A ELEVATOR GROUP CONTROL METHOD BASED ON PARTICLE SWARM OPTIMIZATION AND NEURAL NETWORK
In todays city life this elevator group control (EGC) problem is related to many factors, such as stochastic user equilibrium, the number of customers, running condition, is the difficulty of analysis, design and control.In order to improve the operation efficiency and service quality elevator, optimization control strategy, and the elevator was investigated. A new elevator group control method and system based on RBF algorithm is described.The RBF neural network is applied to control strategy in call distribution landing the elevator.Particle swarm optimization (PSO) neural controller-the method.Some links of the weighted parameters radial basis function neural network can be modified and optimization algorithms, and on the basis of the elevator group control performance effect can be obtained.The simulation results verify the contains the effectiveness of the method.The results prove that the method is effective.
Elevator Group Control Particle Swarm Optimization Neural Network
FU GUOJIANG
Information and control engineering Institute,Shenyang Jianzhu University,Shenyang 110168,China
国际会议
成都
英文
1548-1552
2011-11-25（万方平台首次上网日期，不代表论文的发表时间）