IEEE Trans Neural Netw Learn Syst. 2013 Jul;24(7):1150-6. doi: 10.1109/TNNLS.2013.2249668.
This brief presents a novel framework of robust adaptive dynamic programming (robust-ADP) aimed at computing globally stabilizing and suboptimal control policies in the presence of dynamic uncertainties. A key strategy is to integrate ADP theory with techniques in modern nonlinear control with a unique objective of filling up a gap in the past literature of ADP without taking into account dynamic uncertainties. Neither the system dynamics nor the system order are required to be precisely known. As an illustrative example, the computational algorithm is applied to the controller design of a two-machine power system.
本简介提出了一种新的鲁棒自适应动态规划(robust-ADP)框架,旨在计算存在动态不确定性时的全局稳定和次优控制策略。一个关键策略是将 ADP 理论与现代非线性控制技术相结合,其独特的目标是填补过去 ADP 文献中不考虑动态不确定性的空白。既不需要精确知道系统动力学也不需要精确知道系统阶数。作为一个说明性示例,该计算算法被应用于两机电力系统的控制器设计。