Research On Parameters Identification And Control Ofasynchronous Motor Based On ICPSO Algorithm

With the constant development of the vector control theory and technology, ACelectric drive systems have dominated in the field of high-performance electric drive.When the demand for the control performance of vector control system is enhanced,the parameters time-variety of induction motor and the sensitivity of vector controlsystem to motor parameters variation have become problems. Both off-line andon-line existing parameter identification methods of induction motor, cannot meet therequirement of vector control system on real time and convergence. Therefore,researching an online induction motor parameters identification algorithm, andimproving vector control systems, is of great significance for further enhancingperformance of AC electric drive systems. In view of these problems, this articlestudied on online induction motor parameters identification method and itsapplication in vector control systems.Integrated with the advantages of the standard particle swarm algorithm (SPSA),the thought of co-evolutionary and immune clone selection algorithm (CSA), animmune co-evolutionary particle swarm optimization (ICPSO) algorithm wasproposed. In this algorithm, the population is divided into several general populationsand one dominant population. SPSA is used in the general populations withneighbor information, while CSA is used in dominant population toaccelerate convergence of dominant individuals, and the thought of parallelcomputing and the interactions between species in co-evolutionary algorithm isborrowed in ICPSO.By adopting the superiority of ICPSO algorithm in wide range search anddynamic target optimization, the problem of online identification of asynchronousmotor parameters has been solved. Based on original vector control system, with theresults of online identification, the parameters of the flux observation, thedecoupling controller and the PI controllers have been adjusted. A novel vectorcontrol system with parameters identification based on the ICPSO algorithm has beendesigned. With the simulation model built on MATLAB/Simulink platform, theeffectiveness of asynchronous motor parameters identification by the ICPSOalgorithm has been tested via the simulations. On the condition of motor parametersvarying, compared with the original vector control system, the novel system designedin this paper preforms better in flux observation, speed tracking and torquecontrolling.