于振中,周枫.粒子群优化模糊PID的电动负载模拟器研究[J].电子测量技术,2019,42(10):16-21
粒子群优化模糊PID的电动负载模拟器研究
Study on electric load simulator based on particle swarm optimization fuzzy PID controller
  
DOI:
中文关键词:  多余力矩  电动负载模拟器  模糊PID  粒子群优化算法
英文关键词:surplus torque  electric load simulator  fuzzy PID controller  particle swarm optimization
基金项目:江苏省自然科学基金项目(BK20130159)资助
作者单位
于振中 江南大学物联网工程学院 无锡 214122 
周枫 江南大学物联网工程学院 无锡 214122 
AuthorInstitution
Yu Zhenzhong School of Internet of Things Engineering, Jiangnan University, Wuxi 214122,China 
Zhou Feng School of Internet of Things Engineering, Jiangnan University, Wuxi 214122,China 
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中文摘要:
      为了解决多余力矩对电动负载模拟器强干扰,影响加载指令跟踪精度的问题,将基于粒子群优化的模糊PID控制方法用于加载电机控制器的设计。首先在分析加载电机结构以及工作原理的基础上建立了电动加载系统的数学模型,并利用结构不变性原理进行前馈补偿推导;其次针对常规PID控制器无法通过变参数来应对复杂的非线性环境,以及模糊PID量化因子、比例因子难以依靠经验调整问题,提出了一种基于模糊PID和粒子群优化算法的复合控制策略;最后通过仿真验证了该控制策略在对多余力矩消除上要优于常规的模糊PID控制。
英文摘要:
      In order to solve the problem that the surplus torque′s strong interference to the electric load simulator and affects the tracking accuracy, the fuzzy PID control method based on particle swarm optimization is applied to the design of motor controller. Firstly, the mathematical model of the electric loading system is established based on the analysis of the structure and working principle of the loading motor, and feedforward compensation is deduced by the principle of structural invariability; Secondly, because of conventional PID controller cannot deal with the complex nonlinear environment by changing parameters, and the fuzzy PID quantization factor scale factor is difficult to adjust by experience, a compound control strategy based on fuzzy PID and particle swarm optimization algorithm is proposed. Finally, the simulation result shows that the proposed control strategy is superior to the conventional fuzzy PID controller.
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