粒子群优化的磁轴承自适应反演滑模控制

Application of Adaptive Backstepping Sliding Mode Control Based on Particle Swarm Optimization in Magnetic Bearings

为实现两自由度主动磁轴承的高精度、强鲁棒控制,提出了一种基于粒子群优化的自适应反演滑模控制器对磁轴承进行控制。利用自适应反演滑模控制器对外部环境干扰进行预估,实现对磁轴承的位移进行精准跟踪和悬浮力的低脉动稳定运行,并且能够有效避免传统滑模的抖振效应。但由于影响控制品质的控制器参数较多,为了提高控制系统的收敛速度与精度,引入粒子群算法来在线优化控制器的参数。仿真结果表明经过整定后的自适应滑模控制器具有良好的动态跟踪性能。

In order to realize the high precision and strong robust control of the two-degree-of-freedom active magnetic bearing,an adaptive backstepping sliding mode controller based on particle swarm optimization is proposed to control the magnetic bear⁃ing.The adaptive backstepping sliding mode controller is used to estimate the external environmental interference,which can ac⁃curately track the displacement of the magnetic bearing and the low pulsation stable operation of the suspension force,and can ef⁃fectively avoid the buffeting effect of the traditional sliding mode.However,there are many parameters of the controller that affect the control quality.In order to improve the convergence speed and accuracy of the control system,particle swarm optimization is introduced to optimize the parameters of the controller online.The simulation results show that the tuned adaptive sliding mode controller has good dynamic tracking performance.