Control Of Brushless DC Motors Based On Smith Predictor

The brushless DC motor (BLDCM) has been broadly applied because of its eminent performance. But there are some inherent time lag factors in Brushless DC motor system. These factors have an adverse impact on the system which needs a high degree of accuracy and rapidity. They probably decrease the stability, the quality of regulation and the dynamic quality of the system. There will be greater overshoot and longer adjustment time if PID control is used only. In this paper, Smith predictor is introduced in the brushless DC motor system to compensate the time delay. Smith's principle is well known as an effective time compensator for the time delay. The main advantage of this technique is that the time delay is eliminated from the characteristic equation of the closed-loop system. Thus, the pure delay system can be transformed to the one without delay. Thus eliminates the adverse impact of due to time lag to system stability. The control system of BLDCM based on the microprocessor MSP430F149, which has the ability to realize real-time control, is proposed in this paper. Then the simulation results approve the validity.However, an accurate and stable mathematical model is needed for traditional Smith predictor to get satisfactory control quality. If not, it may lead to divergence and oscillation of system easily. In this paper a modified Smith predictor is proposed, which use fuzzy-PI controller to eliminate the parameters'deviations between Smith predictor and actual control object rapidly. So it can ensure that the state of the system stability. This scheme enhances robustness of the controlled system and alleviates the disadvantage of traditional Smith predictor in which an exactly precise model is needed. Simulation results show that the proposed method has good parametric adaptability and can provide higher characteristics to the system of with time-varying parameters and time lag.Secondly, another advanced Smith predictor system is proposed in this paper. The system uses fuzzy immune controller to eliminate the parameters'deviations between Smith predictor and actual control object. The simulation results approve the validity, and the new control system shows quick response speed, strong immunity ability, and strong robustness.