Research On The Speed Sensorless Vector Control System Of Induction Motor

In this thesis, the methods of parameter identification and state estimation are studied for AC induction motor, which is a multi-variable, strongly coupled and parameter-variable nonlinear control system. The complete digital control scheme was also presented with the design of hardware and software for AC induction motor.The rotor field oriented control has brought essential advances in AC variable speed drive system.Speed sensorless induction motor drive promotes the simplicity and robustness further, and two problems must be solved in the system: the speed estimation and rotor flux observation. Based on the former researches, the speed estimation and rotor flux observation methods are studied using the theory of Model Reference Adaptive System. The simulation results show the MRAS-based field oriented control system has good static and dynamic performance.In the third chapter, fuzzy logic and artificial neural networks will be introduced, which are made use of to estimate the resistance of stator and rotor respectively. Fuzzy logic control system does not confirm the accurate math mode of system, and neural networks have the ability to learn, so have become attractive tools for parameter identification. The simulation results show that these methods have good static and dynamic performance.The realization scheme of digital control system based on the digital signal processor was presented. The design of both software and hardware was optimized, and so the system can operate in real time with safety, the control soft is programmed base on TMS320F2812, and the overall digital control was achieved.