摘要
针对塔式起重机运行中重物摆动造成的工作效率降低、存在安全隐患等问题,建立塔式起重机的动力学模型,设计基于PSO的模糊神经网络滑模控制器,用于塔式起重机的定位、防摆控制。用模糊神经网络辨识塔式起重机系统模型的不确定项,并用PSO算法优化滑模控制器的参数。该方法降低了滑模控制系统的抖振,提高了控制系统的性能。仿真结果表明该方法的有效性和可行性。
The efficiency of tower crane will decrease, moreover hidden safety problems existing because of swing of the heavy load in the operation of the tower crane. The dynamics model of the tower crane was analyzed, and a kind of fuzzy neural network slid- ing mode controller based on PSO was designed using for tower crane positioning and anti-swing control. The fuzzy neural network was used for identification of tower crane model uncertainties, and PSO algorithm was used to optimize parameters of the sliding mode con- troller. The method reduces the chattering of sliding mode control system, improves the performance of the control system. The simula- tion results show the effectiveness and feasibility of the method.
出处
《机床与液压》
北大核心
2016年第22期155-159,共5页
Machine Tool & Hydraulics
基金
江苏省电子信息工程技术研究开发中心开放基金项目(KF20140203)
