Trajectory Tracking Control of Automated Guided Vehicle Based on Improved Sparrow Search Algorithm Optimizing PID Parameter Tuning
PID parameters tuning is a key to optimize the motion control of automatic navigation vehicles.Therefore,a AGV control algorithm based on improved sparrow search algorithm ISSA for optimizing PID parameters tuning is proposed.In order to address the shortcomings of SSA search accuracy,a logistic-tent hybrid chaotic initialization mechanism is introduced to optimize the initial population.An adaptive manner is used to update the proportion of the discoverer population,and an inertial adaptive mechanism is used to update the discoverer position to improve the algorithm global search ability.At the same time,a hybrid mutation mechanism is designed to enrich the diversity of the population in the later iteration stage and avoid falling into a local optimum.The improved SSA algorithm is utilized to optimize PID parameter tuning in AGV motion control and achieve AGV trajectory optimization control.The experimental results show that compared with five comparative algorithms,the improved algorithm has higher PID parameter tuning accuracy and can effectively improve AGV trajectory tracking performance,whose actual trajectory and target trajectory have a higher degree of fit.
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