Optimal control of multiple CSPS system based on event-based Q learning

The optimal control problem of multiple conveyor-serviced production station (CSPS) system is concerned, and the objective is to maximize the part-processing rate of the entire system by choosing a coordinate look-ahead control strategy for each station. According to the idea of event-based optimization, and by using the concept of performance potentials, an event-based Q-learning algorithm is proposed to solve the coordinated look-ahead control problem with either discounted or average performance criteria. A simulation example is used to illustrate the effectiveness of the proposed algorithm, and the derived results show that the part-processing rate of the entire system is increased significantly compared to that obtained by a Wolf-PHC algorithm.