The paper designs a brushless direct current motor (BLDCM) control system, mainly including design of former stage driver circuit, H bridge drive circuit, sensor commutation control, Forward / reverse control. In order to increase the reliability of the system, improve the performance of motor running, one has a good choice of parameters about power amplifying circuit device. What is more, one adopts PID algorithm in the system. Experiments show that the operating speed is with wide speed range from 150 r/min to 4000r/min. Through the adjusting of PID parameters, the error of speed can be stabilized within 5r/min, the system exhibits very good performance. Both hardware implementation and software control algorithms are reliable. The system has a wide range of practical value.

The paper designs a high power DC motor closed-loop control system, mainly including design of H bridge drive circuit, speed detection circuit and signal conditioning circuit. In order to improve the performance of motor running, one proposes a fuzzy adaptive PID control algorithm. Firstly, one determines the degree of membership of the input values to defined fuzzy sets, then constructs the fuzzy rule table according to experience and experiments, finally, makes defuzzification for every parameter of PID controller, that is, Kp, Ki, Kd. Experiments show that both hardware implementation and software control algorithms are reliable, the running performance of the system is robust before or after adding load.

An efficient and practical controller was designed, which achieves high performance for a BLDC motor. Actual hardware experimental platform was established. Double-closed loop control scheme using PID algorithm is presented and applied into the system successfully. Through the tuning of PID parameters, the start and stop of motor is fast, current fluctuation is small, and the actual speed of operation is consistent to the set speed, the error of stability maintains at 10r/min or less. The experiment result shows the BLDC control system operates smoothly, and it has high reliability, robustness.

Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise. The presence of speckle damages radiometric resolution, at the same time, it hampers the human interpretation and scene analysis for SAR images. On the base of studying and analyzing the mathematical model of the bilateral filter, the paper proposed a modified adaptive bilateral filter (MABF). First, it separates non-independent two-dimensional Gaussian filter into two independent one-dimensional Gaussian filter, which improves the operation speed greatly. Then through the effective noise parameter estimation, it adaptively selects optimal parameters, which improves the filtering effect. The real SAR image data is used to test the presented method and the experimental results verify that MABF is feasible and effective.