining Lyapunov-Krasovskii functionals and the backstepping approach. The proposed controller guarantees uniform ultimate boundedness of all the signals in the closed-loop system, while the tracking error converges to a small neighborhood of the origin. An advantage of the proposed control scheme lies in that the number of adaptive parameters is not more than the order of the systems under consideration. Finally, simulation studies are given to demonstrate the effectiveness of the proposed design scheme.