Development of MPC-ACO based Direct Torque Controller for Induction Motor Drive

Abstract

The purpose of this paper is to control the torque of a three-phase induction motor using model predictive control (MPC) with an ant colony optimization (ACO) based direct torque control (DTC) scheme in a 3.7 kW induction motor (IM) with simulation and experiment. DTC is the most popular method to control the torque, speed, and stator current ripple of the induction motor as it overcomes the demerits of vector control by implementing the advanced control strategy. The conventional model of DTC using a proportional integral (PI) controller has low tracking performance with parameter changes, hence the analysis has been performed to suppress the ripple content of speed and torque by introducing a model predictive control scheme which is one of the latest and most popular techniques. Further, the network is properly trained with network parameters using an ant colony optimization algorithm so that the designed network can think from its intelligent data process and will set the required voltage vector for the three-phase inverter. Moreover, the MPC-ACO controller is verified and compared with the PI controller in many aspects such as steady-state analysis, dynamic response, and robustness study. Therefore, torque and speed can be controlled with an acceptable limit and the desired dynamic performance is achieved with MPC-ACO controller by comparing with the PI controller as verified from simulation and experiment.