Abstract
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.
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Wang, Z., Chen, Z., Zhang, J. (2011). On PSO Based Fuzzy Neural Network Sliding Mode Control for Overhead Crane. In: Wang, Y., Li, T. (eds) Practical Applications of Intelligent Systems. Advances in Intelligent and Soft Computing, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25658-5_67
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DOI: https://doi.org/10.1007/978-3-642-25658-5_67
Publisher Name: Springer, Berlin, Heidelberg
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