Parallel Control for Robust Optimal Tracking via Adaptive Dynamic Programming

This paper attempts to develop a novel robust optimal tracking control method for continuous-time uncertain nonlinear systems via adaptive dynamic programming (ADP). First, a control system for the actual system is established based on the parallel control scheme, so that the general nonlinear system can be transformed into an affine system to introduce the optimal tracking control problem by defining an augmented vector. Then, the main objective of this paper is to investigate the relationship between the solutions of the optimal control problems for the uncertain system and the nominal system. Furthermore, critic neural networks (NNs) are utilized to design the virtual control law to achieve the proposed robust optimal control online. Finally, simulation experiments validate the effectiveness of the proposed method.