关键词: 行李导入电机, RBF 神经网络, 蚁群算法, 同步控制, PID

Abstract:

Based on synchronization control theory,a novel ACA-RBF-PID control strategy is proposed to achieve the accurate importing of airport luggage from conveyer belt to luggage sorter. Ant colony algorithm is employed to optimize the RBF neural network,averting the local optimization caused by traditional RBF neural network and achieving total optimization. Meanwhile,the motor synchronous control system is applied to guarantee the consistent speed of the luggage induction sorting motors,preventing two pieces of luggage from getting to the same luggage tray at the same time. Simulation results show that this strategy greatly improves the luggage importing efficiency and guarantees subsequent sorting smooth.

Key words: luggage importing motor, RBF neural network, ant colony algorithms, synchronization control, PID