﻿ 基于模糊神经网络的MIMO系统自适应解耦控制
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Adaptive decoupling control of a MIMO system based on fuzzy neural networks
BAI Chen, FAN Yao, REN Zhang, YANG Peng
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
Abstract: According to the control problem of a class of uncertain multiple-input multiple-output (MIMO) nonlinear systems, an adaptive decoupling control approach based on fuzzy neural networks was proposed. Firstly, a sub-channel decoupling control law of MIMO nonlinear systems was designed using decentralized control theory and feedback linearization approach. Secondly, the approximation of the system coupling terms and uncertainty terms were obtained by a fuzzy neural networks observer and compensated into the control law as compensation signal. It was proved that the control law, the observer and the weighted vector adaptive law could guarantee the uniform convergence of the errors of the output variable, the observer variable and the weighted vector finally. Simulations were carried on a typical uncertain MIMO system. The proposed method was compared with a traditional output feedback control method without adding compensation control signal. The simulation results show that the influence caused by coupling among the channels and uncertainty is eliminated by the compensation control and the observer errors can converge. The results validate the effectiveness and stability of the proposed control approach.
Key words: multiple-input multiple-output systems     fuzzy neural networks     adaptive     decoupling control     uncertainty

1 问题描述

2 主要结果 2.1 解耦控制

i个输出变量设计系统的期望动态为

Yi=[yi yi(1)yi(ri-1)]T,把控制律式(7)代入式(4)可得

2.2 模糊神经网络

2.3 基于模糊神经网络的自适应解耦控制

piPi的最后一列,另定义

 图 1 闭环系统结构 Fig. 1 Closed-loop system structure

3 仿真结果

 图 2 x1控制效果 Fig. 2 Control performance of x1

 图 3 x3控制效果 Fig. 3 Control performance of x3

 图 4 模糊神经网络观测误差 Fig. 4 Fuzzy neural networks observer errors

4 结 论

1) 基于Tornambe分散控制思想,结合反馈线性化方法,给出了输出方程形式更为一般情况下,MIMO非线性系统的分通道解耦控制律.

2) 结合模糊系统的非线性泛逼近能力和神经网络的自学习能力,通过观测器方法给出了通道耦合和不确定性的估计值,并作为补偿信号加入到解耦控制律中,消除了其对系统的影响.

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#### 文章信息

BAI Chen, FAN Yao, REN Zhang, YANG Peng

Adaptive decoupling control of a MIMO system based on fuzzy neural networks

Journal of Beijing University of Aeronautics and Astronsutics, 2015, 41(11): 2131-2136.
http://dx.doi.org/10.13700/j.bh.1001-5965.2014.0758