面向刚柔耦合定位平台的模型预测控制算法

Model predictive control algorithm for rigid-flexible coupling positioning stage

针对刚柔耦合定位平台(RFCS)在运动阶段和定位阶段模型不同的特点,提出了一种扩张状态观测器辅助的模型预测控制(ESO-MPC)算法。该算法采用时域离散的差分方程对RFCS的动力学响应进行预测,并且在时域离散时引入了可调参数应对实验模型的不确定因素。通过扩张状态观测器(ESO)获取反馈信息,对RFCS的位置、速度及柔性铰链的弹性力和阻尼力进行实时观测。通过RFCS的25组点位运动实验和负载实验,对比了传统PID、前馈PID、LADRC与ESO-MPC算法的性能。实验结果表明,4种控制方案都能达到±0.1μm的稳态误差,而ESO-MPC算法的整定时间最短,并且通过负载实验验证了ESO-MPC算法的鲁棒性。

For the feature that the RFCS has different models in motion and positioning stage,an extended state observer assisted model predictive control(ESO-MPC)method was proposed.The time-domain discrete difference equation was used to predict the dynamic response of RFCS,and an adjustable parameter during the time-domain discretization process was introduced to deal with uncertain factors of the experimental model.The feedback information was obtained through the Expanded State Observer(ESO),which can observe the position and speed of the RFCS as well as the spring and damping forces of the flexible hinge in real time.The performance of traditional PID,feedforward PID,LADRC and ESO-MPC was compared by 25 sets of RFCS point-to-point experiments and load experiments.The experimental results show that the four control schemes can achieve a steady-state error of±0.1μm,and ESO-MPC has the smallest setting time and the robustness of ESO-MPC is verified by load experiment.