基于模糊强化学习的双轮机器人姿态平衡控制

In order to solve the inherent problem of static instability of monorail two-wheel robot under resting conditions, a control method of monorail two-wheel robot based on fuzzy reinforcement learning (Fuzzy-Q in short) is proposed.Firstly, the Lagrange method is used to establish the system dynamics model with control moment gyro. And then, on this basis, the tabular reinforcement learning algorithm is designed to realize the stable balance control of the robot. Finally, In order to solve the problems of low control accuracy and discretization of controller output, the fuzzy theory is used to generalize the action space, improve the control accuracy and make the control output continuous. The simulation results show that compared with the traditional reinforcement learning methods, the proposed Fuzzy-Q method can significantly improve the control accuracy, effectively inhibit the influence of external interference torque on the system, and ensure that the system has a great anti-interference capability.