Nonlinear Adaptive Extended State Space Predictive Control of PMSM

This book proposes new adaptive predictive control approach to control the current loop of the surface permanent magnet synchronous motor (SPMSM) called as Nonlinear Adaptive Extended State Space Predictive Control (NAESSPC). The detailed derivation of extended state space predictive control was given. A solution for the nonlinear problem based on Extended Non-Minimal State Space PC (ENMSSPC) and Modified Linear Quadratic (LQ) was given. Another solution for this problem based on ESSPC was applied to SPMSM. Then, a new state space model based on the states changes and output tracking error as the new states for new extended state space model was proposed for SPMSM. Accordingly, a new cost function was proposed which provided the change of the control input. Therefore, the simulation results proved that the proposed method had improved reference tracking, fast transient response, compensation of parameters variations and disturbance attenuation compared to PI controller in field oriented vector control scheme.

Autorentext

Dr. Ashraf Hagras behaalde de B. Sc. en M. Sc. graden in Power Electronics van respectievelijk Benha University in 1997 en 2008 en een PhD graad in Electrical Power and Machines van Cairo University in 2015. Zijn onderzoeksinteresses zijn onder andere Renewable Energy, Electrical Machines and Drives, Nonlinear Control, Neural Network en Fuzzy Logic Control.