不确定非线性组合系统基于神经网络的鲁棒控制

Robust Control for Uncertain Nonlinear Composite Systems Based on Neural Networks

针对不确定非线性组合系统,基于神经网络提出了一种新的鲁棒控制器设计方法·利用神经网络逼近系统的未知扰动和互联项·首先考虑不确定非线性组合系统的标称系统并且设计相应的标称控制器;其次考虑系统的未知扰动和互连项,设计了校正控制信号并把它加入了标称控制器中,这种设计方法可以保证实际系统具有最终一致有界的特性·控制信号是光滑的且不需要预先知道神经网络连接权或模型误差的上界·最后给出一个数值的例子,仿真结果表明该方法的有效性·

Based on neural networks, a new robust control methodology is presented for nonlinear uncertain composite systems of which the nonlinearities are assumed unknown. The unknown disturbance and interconnected terms are approximated using neural networks. The nominal system is considered to develop a nominal controller. Then, the unknown disturbance and interconnected terms are taken into account to design correction control signals and add them to the nominal controller, thus the actual system is guaranteed to be uniformly ultimately bounded. In this way the control signals are smooth without the requirement for knowing the upper bounds on the optimal weight values and modeling error in advance. Numerical simulation studies are used to illustrate and clarify the approach.