Research
A Modified Active Disturbance Rejection Controller Based on Radial Basis Function Neural Network for AUV Attitude Control, 2022 IEEE International Conference on Advanced Robotics and Mechatronics (ICARM), 2022
with coworkers: Huixi Xu, Zhibin Jiang
Abstract: In this paper, an Active Disturbance Rejection Controller (ADRC) based on Radial Basis Function Neural Network (RBFNN) is proposed to increase Autonomous Underwater Vehicle’s (AUV) motion control capacity and anti-disturbance performance. An extended state observer based on the adaptive RBF neural network is designed. And the method treats both internal and external unknown disturbances as one of system’s states and estimates and compensates it online into control system’s input. The results of simulation indicate that the method can improve controller’s performance effectively. Compared with PID control and original ADRC control, the proposed method can better meet the requirements of system for high precision control performance.
Working Papers
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with coworkers
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