具有PPAUD的矿井提升机速度与位置跟踪控制

Tracking Control of Mine Hoist System in Presence of Environmental Constraint

矿井提升机在煤矿开采和生产过程中发挥着至关重要的作用。在实际提升过程中,由于提升机自身或者周围环境的影响,出现参数摄动和未建模动态(PPAUD)等情况,降低了提升机速度与位置跟踪精度。针对上述问题设计了一种自适应迭代学习控制策略,建立了提升机的数学模型,证明了系统的收敛性,并对所提的控制策略进行了仿真以及实际测试。仿真结果表明:所提出的自适应迭代学习控制算法可以有效抑制参数摄动以及未建模动态(PPAUD),获得较好的跟踪性能;实际测试结果表明提出控制策略具有较强的鲁棒性,提升系统速度与位置跟踪精度有较大提高,证明自适应迭代学习控制方法是一种抑制上述扰动的有效方法。

Mine hoist syestem plays a critical role in the exploitation and production process of coal resources. In the actual process of ascension, the influence of hoisting machine itself or the surrounding environment, the parameter perturbations and unmodeled dynamics （PPAUD） and so on, reduce the hoist speed and position tracking accuracy. In view of the above problem, the adaptive iterative learning control strategy was proposed, mathematical model of mine hoist was established, the convergence of the system was proved, and also the control strategy wa~ tested by sim- ulating and practical tests. Simulation results illustrated the validity of parameter perturbations and unmodeled dynam- ics （PPAUD） attenuation, and the better tracking performance was obtained. The practical test also illustrates that this control strategy has strong robustness, the speed and position tracking accuracy of the hoist system are improved greatly. So the adaptive iterative learning control method is an effective approach attenuating the above-mentioned disturbance.