Conventional and model predictive direct torque control techniques for induction motor drive

Abstract

Finite control set model predictive control (FCS-MPC) is one of the promising alternatives for classical controllers (PID, hysteresis, etc…) in electric drive applications. The inherent discrete nature of FCS-MPC is suitable for a converter fed direct torque control (DTC) of induction motor drive. This paper presents a comparative study between conventional DTC and finite control set model predictive direct torque control (FCS-MPDTC) for an induction motor drive. The conventional DTC offers fast dynamic response, however the presence of nonlinear controllers causes considerable torque and flux ripples. In this paper, a simple one step ahead FCS-MPDTC is used by considering stator flux and rotor flux as state variables. In this method, nonlinear controllers and heuristic switching table are replaced with a cost function based online optimization for the selection of suitable switching state. Further, a new cost function is introduced based on simple weighted sum method to eliminate the selection of weighting factors. The results are verified for both control techniques applied to a 6 kW squirrel-cage induction motor under different operating conditions using MATLAB/Simulink. Proposed method resulted in improved steady state and dynamic response along with reduced torque and flux ripples compared to its counterpart.