TL;DR
The Improved Greater Cane Rat Algorithm (IGCRA) is proposed, which was hybridized through Greater Cane Rat Algorithm (GCRA) and Artificial Hummingbird Optimization (AHO) and is suggested to tune the parameters of the controller and the FENN.
The integration of intelligent PID optimization with backlash compensation provides a robust and efficient motion control solution for high-performance industrial servo systems operating under nonlinearities, load variations, and parameter uncertainties.
This paper presents a speed control strategy for an interior permanent magnet synchronous motor (IPMSM) used in electric vehicles employing the ant colony optimization algorithm (ACO). The ACO algorithm is utilized to optimize the speed controller parameters, aiming to minimize overshoots, settling time, and tracking e...
Permanent Magnet Synchronous Motors (PMSMs) are widely employed in electric vehicle (EV) propulsion systems because of their high efficiency, high power density, and superior dynamic performance. The performance of field-oriented control (FOC)-based PMSM drives strongly depends on accurate tuning of the proportional–in...
The permanent magnet synchronous motor (PMSM) is commonly used in industrial and home appliances for its high efficiency and dynamic performance. In this research, a PMSM drive based on field-oriented control (FOC) is designed and simulated using MATLAB/Simulink. The speed controller of the drive is tuned using the tri...
Brushless DC (BLDC) motors are now the dominant propulsion choice for electric vehicles (EVs) because of their high torque density, efficiency and reliability, but their nonlinear dynamics, electronic commutation, and wide load and speed range make fixed-gain control difficult. A single set of proportional–integral–der...
An intelligent IMC-based controller is proposed, in which the inversion gain of the temperature regulation loop is optimally tuned (offline) using a Genetic Algorithm to optimize the performance of robust control techniques applied to time-delay systems.
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