电动缸举升伺服机构高精度复合控制策略

针对电动缸举升机构的高精度伺服控制的现实需求,提出结合辨识伺服环路和差分激励信号的一种基于限定记忆区间的循环最小二乘法(CLS)以及基于迭代控制器参数和观测器参数的一种变参数比例积分控制器(VPI)结合基于卡尔曼滤波器的变参数比例多重积分观测器(VPMISAKF)的复合控制策略.实验结果表明:相比于最小二乘法, CLS辨识法辨识拟合的惯量和阻尼均方根误差分别下降93.61%和82.39%;相比于PI控制器, VPI结合VPMISAKF的复合控制策略使得系统的阶跃响应拟合度在空载和带载工况下分别提高至0.994和0.991;相比于VPI控制器,VPI结合VPMISAKF的复合控制策略使得系统的正弦响应误差在空载和带载工况下分别降低88.89%和86.45%. CLS辨识法和VPI结合VPMISAKF的复合控制策略对电动缸举升机构的高精度伺服控制具有一定的参考意义.

High precision control strategy of EMA lifting servo mechanism

Aiming at the practical demand of high-precision servo control of electric cylinder lifting mechanism, a compound control strategy based on a limited memory interval cyclic least(CLS) square method and a variable proportional integral(VPI) controller based on iterative controller parameters and observer parameters combined with proportional multiple integral observer based on the Kalman filter(VPMISAKF) to identify the servo loop and differential excitation signals is proposed. The experimental results show that compared with the least square method, the inertia and damping root mean square errors of the CLS identification method are reduced by 93.61% and 82.39% respectively. Compared with the PI controller, the composite control strategy of the VPI and VPMISAKF improves the step response fit of the system to 0.994 and 0.991 under no-load and loaded conditions respectively. Compared with the VPI controller, the combined control strategy of the VPI and VPMISAKF reduces the sinusoidal response error of the system by 88.89% and 86.45% under no-load and loaded conditions respectively. The CLS identification method and the compound control strategy of the VPI combined with the VPMISAKF have certain reference significance for high-precision servo control of electric cylinder lifting mechanism.