有关模糊控制器的设计 - 控制工程 非线性系统含糊系统自适应控制不确定系统自适应含糊控制 有关含糊控制器的设计 摘要 5-7 Abstract 7-8 第1章绪论 11-19 1.1含糊控制概述 11-13 1.1.1含糊控制的研究背景 11-12 1.1.2含糊控制主要研究方向 12-13 1.2含糊控制理论开展 13-15 1.2.1一般含糊控制器 14 1.2.2一般自适应含糊控制器 14-15 1.3国内外研究现状 15-17 1.4当前含糊控制需要研究的问题 17-18 1.5本论文的内容及结构安顿 18-19 第2章含糊控制的数学根底 19-27 2.1根本概念 19-20 2.2含糊控制的根本原理 20-25 2.2.1含糊化接口 21-22 2.2.2含糊规那么库 22 2.2.3含糊推理积 22-23 2.2.4解含糊化接口 23-25 2.3典型的含糊系统 25-27 2.3.1纯含糊逻辑系统 25 2.3.2TSK含糊逻辑系统 25 2.3.3基于含糊产生器和含糊打消器的含糊逻辑系统 25-27 第3章SISO非线性系统的自适应含糊H_∞跟踪控制 27-45 3.1引言 27-30 3.2问题描述 30-32 3.3控制器及观测器的设计 32-36 3.3.1鲁棒自适应含糊控制器的设计 32-34 3.3.2观测器的设计 34-36 3.4稳定性与性能分析 36-42 3.5仿真实例 42-43 3.6本章小结 43-45 第4章MIMO非线性系统自适应含糊控制 45-61 4.1引言 45-46 4.2问题描述 46-49 4.3含糊控制器及观测器的设计 49-51 4.3.1含糊控制器的设计 49-50 4.3.2观测器的设计 50-51 4.4稳定性及性能分析 51-57 4.5仿真算例 57-59 4.6本章小结 59-61 第5章总结与展望 61-63 5.1本文的主要研究结果 61 5.2需要进一步研究的问题 61-63 参考文献 63-69 致谢 69 【摘要】 近年来,作为控制理论研究热点之一的非线性系统控制理论得到了长足的开展,尤其是微分几何办法的引入,使得非线性系统控制理论得到了很大的飞跃.复杂工业过程常常具有强非线性、不确定性、多变量、强耦合等特点,动态特性难于用精确的数学模型描述.非线性系统的含糊建模与自适应控制的根本出发点是仿人的智能以实现对复杂不确定性系统进行有效的控制,它具有从环境自学习、适应环境的能力,自动进行信息处理以减少其不确定性,能规划、产生并能平安、可靠地执行控制作用.另外含糊控制技术具有控制器设计简便,适用于许多非线性系统并且具有鲁棒性强等特点,20世纪80年代以来在控制理论和项目实践方面获得了巨大的开展.实际中,被控对象的数学模型往往很难精确得到的.具有含糊IF-THEN规那么集的含糊系统在给定的紧集内能一致逼近任意非线性不确定连续函数到任意精度.近年来,由于含糊系统理论不需要精确的数学模型并且可以有效地利用专家知识,从而成功地应用于许多控制问题中.另外,近年来自适应含糊控制的研究得到迅速开展.本文针对一类不确定非线性系统提出基于观测器的自适应含糊控制办法.主要内容分为两个局部：第一局部针对一类具有扰动的SISO非线性系统,设计状态观测器来估计系统的不可测状态,利用H∞鲁棒控制理论和含糊系统是万能逼近器的特点,提出一种间接型鲁棒自适应含糊控制设计办法,利用李雅普诺夫第二办法,证明闭环控制系统状态是有界的和跟踪误差减到指定的水平度.论文的主要结果：(1)该算法不需要若逼近误差的界限已知条件,也不需要假定系统状态是完全可测的,只是若逼近误差和系统的外扰有界但未知.给出的自适应律只是对逼近误差的不确定界进行自适应调节,从而大大地减少了计算量；(2)该算法讨论了基于状态设计的观测器和基于跟踪误差设计的观测器之间可以相互转化,设计的参数自适应律简便而且有界,最终使不确定非线性系统到达H∞性能指标来减少外扰及逼近误差对系统跟踪误差的影响.第二局部针对一类具有扰动的MMIO不确定非线性系统,设计状态观测器来估计系统的不可测状态,提出一种间接自适应鲁棒含糊控制办法.通过鲁棒控制项来补偿函数逼近误差以及外部干扰对跟踪误差的影响.针对现有的自适应含糊控制器的参数自适应律仅由跟踪误差进行调节从而导致了系统的跟踪性能收敛过慢的现状.第二局部针对状态不完全可测的系统,讨论自适应含糊控制器的参数自适应律由观测误差和逼近误差共同进行调节,并从理论分析和仿真角度证明了该办法比参数自适应律仅用跟踪误差进行调节的控制器具有更好的跟踪效果,在最优逼近误差满足平方可积的情况下,这样设计不仅能够使观测误差收敛到零而且能使系统的建模误差收敛到零,也就是说自适应参数收敛到最优,从而能到达系统所要求的最优控制. 【Abstract】 As an active research field, the nonlinear system theory made a rapid progress recently, especially in introducing differential geometry, which plays main important role in nonlinear system theory. The complex industry processes in varying operation conditions are often nonlinear and multi variable with uncertainties and strong coupling. So the exact mathematical model can not be determined with case. The foundation of fuzzy modeling and adaptive control of nonlinear systems is of artificial intelligence, which has the abilities such as self-studying and adaptive ability, automatic information processing ability to abate uncertainties and the programming ability to reliably complete control and can achieve effective control of the complex systems. Furthermore, the controller designed is easy in fuzzy control techniques, which is the same with many nonlinear systems and has strong robust characteristic. Since 