基于DHNN的移动域控制策略及应用

为避免基于Riccati方程求解移动域控制问题时复杂的矩阵求逆运算,提出一种基于离散Hopfield网络(DHNN)的移动域控制策略.对每个离散时刻,通过建立DHNN能量函数与移动域线性二次(LQ)性能指标间的等价关系,在线构建相应时刻的DHNN,理论设计能够保证该网络具有稳定性,而且由其稳态输出可获得移动域控制输入.应用于倒立摆平衡控制的仿真实验说明了论文提出的移动域控制策略的正确性及与滚动优化思想相结合实现无限域闭环最优控制的可行性.

Receding Horizon Control Strategy Based on Discrete Hopfield Neural Network and Its Application

To avoid the complex computation of inverse matrix with Riccati Eq.for solving receding horizon con- trol(RHC)problem,this paper develops a RHC strategy based on discrete Hopfield neural network(DHNN).For every discrete time,a DHNN can be constructed online by establishing the equivalent relation between the energy function of DHNN and the performance index of RHC.The theoretical design guarantees the stability of DHNN,and the RHC input is obtained directly from the stable outputs of DHNN.The simulation experiment in balancing control of inverted pendulum shows that the proposed RHC strategy is correct,and the realization of infinite horizon closed- loop optimal control is feasible by integrating with rolling optimization idea.