Output constrained adaptive dynamic programming for continuous-time nonlinear systems
Jingjing Yang, Jingjia Chen, Bo Fan, Qinmin Yang · 2017
This study presents a novel adaptive dynamic programming (ADP) based strategy for the optimal control of a class of continuous-time unknown nonlinear systems with output-constraints. Our contribution includes a step forward beyond the usual optimal control result to show that the output of the plant is always within pre-defined bounds, which can finds numerous applications in renewable energy control and integration, power flow optimization, and inverter control. To obtain the new results, an error transformation function is introduced to generate an equivalent nonlinear system, whose asymptotic stability ensures both the asymptotic stability and the satisfaction of the output restriction of the original system. Besides, ADP algorithms are developed to solve the transformed nonlinear optimal problem with completely unknown system dynamics. Furthermore, asymptotic stability of the original and transformed nonlinear system is theoretically guaranteed. Finally, comparison results demonstrate the merits of the proposed policy.