80’s 20th century, the fuzzy control obtains great development in control theory and engineering. In practice, it is very difficult to get the precise mathematical model from the traditional modeling method. Fuzzy systems with a collection of fuzzy IF-THEN rules are capable of approximating any real continous function on a compact set with arbitrary accuracy. Recently, fuzzy systems are successfully applied to many control problems because they need not accurate mathematical model of the system and can cooperate with human experts, knowledge. In addition, the recent study of adaptive fuzzy control has developed quickly. In many design problems, all states of systems are supposed to be available for measurement.The robust indirect adaptive fuzzy control methods are proposed for a class of nonlinear systems 12 非线性系统含糊系统自适应控制不确定系统自适应含糊控制 based on observer in this paper. The main content has two parts:In the first part, for a class of nonlinear system with disturbances, we design the state observer to estimate the unknown state and advance the scheme of robust indirect adaptive fuzzy making use of the H∞control theory and the characteristic of fuzzy logic is universal approximation. Finally, we prove that the states of the closed loop systems are uniformly bounded and the tracking error is attenuated to an arbitratily desired level via H∞tracking design technique. The main results are that (1) http://www.51lunwen.org/kzgc/2022/0306/lw202203060843555904.html It is not required to assume that estimation error has a known boundary or satisfies square integral conditions and even it is not required that the states of the system are full observable. It is supposed that the boundary of estimation error and external disturbance are unknown. The online computational burden is greatly reduced since only uncertainty bounds are tuned online. (2) In the first part, we discuss the state observer can transform into tracking error observer and the parameters of adaptive law designed is simple but also bounded. The effect that function approximation error and the external disturbances have on the tracking error is compensated by means of the robust conortller designed. The presented scheme guarantees that H∞tracking performance is aehieved.In the second part, an adaptive robust fuzzy control method is proposed for a class of uncertain MIMO nonlinear systems with disturbances. we design the state observer to estimate the unknown state. The effect that function approximation error and the external disturbances have on the tracking error is compensated by means of the robust controller designed. For the case that the parameter adjustment of adaptive fuzzy control uses only the tracking error and leads to the low convergence rate of the tracking. The second part the adaptive law utilizes the tracking error and approximation error in the adaptive fuzzy control system. And the theory analysis and 12 。