Dynamics assessment of an inverter fed induction motor drive by an improved predictive controller leveraging finite control set mechanism

Abstract

Accenting the importance of Model Predictive Control (MPC) accross used optimization tools in current engineering applications, the proposed scheme establishes the predictive skills by well defined mathematical model in terms of present state variables. This paper projected a predictive  current  control(PCC) approach  scheduled by fininite control set(FCS) inverter switching mechanism  executed by a current modulated objective function.. The anatomy of this controller deals with selecting the control signal from a finite set of signals which satisfies minimum value of the predefined objective function, which is formulated by calculating the square error, i.e. the reference current against the stator measured current of the designed induction motor(IM). The proposed work further enriched with an improved predictive aspect named as integral finite control set(IFCS) action synchronized with a cascade feedback structure with appropriate controller gain to obtain an optimal set of control variables. With the direction in minimization of principle, these methods provide the control of the switching states for inversion, to the inverter and inverter generates actuating voltage signals to the induction motor. IFCS-MPC has the inherent capabilities of compensating steady state errors and slewrates which potrayed this as the preferred forecasted controller as compared to FCS-MPC. This work is also advanced with a comparative demonstration of torque, load currents and speed characteristics of IM, obtained from each of the implemented control techniques to identify the most flexible and dynamic predictive strategy. All these control methods have been investigated using MATLAB/Simulink environment.