Decentralized inverse optimal control for interconnected systems

The Hamilton-Jacobi-Bellman (HJB) equations in optimal control for interconnected systems are difficult to solve, and the presence of external disturbances makes the problem even more challenging. This paper proposes a decentralized control method using inverse optimal strategy for a class of interconnected systems with disturbances. The robustness of the system is maintained by using disturbance observers to estimate unknown disturbances. By using inverse optimal control to find the controller and corresponding cost function, we eliminate the need to solve the HJB equations. By Lyapunov theory, we prove the designed composite controller is of optimality and robustness. Furthermore, the results are extended to n-dimensional interconnected systems with rigorous proof. Finally, the effectiveness of the proposed method is demonstrated through two examples.(c) 2023 The Franklin Institute. Published by Elsevier Inc. All rights reserved.

Automated summary

This paper proposes a decentralized control method using inverse optimal strategy for interconnected systems with disturbances. By using disturbance observers and inverse optimal control, the system achieves robustness and optimality. The results are extended to n-dimensional interconnected systems with rigorous proof.