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On PSO Based Fuzzy Neural Network Sliding Mode Control for Overhead Crane

机译:基于PSO的桥式起重机模糊神经网络滑模控制

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摘要

Based on particle swarm optimization (PSO), a new fuzzy neural network (FNN) sliding mode control (SMC) method is proposed for overhead crane. In order to ensure good dynamic performances of system, PSO algorithm is utilized to adjust adaptively controller parameters. At the same time, two FNNs are adopted to approach the uncertainties of the positioning subsystem and anti-swing subsystem. This approach could satisfy the strict specifications on the swing angle and realize trolley position control accurately. The simulation results show that good control performance is achieved, and the method can guarantee anti-swing control and accurate tracking control of trolley in considering of uncertainties and disturbances.
机译:基于粒子群算法(PSO),提出了一种新的模糊神经网络(FNN)滑模控制(SMC)方法。为了保证系统良好的动态性能,采用PSO算法对控制器参数进行自适应调整。同时,采用两个FNN来处理定位子系统和防摆动子系统的不确定性。该方法可以满足严格的摆角要求,并能准确实现小车的位置控制。仿真结果表明,该方法取得了良好的控制性能,在考虑不确定性和干扰的情况下,可以保证小车的防摆控制和精确的跟踪控制。

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