A Novel HSPICS for Industrial Robotic Controller Based on FPGA_SoC: Modelling and Fabrication
DOI:
https://doi.org/10.53523/ijoirVol9I2ID172Keywords:
HSPICS, HSMDAQ, GA, FPGA_SoC, Robotic ControllerAbstract
Tremendous studies have been proposed to optimize PI controller based Genetic Algorithm (GA) to improve the speed performance of DC motor commonly required in robotic applications. In PID controller, there are very few studies to overcome the drawbacks of classical GA, besides little pay attention to improving the speed performance of a DC motor to be measured in the microsecond unit. The main target is to maximize reduction step response characteristics, by proposing to design and fabricate a high speed proportional integral controller system (HSPICS). The primary methodology includes three sub methodologies using several new techniques and procedures to achieve three objectives. Firstly, to propose an improved genetic algorithm (IGA) to enhance the performance for better searching constraints for PI controller. Secondly, generate VHDL based Simulink model without needing expensive software. Finally, integrate the proposed controller-based on FPGA_SoC using Embedded Coder and FPGA in the loop (FIL) techniques to run the design based model. To show the effectiveness of the proposal, it was used three different DC motors. Simulation results show that the proposed controller achieves much higher reduction step response ratios (RSRR) compared with classical GA and PSO, further shortened step response characteristics to be measured in the microsecond unit. Analyzing the performance demonstrates that the RSRR has been enhanced for motors 1, 2, and 3 by 8, 9, and 35 times over classical GA, and 3, 3, and 10 over PSO, respectively. The comparison response time results between simulation and experimental for the studied motors show that the steady state time ratios (SST) were minimized significantly.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Falih Salih Mahdi Alkhafaji, Wan Zuha Wan Hasan
This work is licensed under a Creative Commons Attribution 4.0 International License.