Design and Comparison of Reinforcement-Learning-Based Time-Varying PID Controllers with Gain-Scheduled Actions

Yi-Liang Yeh, Po-Kai Yang
2021 Machines  
This paper presents innovative reinforcement learning methods for automatically tuning the parameters of a proportional integral derivative controller. Conventionally, the high dimension of the Q-table is a primary drawback when implementing a reinforcement learning algorithm. To overcome the obstacle, the idea underlying the n-armed bandit problem is used in this paper. Moreover, gain-scheduled actions are presented to tune the algorithms to improve the overall system behavior; therefore, the
more » ... roposed controllers fulfill the multiple performance requirements. An experiment was conducted for the piezo-actuated stage to illustrate the effectiveness of the proposed control designs relative to competing algorithms.
doi:10.3390/machines9120319 fatcat:jdpnaicfwjfdthosj5vvg4yll4