Code for: Energy-efficient nonlinear optimal control strategy for induction motors.

Description

Article: Energy-efficient nonlinear optimal control strategy for induction motors. Authors: Javier Vergara, Ingeborg Mahla. Date: March 2026. Institution: Universidad de Santiago de Chile (USACH). This repository contains the MATLAB/Simulink R2024b simulation environment developed to validate the FBL-LQI (feedback linearization with linear quadratic integral) control strategy for induction motors. The primary objective is to provide an open, executable framework to reproduce the energy efficiency and dynamic response results discussed in the associated research paper. To ensure a rigorous technical benchmark, the dataset includes the proposed FBL-LQI controller alongside full implementations of direct field oriented control (DFOC) and scalar control (V/f) used for comparison. The post-processing scripts for calculating RMS errors and generating efficiency maps are integrated directly within the FBL_LQI.m script. This work aims to contribute to the optimization of induction motor controllers by providing verifiable tools for the study of nonlinear and optimal control focused on energy savings under variable load conditions. For more information, see the official article: J. Vergara, I. Mahla. Energy-efficient nonlinear optimal control strategy for induction motors. Corresponding contact person (E-mail addresses): ingeborg.mahla@usach.cl (I. Mahla).

Steps to reproduce

This folder contains the MATLAB implementations of three different control strategies for induction motors, specifically designed for thermal and performance analysis. All scripts are fully compatible with MATLAB R2024b and require the Control System Toolbox and the Statistics and Machine Learning Toolbox to function correctly. Each code is written as an independent function, so they can be run separately to compare how each manages the motor dynamics. The core of this work is found in FBL_LQI_control.m, which contains the proposed technique based on feedback linearization (FBL) and linear quadratic integral (LQI) control. This script is the most complete, as it includes the main error calculations and RMS metrics used in the study. To provide a robust comparison, DFOC_control.m implements classic direct field oriented control (DFOC), and VF_control.m provides standard scalar control V/f . Each simulation uses a common foundation: a nonlinear motor model, a two-node thermal network to monitor temperature rise in the stator and rotor, and an adaptive observer for real-time flux estimation. The motor is tested under a stochastic load following a Weibull distribution for 1800 seconds, providing sufficient time to observe the thermal effects on efficiency and resistance variation. To begin, simply open any script in MATLAB and run it. Average efficiency and tracking error results will appear in the command window, and graphs will display speed, torque, and thermal behavior.

Institutions

• Universidad de Santiago de Chile

  Santiago Metropolitan, Santiago

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