Data-Driven Suboptimal Scheduling of Switched Systems

Sensors

Minggang Gan¹  Jingang Zhao¹  Chi Zhang¹  Chenchen Xue¹ 

[1] State Key Laboratory of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, China;

关键词: optimal switching;    data-driven control;    switched systems;    policy iteration;    continuous time;   

DOI  :  10.3390/s20051287

来源: DOAJ

【 摘 要 】

In this paper, a data-driven optimal scheduling approach is investigated for continuous-time switched systems with unknown subsystems and infinite-horizon cost functions. Firstly, a policy iteration (PI) based algorithm is proposed to approximate the optimal switching policy online quickly for known switched systems. Secondly, a data-driven PI-based algorithm is proposed online solely from the system state data for switched systems with unknown subsystems. Approximation functions are brought in and their weight vectors can be achieved step by step through different data in the algorithm. Then the weight vectors are employed to approximate the switching policy and the cost function. The convergence and the performance are analyzed. Finally, the simulation results of two examples validate the effectiveness of the proposed approaches.

【 授权许可】

Unknown