A new method for controlling an induction motor using a hybrid discretization model predictive field orientated...

Area of Science:

• Electrical Engineering
• Control Systems
• Power Electronics

Background:

• Model Predictive Control (MPC) performance in Induction Motors (IM) depends on Discretisation Technique (DT) accuracy and efficiency.
• Traditional methods like Euler's offer speed but lack accuracy, while Heun's method improves accuracy at the cost of speed.
• Inaccurate or slow discretisation leads to high torque ripple and reduced load handling in MPC-controlled IMs.

Purpose of the Study:

• To introduce a novel Hybrid Discretisation Technique (HDT) for Model Predictive Field Oriented Control (MPFOC) in IMs.
• To achieve robust discretisation with enhanced accuracy and computational efficiency.
• To validate the proposed HDT's effectiveness in improving IM dynamic performance.

Main Methods:

• Developed a Hybrid Discretisation Technique (HDT) combining Euler's method for initial samples and a predictor-corrector approach for subsequent samples.
• Implemented the HDT within the MPFOC framework for a three-phase IM.
• Verified the system using Processor-In-Loop (PIL) simulation under varying load conditions and bi-directional rotation.

Main Results:

• The proposed HDT reduced IM torque ripple by up to 20%.
• Load handling capability was improved by up to 10%.
• Controller performance showed a 20% improvement in rise time and a 23% improvement in settling time under high load conditions compared to Euler and Heun methods.

Conclusions:

• The Hybrid Discretisation Technique (HDT) offers a superior approach for MPFOC in IMs, balancing speed and accuracy.
• HDT significantly enhances IM dynamic performance, reducing torque ripple and improving load handling.
• This technique provides a practical solution for achieving robust and efficient IM control systems.