Robust Control of Uncertain Nonlinear Systems Based on Adaptive Dynamic Programming

摘要

In this paper, we propose a new approach to address robust control problem of nonlinear systems with uncertainties based on an adaptive dynamic programming (ADP) algorithm. After reformulating the robust control problem as an optimal control problem, we propose a modified ADP method to solve the derived Hamilton-Jacobi-Bellman (HJB) equation, where the optimal cost function is approximated by online training a critic neural network (NN). Then the approximated optimal control action can be derived to guarantee the stability of the controlled system with uncertainties. The closed-loop system stability and convergence have been proved. A simulation example is provided to illustrate the effectiveness of the method.