计算机仿真
計算機倣真
계산궤방진
COMPUTER SIMULATION
2014年
5期
363-368
,共6页
岳伟超%余发山%卜旭辉%栗三一
嶽偉超%餘髮山%蔔旭輝%慄三一
악위초%여발산%복욱휘%률삼일
未建模动态%参数摄动%矿井提升系统%自适应迭代学习控制%速度与位置跟踪
未建模動態%參數攝動%礦井提升繫統%自適應迭代學習控製%速度與位置跟蹤
미건모동태%삼수섭동%광정제승계통%자괄응질대학습공제%속도여위치근종
Unmodeled dynamics%Parameter perturbation%Hoisting system%Adaptive iterative learning control%Speed and position tracking
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。
礦井提升機在煤礦開採和生產過程中髮揮著至關重要的作用。在實際提升過程中,由于提升機自身或者週圍環境的影響,齣現參數攝動和未建模動態( PPAUD)等情況,降低瞭提升機速度與位置跟蹤精度。針對上述問題設計瞭一種自適應迭代學習控製策略,建立瞭提升機的數學模型,證明瞭繫統的收斂性,併對所提的控製策略進行瞭倣真以及實際測試。倣真結果錶明:所提齣的自適應迭代學習控製算法可以有效抑製參數攝動以及未建模動態(PPAUD),穫得較好的跟蹤性能;實際測試結果錶明提齣控製策略具有較彊的魯棒性,提升繫統速度與位置跟蹤精度有較大提高,證明自適應迭代學習控製方法是一種抑製上述擾動的有效方法。
광정제승궤재매광개채화생산과정중발휘착지관중요적작용。재실제제승과정중,유우제승궤자신혹자주위배경적영향,출현삼수섭동화미건모동태( PPAUD)등정황,강저료제승궤속도여위치근종정도。침대상술문제설계료일충자괄응질대학습공제책략,건립료제승궤적수학모형,증명료계통적수렴성,병대소제적공제책략진행료방진이급실제측시。방진결과표명:소제출적자괄응질대학습공제산법가이유효억제삼수섭동이급미건모동태(PPAUD),획득교호적근종성능;실제측시결과표명제출공제책략구유교강적로봉성,제승계통속도여위치근종정도유교대제고,증명자괄응질대학습공제방법시일충억제상술우동적유효방법。
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 was 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.