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针对一类具有不确定性的多输入多输出(MIMO)非线性系统控制问题,提出了基于模糊神经网络的自适应解耦控制方法.根据分散控制理论和反馈线性化方法设计了MIMO非线性系统的分通道解耦控制律,然后把通道耦合项和不确定性项归结为总的系统扰动项,利用模糊神经网络观测器得到其估计值,并作为补偿信号加入到解耦控制律中.证明了所设计的解耦控制律、模糊神经网络观测器以及模糊神经网络权值向量自适应律可以保证控制误差、扰动估计误差和权值向量误差一致最终收敛.仿真中将本文的方法与传统的输出反馈控制律进行了对比,结果表明加入的补偿控制信号消除了通道耦合和不确定性带来的不利影响,验证了该方法的有效性和稳定性.
Aiming at the control problem of a class of uncertain multiple input multiple output (MIMO) nonlinear systems, an adaptive decoupling control method based on fuzzy neural network is proposed. According to decentralized control theory and feedback linearization method, a MIMO nonlinear system Then the channel coupling term and the uncertainty term are reduced to the total system perturbation term, and the estimated value is obtained by the fuzzy neural network observer and added into the decoupling control law as the compensation signal. The designed decoupling control law, the fuzzy neural network observer and the fuzzy neural network weight vector adaptive law can ensure that the control error, the disturbance estimation error and the weight vector error converge and eventually converge. In the simulation, the method in this paper is compared with the traditional Output feedback control law. The results show that the added compensation control signal eliminates the adverse effects of channel coupling and uncertainty, and verifies the effectiveness and stability of the proposed method.