【摘要】 针对管桩焊接机器人双直流电机系统的转速协同控制问题，提出一种基于扩张状态观测器的滑模控制器，结合逆向传播神经网络同步补偿器的控制方法，建立含有外部扰动（负载突变、外部摩擦等）和内部扰动（参数摄动、模型失配等）这些不确定扰动的无刷直流电机动态模型；利用扩张状态观测器对不确定扰动进行估计，结合滑模控制分别对2个电机进行抗扰动转速闭环控制，实现高精度速度跟踪；同时采用交叉耦合控制结构，利用逆向传播神经网络根据双电机转速误差，对每个电机进行误差补偿，从而减小双电机转速同步误差。仿真结果证明，所提出的控制策略，能够明显提升双电机系统的鲁棒性、转速跟踪精度和同步性能。更多还原

【Abstract】 A sliding mode controller based on extended state observer, combined with BP neural network synchronous compensator control method is proposed to solve the problem of speed cooperative control of dual DC motor system of pipe pile welding robot. A brushless DC motor dynamic model with uncertain disturbances such as external disturbances(load mutation, external friction, etc.) and internal disturbances(parameter disturbances, model mismatches, etc.) is established. Using the extended state observer to estimate the uncertain disturbance, combined with the sliding mode control, the anti-disturbance speed closed-loop control of the two motors is carried out to achieve high-precision speed tracking. At the same time, the cross-coupling control structure is adopted, and the BP neural network is used to compensate the error of each motor according to the speed error of the two motors, thereby reducing the speed synchronization error of the two motors. The simulation results show that the proposed control strategy can significantly improve the robustness, speed tracking accuracy and synchronization performance of the dual-motor system.更多还原