Robust Speed Control And Predictive Current Control Of Switched Reluctance Motor

The speed control system of switched reluctance motor usually adopts double closed loop PI control,namely speed PI control and current PI control.The traditional switched reluctance motor speed control system has disadvantages such as low control accuracy,large overshoot,slow dynamic response speed and poor system robustness.In order to improve the control performance of the switched reluctance motor speed control system,this paper firstly proposes a non-linear model of the switched reluctance motor based on the look-up slice function method.This model not only has high accuracy,but also a small amount of calculation and small CPU storage space,which is suitable for real-time control.On this basis,the advanced control algorithm combination of predictive current control and sliding mode variable structure speed control is adopted to design a high performance switched reluctance motor control system.Current PI control ignores the non-linear characteristics of the motor,resulting in lower control accuracy of the system,slower response speed,and larger current overshoot.Meanwhile,it is difficult to adjust the PI parameters,which needs a lot of simulations and experiments for trial and error.Model predictive control is suitable for processing nonlinear problems with fast dynamic response speed,which can also achieve partial rolling optimization.However,the existing model predictive control has the following three shortcomings that cannot be ignored: the control algorithm has a large amount of calculation;it cannot eliminate the static error of the system;it has higher requirements for the control frequency.Especially when the control frequency is low,the motor cannot be controlled stably.In order to solve the problems of the above control methods,this paper proposes an improved predictive current control method.That is,through the switch control set of the current rotor position,the feedback current,and the non-linear model of the switched reluctance motor based on the slicing function method,predicting the current in the next state;the power determining switch state according to the magnitude of the reference and predicted current;deriving accurate PWM duty cycle with model error correction method.The improved predictive current control not only solves the problems of the above two current control methods,but also inherits their advantages.MATLAB/Simulink simulation verifies that the improved predictive current control method has the advantages of high control accuracy,less calculation,fast dynamic response,and elimination of static errors.The outer speed loop chooses to use a sliding mode controller instead of a PI controller to increase the robustness and dynamic response speed of the system.The traditional sliding mode controller has the following two main disadvantages: First,due to its own variable structure characteristics,the system chattering always exists which cannot be eliminated.Although the traditional approaching law can reduce the chattering,the effect is limited.Second,the robustness of the system only exists in the sliding mode,while the approaching mode does not have robustness.To solve the above problems,this paper uses hyperbolic tangent function to replace the sign function in the reaching law,which reduces the chattering of the system;a global robust sliding mode control is proposed,designing a dynamic nonlinear sliding mode to eliminate the process of the moving point approaching the sliding surface,which solve the problem that the approaching mode is not robust,to make the system robust in whole process of response,and is suitable for the occasions of frequent startup.MATLAB/Simulink simulation shows that the method in this paper not only reduces the fluctuation of the reference current,but also shortens the time for the moving point in the system to reach the sliding surface.While improving the response characteristics of the system,it also improves the robustness of the system.Finally,the construction of the experimental hardware platform and the design of the system software are completed,and a three-phase 12/8-pole switched reluctance motor is used for experimental research.The experimental results verify the effectiveness and feasibility of the method in this paper.