摘要
应用自适应梯度算法和自适应动态规划方法,在线求解非线性系统的最优跟踪控制。首先对所求非线性系统给定性能指标,其次根据系统和性能指标建立哈密尔顿函数,再用神经网络逼近性能指标,然后用另一个神经网络逼近近似最优控制,神经网络权重参数应用自适应梯度算法在线进行估计,最后基于所求结果以及所设计的稳态控制和鲁棒项,求得系统鲁棒最优跟踪控制,对参数收敛性和系统稳定性进行了详细分析。仿真结果表明了本文所提出方法的有效性。
Based on the gradient estimation algorithm and adaptive dynamic programming, this paper solved the optimal control problem online. At first, regarding to the nonlinear system, a performance index was proposed. Then a Hamiltonian（HJB） function was constructed and a neural network（NN） was used to approximate the performance index. Another neural network was proposed to approach the actor, and both critic and actor NN weights are estimated based on gradient estimation online and simultaneously. Furthermore, steady-state control and robust term were designed to obtain the robust optimal control. At last, simulation results proved the effectiveness of the proposed methods.
出处
《计算机与现代化》
2016年第12期34-37,共4页
Computer and Modernization
关键词
自适应动态规划
梯度估计
跟踪控制
最优控制
Adaptive Dynamic Program（ADP）
gradient algorithm
tracking control
optimal control
