Performance Assessment of Inverter fed Machine Drives by Hybrid Optimization Schemes Compounding Predictive and Computational Intelligent Techniques

Abstract

Model Predictive Control (MPC) has demonstrated remarkable efficacy in controlling synchronous and induction machine drives, power converter switching, and various power system parameters. More than one predictive control algorithm has been inspired by its adaptability, resilience, and quick dynamic responses. The exploration of dynamic models of induction motor (IM) and Permanent Magnet Synchronous Motor (PMSM) and the application of Model Predictive Control (MPC) techniques have significantly advanced motor control systems. This research initially focused on implementing Predictive Current Control (PCC) strategies using MPC algorithms, which calculate the squared discrepancies between reference and measured stator currents. These methodologies, tested in MATLAB/Simulink and Python, incorporated finite control set (FCS) and integral finite control set (IFCS) strategies to dynamically adjust control signals based on predefined minimization principles, enhancing voltage signal precision and efficiency. The study further extended to tailor PCC strategies for induction motor and PMSM, using current state variables to predict future conditions and adjust control actions, thereby demonstrating the potential of MPC to enhance motor function control, operational efficiency, and reliability. The application of intelligent techniques such as Genetic Algorithms (GA), Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO), Nelder Mead (NM) Optimization, Ant Colony Optimization (ACO) and Sequential Neural Network (SNN) to Induction Motor and PMSM, utilizing both FCS and IFCS for objective function minimization, provided a comprehensive analysis of how modern control methods could enhance motor performances. By integrating intelligent algorithms with predictive attributes, that adaptively adjust control parameters in real-time, the research achieved significant improvements like reduction in power consumption, enhanced torque response, and maintained stability under fluctuating load conditions,further highli