Investigation into PI controller output ripple in MRAS based electrical drives

Abstract

In Sensorless speed drives, which employ a model reference adaptive system (MRAS) with a PI based adaptation mechanism, the gains of the adaptation mechanism play an important role into the general performance of the drives. The higher the gain, the faster the response and the more robust the drive is going to be against load disturbance. Although it is desirable to utilise an adaptation mechanism with high PI gains, it was demonstrated that high gains will cause the estimated speed to exhibit a high level of noise. More recently it was identified that the generated noise consists of high-order harmonics. As far as the literature is concerned, even though the high-order harmonic phenomenon was identified and addressed by few researchers, there was no description in their literature of the generated high-order harmonics or an assessment of their effect in terms of being problematic. Therefore, the aim of this research is to not only investigate the generation of high-order harmonics, but also to establish whether any generated noise in the estimated speed bear an effect on the overall speed estimation process. An MRAS based speed estimator is implemented to calculate the rotor flux- linkage and the speed estimates required in achieving field orientation and establishing speed control. An investigation has been carried out to gauge how the PI controller gains can influence the speed estimation process of the drive system. As well as examining the estimated speed for any trace of excessive noise and harmonics generation. It is revealed experimentally that no high-order harmonics were generated while implementing an adaptation mechanism with high PI gains. However, it was found that high PI gains do causes the estimated speed to become relatively noisy and also starts to carry some fundamental frequency components relevant to the stator’s electrical frequency. Therefore a programmable adaptive adjustment mechanism has been successfully developed not only to avoid the excessive generation of noise but also improve the speed estimation process. The performance of both of the static adaptation mechanism and the proposed adaptive one was assessed and compared