Application Of Self-adaptive Differential Evolution Algorithm In PMSM Controller

Permanent magnet synchronous motor is important electrical equipment inindustrial and agricultural production. Due to the large number and wide range ofapplications, research and improve their control performance will optimize existingproduction processes and save energy. Multi-variable and multi-coupling is adistinctive feature of permanent magnet synchronous motor, which brings manydifficulties to control system design. The accuracy requirements of control system cannot be met by Conventional control system design methods.In recent years, theadvances in intelligent control technology have brought new ideas to solve theproblems in this area.As a new member of intelligent optimization algorithms, thedifferential evolution algorithm is widespread concerned, whose structure is simpleand optimization efficiency is quite high. However, due to the limitations on structureand the high sensitivity of evolutionary parameters, the standard differential evolutionalgorithm is often unable to obtain satisfactory optimization results in individualcases. Therefore, this paper applied differential evolution algorithm, whoseevolutionary parameters can be adaptively adjusted, to the design of permanentmagnet synchronous motor controller, in order to solve practical engineeringproblems of motor control using intelligent optimization algorithms.This paper analyzes the mathematical model of permanent magnet synchronousmotor in three-phase stationary ABC coordinate system, two-phase stationary coordinate system and two-phase rotating d qcoordinate system. Then theSVPWM modulation algorithm and its application in permanent magnet synchronousmotor drive scheme are introduced.On the base of reviewing extensive literature, the theory of standard differentialevolution algorithm and its improvement strategies are studied.Differential evolutionalgorithm has strong potential in optimization. Thus it becomes research focus inintelligent evolutionary algorithm area. Many scholars have studied the structure andevolutionary parameter settings issue of this algorithm, and proposed correspondingimprovement.As the standard differential evolution algorithm is very sensitive to thesetting of evolutionary parameters，a strategy that evolutionary parameters can beadjusted according to the evolutionary stages is presented in this paper. By constantly adjusting the parameters of evolution, can ensure the appropriate stage of theevolution of the numerical algorithm running with reasonable parameters matchingalgorithm to improve speed and stability. It can be ensured that the evolutionarystages are performed appropriately with appropriate evolutionary parameters by theconstantly adjustment of the evolutionary parameters, which will promote the speedand stability of differential evolution algorithmThe self-adaptive differential evolution algorithm is applied to the design of thepermanent magnet synchronous motor controller and the problems related withpractical engineering application are discussed at last.The PID parameters in motorcontroller are optimized by self-adaptive differential evolution algorithm, whichimprove the dynamic characteristics and anti-jamming capability of the controllersignificantly. Simulation results show that the permanent magnet synchronous motorcontroller designed with self-adaptive differential evolution algorithm can effectivelyreduce the settling time and enhance system torque disturbance rejection capability.