摘要
This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.
基金
supported by the National Natural Science Foundation of China (61973175
61973172)
Tianjin Natural Science Foundation (19JCZDJC32800)。
