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Research And Perfection Of DTC Intellectual Control Based On DSP

Posted on:2009-06-17Degree:MasterType:Thesis
Country:ChinaCandidate:C L MaoFull Text:PDF
GTID:2132360272499628Subject:Detection Technology and Automation
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Direct Torque Control(DTC) is a high performance speed control system developed after Vector Control Technology.During the recent years,DTC has been developed greatly because of its simple system scheme and excellent dynamic and static performances.The produce and development of DTC is firstly introduced detailedly,and then, based on the current development and researching hot point,a new speed-sensorless technology is put forward.DTC technology has many advantages but is not mature and perfect in the theory, since its inherent drawback in its classical model has always baffled the development of DTC.In order to realize a high-performance timing system,the speed of asynchronous motor is to be measured.The application of speed sensor raises system complexity, lowers the reliability and robustness and increases the cost of entire system and maintenance.So speed-sensorless technology becomes a current researching hot point.A speed identifier constructed by Neural Network optimized by artificial fish school algorithm is advanced,which is put into MATLAB/simulink DTC system.When the system is running,contrast with single BP neural network the training curve follows well the actual curve according to the simulating results,and other system performances are improved obviously.For example,the fluctuation of torque and flux reduce obviously.In this paper,the AFSA is firstly used in DTC system.By simulate the speed identifier constructed by AFSA and BP Neural Network is also a forceful exploration in the development of speed-sensorless.For improving the motor low speed capability,the flux observation constructed by AFSA and BP Neural Network will apply to Direct Torque Control experiment in Intelligence comprehensive test machine by the form of DSP softwareIt possesses favorable dynamic response because of the parallel computing ability of modified NN.The experimental result proves the feasibility of this method,so this model can be the feedback quantity in speed governing system of asynchronous machine.At the same time this method can restrain the unstabilizing factor which aroused by stator resistance in low speed state.
Keywords/Search Tags:direct torque control, artificial fish school algorithm, neural network, speed identifier
PDF Full Text Request
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