BLDCM LabVIEW-based Intelligent Control

The brushless DC motor (BLDCM) has broad applied to replace the DC motor in Marine Electric Propulsion Control System because of its high torque density, high efficiency and stabilization. In order to improve Anti-disturbance performance of Marine Electric Propulsion Motor, in this paper, using brushless DC motor for the study, the research focuses on speed control, and combines artificial intelligence control methods with the traditional control strategies. The fuzzy neural network control algorithm is applied to the control system.Based on BLDCM's mathematical model, the simulation model of control system is built and simulated in MATLAB environment. According to fuzzy self-tuning PID controller, an adaptive neural fuzzy PID controller has proposed. This paper gives the descriptions of fuzzy neural network control technology and the structure of fuzzy neural networks. A two-dimensional FNN controller makes up the nucleus of the control strategy that integrates characteristics of fuzzy control and neural networks. Simulation results show that the fuzzy neural network algorithm obtains satisfactory static and dynamic performance, with strong robustness and adaptability.This paper selects NI's LabVIEW as software platform to build intelligent control system of brushless DC motor. The combination of FIS Editor and Simulink method in MATLAB is studied for making fuzzy reasoning structure, and then a mixed programming with LabVIEW and Simulink is realized by MATLAB Script Node. Not only Fuzzy Self-adjusting PID Controller and ANFIS PID Controller are designed, but also a fuzzy reasoning system is set up and applied. Data acquisition (DAQ) is applied for the speed signal acquisition and the output of control signals, which constitutes a closed loop. Hardware uses an integrated chip to complete the design of the main circuit.