Decentralized inverse optimal control for interconnected systems.

• Inverse optimal method overcomes the difficulties of solving the nonlinear HJB equation. Not only are design procedure for 2-nd order systems given, but results for higher order systems are also generalised. • Integration of disturbance estimation in the virtual control design of the backstepping method, realizing the treatment of mismatched disturbances. • The composite inverse optimal control method gives a stabilizing control first with optimality and robustness, and then find the corresponding cost function. Controllers given in advance achieve well control performance with physical constraints, such as inpur saturation. • The proposed controller has a well understood and clear structure, which makes it easier for engineers to implement for practical systems. [Display omitted] 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. [ABSTRACT FROM AUTHOR]