Optimization Design of Decentralized Control for Complex Decentralized Systems

TL;DR

This paper presents a genetic algorithm-based method for designing decentralized controllers that match the performance and robustness of centralized controllers in complex systems, demonstrated on a fighter aircraft.

Contribution

It introduces a systematic optimization approach for decentralized control design using GA to match centralized control performance with minimal trial and error.

Findings

Decentralized controllers achieve performance comparable to centralized controllers.

The method reduces design time and improves accuracy in decentralized control systems.

Validated on a fighter aircraft system with successful simulation results.

Abstract

A new method is developed to deal with the problem that a complex decentralized control system needs to keep centralized control performance. The systematic procedure emphasizes quickly finding the decentralized subcontrollers that matching the closed-loop performance and robustness characteristics of the centralized controller, which is featured by the fact that GA is used to optimize the design of centralized H-infinity controller K(s) and decentralized engine subcontroller KT(s), and that only one interface variable needs to satisfy decentralized control system requirement according to the proposed selection principle. The optimization design is motivated by the implementation issues where it is desirable to reduce the time in trial and error process and accurately find the best decentralized subcontrollers. The method is applied to decentralized control system design for a short takeoff and landing fighter. By comparing the simulation results of the decentralized control system with those of the centralized control system, the target of the decentralized control attains the performance and robustness of centralized control is validated.