摘要
针对交流调速传统控制方式的不足,提出了一种将模糊控制与神经网络结合的交流电机控制策略,并利用粒子群优化算法对模糊神经网络控制器的3个比例因子参数ka、kb、ku进行全局优化,充分发挥模糊神经网络控制器的鲁棒性。经与PID控制对比进行了试验验证表明,经过粒子群优化后系统具有很强的鲁棒性和自适应性,能够很好的跟踪负载变化,动态响应快,速度跟随准确。
In view of the shortages of the traditional control method for AC speed regulation, an AC motor control strategy by combining fuzzy control and neural network is proposed, and the particle swarm optimization algorithm is used to optimize the three-parameter ka, kb, ku of the FNN controller to increase the robustness of overall system. The system to compare with PID control examination test shows that it is with better robust, adjustability, follow performance, faster dynamic response and higher accuracy to load variation.
出处
《煤矿机电》
2009年第1期3-5,共3页
Colliery Mechanical & Electrical Technology
基金
辽宁省科技攻关项目(编号2007231003)
辽宁省创新团队项目(编号:2007T071)
国家自然科学基金项目(编号:50874059)
关键词
交流调速
鲁棒性
粒子群优化
模糊神经网络
AC speed regulation
robustness
particle swarm optimization
fuzzy neural network
