1. An Extended-State Observer based system of Brushless DC Motor using fuzzy logic
Cross Strait Quad-Regional Radio Science and Wireless Technology Conference, VOL. 1, p.p , July 2011 

2. Outline ABSTRACT INTRODUCTION MATHEMATIC MODEL OF THE BLDCM MODEL
NONLINEAR PID CONTROLLER WITH FUZZY LOGIC
HARDWARE STRUCTURE
EXPERIMENT RESULTS
CONCLUSION
REFERENCES

3. Abstract
Brushless DC (BLDC) motors are widely used in vehicles because of its superior performance. The load disturbances in a BLDC have great influence on system performance.
Some complex algorithms were proposed to overcome the deficiency are difficult to implement on a single DSP chip but they are not easy to implement.

4. Abstract
To solve the problem, an extended-state observer was used to obtain the estimate signals for speed feedback signal and its differential, as well as estimated signal for load disturbance.
A functional design of FPGA in a brush less DC motor system based on FPGA and DSP was completed by using modular design method. The simulation and experiment results show that the proposed control method can enhance the performances of the servo system in rapidity, control accuracy, adaptability and robustness

5. INTRODUCTION
Brushless DC motors enjoy their tremendous popularity in fields such as vehicles, aerospace, medical, industrial automation equipment and instrumentation because of their high efficiency, high power factor, silent operation, compact form, reliability, and low maintenance. raditional linear PID servo control algorithm is simple, easy to implement, but can not meet the requirements for applications of more accuate and dynamic occations

6. MATHEMATIC MODEL OF THE BLDCM MODEL
The BLDCM produces a trapezoidal back electromotive force (EMF), and the applied current waveform is rectangular­ shaped. The self-inductance is L, and the mutual inductance is M. Hence the three-phase stator voltage balance equation can be expressed by the following state equation

7. NONLINEAR PID CONTROLLER WITH FUZZY LOGIC

8. NONLINEAR PID CONTROLLER WITH FUZZY LOGIC

9. NONLINEAR PID CONTROLLER WITH FUZZY LOGIC

10. NONLINEAR PID CONTROLLER WITH FUZZY LOGIC

11. HARDWARE STRUCTURE

12. HARDWARE STRUCTURE

13. EXPERIMENT RESULTS
The algorithm mentioned above is approved both by the MA TLAB simulation and the experiment. And the simulation and experiment results are shown as below.

14. EXPERIMENT RESULTS

15. EXPERIMENT RESULTS
A novel control strategy is applied into the BLDC speed servo system. Simulation and experiment results show that the proposed controller enhance the dynamic and static performance of the whole system. It maintains not only the advantages of the nonlinear PID control system, but also has greater flexibility, adaptability, the better control accuracy and robustness.

16. REFERENCES