Distributed optimal control for continuous-time nonaffine nonlinear interconnected systems

Abstract

In this paper, a new distributed optimal control strategy for continuous-time nonaffine nonlinear systems with unknown dynamics is presented. We exploit a paradigm based on an Extended Adaptive Dynamic Programming (EADP), which will be fully stated in the paper, to provide a distributed optimal control strategy in the presence of subsystem interactions. A proper design of optimal control law is further fully investigated through the framework of Hamilton–Jacobi–Bellman (HJB). The proposed EADP algorithm can now be employed in order to solve iteratively the HJB equation associated with each subsystem. The proposed distributed optimal control system mainly consisting of three weighted basis functions for each subsystem is fully developed to handle the issue associated with the availability of unknown dynamics. The convergence analysis of the proposed algorithms is also established. Finally, two numerical examples are given to confirm the effectiveness of the proposed control scheme.

Keywords:

• Adaptive dynamic programming
• nonlinear interconnected systems
• distributed control systems
• data-driven
• optimal control
• reinforcement learning

Disclosure statement

No potential conflict of interest was reported by the author(s).