基于改进粒子群优化算法的电梯群控方案设计

Design of elevator group control scheme based on improved particle swarm optimization algorithm

由于电梯本身所具有的多目标性、不确定性和非线性,使得在电梯群调度控制方面容易出现候梯时间较长、能量消耗较大等问题。为了减轻这些问题对电梯群控制的影响,提出了一种基于改进粒子群算法的电梯群控方案。仿真结果表明:以权值优化改进粒子群算法加快了控制过程的收敛速度,使得平均到达时间、平均拥挤度、电梯的启停次数都有了很大的改善,满足了智能大厦电梯群控系统的需要。

Due to elevator inherent of multi-objective, uncertainty and nonlinear, so in the elevator group scheduling control prone to the problems such as wait for a long time, large energy consumption etc. In order to reduce the impact of these problems to elevator group control, this paper puts forward a kind of elevator group control scheme based on improved particle swarm algorithm. The simulation results show that the weight optimized improved particle swarm algorithm accelerates the convergence speed of the control process, making the average arrival time, average crowded degree, elevator start-stop times to have a lot of improvement, and has met the demands of the intelligent building elevator group control system.