本文将基于模型的策略迭代方法推广到了分布式时滞系统的线性二次最优控制问题(LQR)的求解,证明了由该迭代方法得到的性能指标是递减的,且控制器收敛于最优控制器。This paper extends the model-based policy iteration method to the ...本文将基于模型的策略迭代方法推广到了分布式时滞系统的线性二次最优控制问题(LQR)的求解,证明了由该迭代方法得到的性能指标是递减的,且控制器收敛于最优控制器。This paper extends the model-based policy iteration method to the solution of the Linear Quadratic Regulator (LQR) problem for distributed delayed systems. It is demonstrated that the performance criterion obtained through this iterative method is monotonically decreasing, and the controller converges to the optimal controller.展开更多
文摘本文将基于模型的策略迭代方法推广到了分布式时滞系统的线性二次最优控制问题(LQR)的求解,证明了由该迭代方法得到的性能指标是递减的,且控制器收敛于最优控制器。This paper extends the model-based policy iteration method to the solution of the Linear Quadratic Regulator (LQR) problem for distributed delayed systems. It is demonstrated that the performance criterion obtained through this iterative method is monotonically decreasing, and the controller converges to the optimal controller.
