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Shuangyi Hu,Xuemei Ren,Dongdong Zheng 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.1
In this paper, a disturbance observer-based finite-time optimal synchronization control strategy is proposed with an adaptive bias torque for multi-motor driving servo systems. Finite time disturbance observers are designed to estimate the system nonlinearity and external disturbance, which ensure the finite time convergence of observation errors. Meanwhile a virtual tracking control input is designed to guarantee the output tracking of the load subsystem and a generalized synchronization error is obtained for the motor subsystem. Based on the synchronization error system, an auxiliary exponential function with finite-time convergence property is introduced to obtain the sufficient conditions for optimal synchronization control, which avoids solving the complex HamiltonJacobi-Bellman function. Simulation and experimental results reveal the flexibility of the proposed control scheme.
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Approximate Optimal Stabilization Control of Servo Mechanisms based on Reinforcement Learning Scheme
Yongfeng Lv,Xuemei Ren,Shuangyi Hu,Hao Xu 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.10
A reinforcement learning (RL) based adaptive dynamic programming (ADP) is developed to learn the approximate optimal stabilization input of the servo mechanisms, where the unknown system dynamics are approximated with a three-ayer neural network (NN) identifier. First, the servo mechanism model is constructed and a three-layer NN identifier is used to approximate the unknown servo system. The NN weights of both the hidden layer and output layer are synchronously tuned with an adaptive gradient law. An RL-based critic three-layer NN is then used to learn the optimal cost function, where NN weights of the first layer are set as constants, NN weights of the second layer are updated by minimizing the squared Hamilton-Jacobi-Bellman (HJB) error. The optimal stabilization input of the servomechanism is obtained based on the three-layer NN identifier and RL-based critic NN scheme, which can stabilize the motor speed from its initial value to the given value. Moreover, the convergence analysis of the identifier and RL-based critic NN is proved, the stability of the cost function with the proposed optimal input is analyzed. Finally, a servo mechanism model and a complex system are provided to verify the correctness of the proposed methods.
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