In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new se...In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.展开更多
将一种基于模糊推理的参数自整定 PI 控制器引入到永磁同步电动机(PMSM)矢 量控制系统中，该控制器可以根据控制量给定值和反馈值的偏差 E 和偏差变化率 EC 按照模糊控 制规则实时自整定 PI 控制器的两个参数。仿真结果表明，运用该控...将一种基于模糊推理的参数自整定 PI 控制器引入到永磁同步电动机(PMSM)矢 量控制系统中，该控制器可以根据控制量给定值和反馈值的偏差 E 和偏差变化率 EC 按照模糊控 制规则实时自整定 PI 控制器的两个参数。仿真结果表明，运用该控制方法的系统响应快、超调 小、鲁棒性好，较常规 PI 控制具有更好的动静态性能。展开更多
基金This research is financially supported by the Ministry of Science and Technology of China(Grant No.2019YFE0112400)the Department of Science and Technology of Shandong Province(Grant No.2021CXGC011204).
文摘In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.
文摘将一种基于模糊推理的参数自整定 PI 控制器引入到永磁同步电动机(PMSM)矢 量控制系统中，该控制器可以根据控制量给定值和反馈值的偏差 E 和偏差变化率 EC 按照模糊控 制规则实时自整定 PI 控制器的两个参数。仿真结果表明，运用该控制方法的系统响应快、超调 小、鲁棒性好，较常规 PI 控制具有更好的动静态性能。
