基于T-S模糊双曲正切模型的非线性系统控制

发布时间：2018-05-23 18:03

本文选题：随机T-S模糊双曲正切模型 + 软约束控制　；参考：《西安电子科技大学》2015年硕士论文

【摘要】：模糊逻辑系统利用模糊集合和模糊推理方法处理难以用数学工具精确描述的不确定信息,对研究复杂非线性系统具有很大的突破。由此形成的模糊控制是研究非线性系统的重要方法。目前,基于0#1#(1)模糊模型的控制理论包括1模糊线性模型,1模糊双线性模型,1模糊非线性模型。除此之外,在1随机模糊系统,1模糊采样控制以及保性能控制方面取得了可观的研究成果。本文主要基于1模糊双曲正切系统,根据-(+稳定性定理,补定理,线性矩阵不等式(-$)和非脆弱保性能控制理论,分别利用1随机模糊双曲正切模型和1采样模糊双曲正切模型深入研究非线性系统。主要工作总结如下:1.针对连续的非线性系统,提出1随机模糊双曲正切系统模型,该模型的后件部分为模糊双曲正切动态模型。首先,利用/'算法设计1随机模糊双曲正切系统的模糊双曲正切控制器,以-$形式给出闭环系统稳定的充分条件。其次,结合1模糊输出反馈控制器分析1随机模糊双曲正切系统的输出反馈控制的稳定性条件。最后,将该模型推广到1不确定系统。相比其他1模糊模型,该模型的主要优点在于具有较小的控制振幅,可以达到“软”约束的控制效果。2.针对连续时间1模糊双曲正切模型表示的非线性系统,研究具有时变采样方式的非线性系统的非脆弱保性能控制。考虑有约束控制输入的情形,给出一个新的引理来得到采样模糊控制系统的隶属函数偏差界,并建立偏差界和时变采样区间上界之间的定量关系。然后,提出一种采样模糊控制器设计的隶属函数偏差方法,并以-$形式给出采样模糊控制器存在隶属函数偏差的条件。除此之外,将该方法推广到非脆弱保性能控制,确定稳定性条件。最后,用两个例子证明所提的隶属函数偏差方法可以降低现有采样模糊控制设计结果的保守性。
[Abstract]:Fuzzy logic systems use fuzzy sets and fuzzy reasoning methods to deal with uncertain information which cannot be accurately described by mathematical tools, which is a great breakthrough in the study of complex nonlinear systems. The resulting fuzzy control is an important method for the study of nonlinear systems. At present, the control theory based on #1 #1) fuzzy model includes 1 fuzzy linear model, 1 fuzzy bilinear model and 1 fuzzy nonlinear model. In addition, considerable research results have been obtained in the field of fuzzy sampling control and guaranteed cost control for 1 stochastic fuzzy system. This paper is mainly based on 1 fuzzy hyperbolic tangent system, according to-(stability theorem, complement theorem, linear matrix inequality) and non-fragile guaranteed cost control theory. 1 random fuzzy hyperbolic tangent model and 1 sampling fuzzy hyperbolic tangent model are used to study the nonlinear system. The main work is summarized as follows: 1. A stochastic fuzzy hyperbolic tangent system model is proposed for continuous nonlinear systems. The latter part of the model is a fuzzy hyperbolic tangent dynamic model. Firstly, a fuzzy hyperbolic tangent controller for random fuzzy hyperbolic tangent systems is designed by using the r 'algorithm. A sufficient condition for the stability of the closed-loop system is given in the form of -$. Secondly, the stability condition of output feedback control for random fuzzy hyperbolic tangent system is analyzed by using 1 fuzzy output feedback controller. Finally, the model is extended to 1 uncertain system. Compared with other 1 fuzzy models, the main advantage of this model is that it has smaller control amplitude and can achieve the control effect of "soft" constraint. For nonlinear systems with continuous time 1 fuzzy hyperbolic tangent model, the nonfragile guaranteed cost control for nonlinear systems with time-varying sampling mode is studied. In this paper, a new Lemma is given to obtain the deviation bound of membership function of the sampled fuzzy control system, and the quantitative relationship between the deviation bound and the upper bound of time-varying sampling interval is established. Then, a membership function deviation method for the design of sampled fuzzy controller is proposed, and the condition for the existence of membership function deviation of the sampled fuzzy controller is given in the form of -$. In addition, the method is extended to non-fragile guaranteed cost control and stability conditions are determined. Finally, two examples are given to prove that the proposed membership function deviation method can reduce the conservatism of the design results of sampling fuzzy control.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：O231

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