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
采用微机械电子系统(Micro Electro-Mechanical Systems,MEMS)和硅隔离(Silicon on Insulator,SOI)技术制作出了量程为25MPa的倒杯式耐高温压阻力敏芯片,敏感电阻条与硅基底之间采用二氧化硅隔离,解决了在大于120℃高温下力敏芯片工作...采用微机械电子系统(Micro Electro-Mechanical Systems,MEMS)和硅隔离(Silicon on Insulator,SOI)技术制作出了量程为25MPa的倒杯式耐高温压阻力敏芯片,敏感电阻条与硅基底之间采用二氧化硅隔离,解决了在大于120℃高温下力敏芯片工作稳定性和可靠性的难题。设计了齐平式机械封装结构,避免了管腔效应影响,提高了传感器的动态响应频率。对研制出的耐高温动态压力传感器进行了静态性能和动态性能的标定实验,静态实验温度为250℃,得到了传感器基本性能参数,分析了传感器的不确定度,得出该传感器的基本误差为±0.114%FS(Full Scale,全量程),不确定度为0.01794mV,计算得到了传感器的热零点漂移和热灵敏度漂移指标,由动态性能实验得到传感器的响应频率为555.6kHz,实验表明所研制的MEMS压力传感器在高温下具有良好的精度和固有频率。展开更多
The local robust stabilization for a class of nonlinear uncertain systems is studied. The robustness concept of Lyapunov type stabilizability for nonlinear uncertain systems is defined. Under the norm bounded struct...The local robust stabilization for a class of nonlinear uncertain systems is studied. The robustness concept of Lyapunov type stabilizability for nonlinear uncertain systems is defined. Under the norm bounded structured condition, two cases for uncertainty in control matrix are taken to discuss Lyapunov type stabilizability of systems. The sufficient conditions of Lyapunov type stabilization are given from differential geometry and nonlinear H ∞ control of view, respectively.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The local robust stabilization for a class of nonlinear uncertain systems is studied. The robustness concept of Lyapunov type stabilizability for nonlinear uncertain systems is defined. Under the norm bounded structured condition, two cases for uncertainty in control matrix are taken to discuss Lyapunov type stabilizability of systems. The sufficient conditions of Lyapunov type stabilization are given from differential geometry and nonlinear H ∞ control of view, respectively.
