Analysis and Simulation of DC Motor Control System Based on Fuzzy-PID Control
Zang Xiao-hui
Abstract
Zang Xiao-hui
Abstract
It is difficult to define the control parameter in DC motor control system by using the routine PID controller.So the paper designs an adaptive PID controller based on fuzzy principle according to the system model.The error e and error rate ec are applied to FUZZY-PID controller as inputs to identify the fuzzy relationship between the three conventional PID parameters and e,ec.And through ongoing testing e and ec,three parameters can be changed according to the principle of fuzzy reasoning to meet the requirement of defining the PID control parameters at different moments.And the system is simulated based on Simulink.The analysis and simulation results indicate that the adaptive PID controller method is superior to the routine PID controller in that the former works well with high dynamic and static performance because of its quick response and good robustness. The experimental results show that the method is correct and efficient.
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It is difficult to define the control parameter in DC motor control system by using the routine PID controller.So the paper designs an adaptive PID controller based on fuzzy principle according to the system model.The error e and error rate ec are applied to FUZZY-PID controller as inputs to identify the fuzzy relationship between the three conventional PID parameters and e,ec.And through ongoing testing e and ec,three parameters can be changed according to the principle of fuzzy reasoning to meet the requirement of defining the PID control parameters at different moments.And the system is simulated based on Simulink.The analysis and simulation results indicate that the adaptive PID controller method is superior to the routine PID controller in that the former works well with high dynamic and static performance because of its quick response and good robustness. The experimental results show that the method is correct and efficient.
Key concepts: PID controller, Control theory (sociology), Robustness (evolution), DC motor, Fuzzy logic, Control engineering, Computer science, Fuzzy control system