非线性系统的神经网络学习控制
LEARNING CONTROL FOR NONLINEAR SYSTEMS USING NEURAL NETWORKS
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摘要: 主要研究了一类非线性系统的神经网络学习控制问题.讨论了以迭代学习方式训练的神经网络学习控制器,在满足一定条件时,可以实现一定时间内的系统输出跟踪.当系统的每次操作时间较长时,给出了一种新的训练加权的方法,不仅能减小计算量,且收敛速度快.Abstract: In this paper, an iterative learning controller using neural networks is presented for a class of nonlinear systems. It is discussed that the proposed controller scheme for nonlinear systems can achieve the desired trajectory tracking after several trials. In addition, the improved algorithm is employed in neural networks, resulting in lower computation of burden and faster convergence of learning.