SYNESep 3, 2018

Optimization Design of Decentralized Control for Complex Decentralized Systems

arXiv:1809.00596v1
Originality Incremental advance
AI Analysis

This work addresses the challenge of efficiently implementing decentralized control in complex systems, such as aircraft, but appears incremental as it builds on existing optimization techniques.

The paper tackles the problem of designing decentralized control systems that maintain the performance and robustness of centralized control, and demonstrates through simulation that the proposed method successfully achieves this target for a short takeoff and landing fighter.

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.

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