带遗忘因子的ILC在桥式起重机防摆中的应用研究

Application of With Forgetting Factor of PD Type Iterative Learning Control in Bridge Crane Anti-swing

在起重机防摆控制研究中,由于桥式起重机防摆控制系统是一个强耦合、非线性系统,系统的实时性能差,传统的PID控制器难以达到高精度跟踪,防摆效果并不理想。针对桥式起重机的非线性和不确定性,分析桥式起重机的动力学模型,提出带遗忘因子的PD型迭代学习控制策略,利用2个迭代学习控制器对小车的速度和负载的摆动分别进行控制。其中,迭代学习速度控制器的设计是参考一个简单的速度曲线。仿真结果证明了该方法能够提高系统的控制性能,改善系统的控制品质。与无遗忘因子的PD型迭代学习控制相比,遗忘因子算法在平滑跟踪期望曲线、抑制摆角残留方面更具优越性。

In crane anti-swing control research, the bridge crane anti-swing control system is a strong coupling, nonlinear systems, and poor real-time performance of the system, the traditional PID controller is often difficult to achieve high precision tracking, the effect is not ideal. In view of the bridge crane, nonlinear and uncertainty analysis of bridge crane dynamics model, put forward with forgetting factor of PD type iterative learning control strategy, using two iterative learning controller for the speed of the car and the motion of the load control respectively. Among them, the speed of iterative learning controller design is a simple reference speed curve. The simulation results show that the method can improve the control performance of system, improve the control quality of system. And without forgetting factor compared to the pd type iterative learning control, forgetting factor algorithm in smooth tracking expectation curve, inhibit angular residue has more advantages.