基于粒子群优化的升降机驱动装置控制策略

针对由于施工升降机驱动装置存在非线性因素，导致吊笼驱动装置运动精度低和响应慢的问题，提出了一种基于粒子群优化的比例、积分和微分(proportional integral derivative, PID)控制策略。首先，建立异步电机的矢量变频控制模型，基于MATLAB/Simulink通过偏差耦合控制策略实现三电机同步控制模型搭建，并设计了粒子群PID控制器以及模糊PID控制器；然后在ADAMS软件中建立驱动装置的虚拟样机，通过ADAMS的Controls接口模块与MATLAB实现机电联合仿真；最后根据施工升降机实际运行工况进行联合仿真验证并分析控制策略可行性。研究结果表明：粒子群PID控制器提升了吊笼位置控制精度与响应速度，粒子群优化PID系统响应时间相较于PID控制系统提升38%,相比模糊PID提升6%,系统稳态误差分别提升62%、98%,满足实际运行需求。

Control Strategy of Elevator Driving Device Based on Particle Swarm PID

To solve the problem of low motion accuracy and slow response of the cage driving device due to the nonlinear factors of the elevator driving device, a PID control strategy based on particle swarm optimization is proposed. Firstly, the vector frequency conversion control model of asynchronous motor is established. Based on Matlab/Simulink, the synchronous control model of three motors is built by deviation coupling control strategy. Particle swarm PID controller and fuzzy PID controller are designed; Then, the virtual prototype of the driving device is established in ADAMS, and the electromechanical joint simulation is realized through ADAMS''s Controls interface module and MATLAB; Finally, according to the actual operating conditions of the construction elevator, the joint simulation is carried out to verify and analyze the feasibility of the control strategy. The research results show that the particle swarm optimization PID controller improves the control accuracy and response speed of the cage position. The response time of the particle swarm optimization PID system is 38% higher than that of the PID control system, 6% higher than that of the fuzzy PID control system, and the steady-state error of the system is 62% and 98% higher respectively, meeting the actual operation requirements.