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Research On Permanent Magnet Synchronous Motor Servo System Based On Adaptive Slinding Mode Control

Posted on:2015-11-28Degree:MasterType:Thesis
Country:ChinaCandidate:L YeFull Text:PDF
GTID:2272330467951257Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
With high-performance and low-cost permanent magnet materials had been found one after another, the development of power electronics and innovation of control theory, permanent magnet synchronous motor (PMSM) was widely used in various fields, such as aerospace, medical equipment and machinery manufacturing. Compared with DC motor, the mechanical structure of PMSM was more simple and stable, and PMSM had comparable or even better static and dynamic performance.Sliding mode control was not sensitive to control object parameters and uncertain interference when sliding mode was reached. But the specific model of controlled object was needed when designed the sliding surface to achieve a high performance. In practical applications, the system state went across the sliding surface back and forth instead of moving along the designed line. Neural network (NN) was capable to approximate arbitrary nonlinear function, but it took a long time to turn the parameters. By combining these two control methods properly, we can complement each other’s advantages and improve the performance.Aiming at improving the speed tracking performance and reducing the effect caused by mismatching parameters of proportion integral (PI) controllers when wide range of speed and variable load were considered in traditional permanent magnet synchronous motor (PMSM) speed control system, a finite time speed control approach was proposed. With the feedback error learning structure, a nonlinear PI (NPI) controller was provided to guarantee system convergence and stability, and its output was used to update the NN parameters. The adaption laws of NN parameters were designed based on terminal sliding mode (TSM) principle to accelerate the parameters convergence speed. Then, the output of the RBFNN controller can gradually replace that of the nonlinear PI controller. The stypticity and stability of the controller was analyzed based on Lyapunov, and it was simulated on PMSM speed control system. The results indicate that the proposed finite time speed control approach which based on feedback error learning structure can reduce the static system error and chattering, and have strong anti-disturbance ability. Using digital signal processor named TMS320LF2407A as the control system’s core, designed the rectifying circuit, current sensing circuit, PWM control circuit based on intelligent power module (IPM), fault handing circuit, et al. and constructed the experimental system. Then developed the software of the control system based on the voltage vector control principle and the approach proposed in this paper, including current sampling procedures, speed control procedures, transformation of coordinates procedures, SVPWM procedures and interrupt handling procedures. Finally, completed commissioning of PMSM vector control system and verified the feasibility of this method.
Keywords/Search Tags:permanent magnet synchronous motor (PMSM), sliding mode control (SMC), neural network (NN), digital signal processor (DSP), feed back error learning
PDF Full Text Request
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