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Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm

Pneumatic servo systems face challenges such as friction, compressibility, and nonlinear dynamics, necessitating advanced control techniques. Research suggests model-based, model-free, hybrid, and optimization-based methods have their strengths. Therefore, this study presents an optimal control stra...

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Main Authors: Addie Irawan, Hashim, Mohd Herwan, Sulaiman, Mohd Syakirin, Ramli, Mohd Iskandar Putra, Azahar
Format: Article
Language:English
Published: Elsevier B.V. 2024
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/41474/1/Pneumatic%20servo%20position%20control%20optimization%20using%20adaptive-domain.pdf
http://umpir.ump.edu.my/id/eprint/41474/
https://doi.org/10.1016/j.rico.2024.100434
https://doi.org/10.1016/j.rico.2024.100434
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spelling my.ump.umpir.414742024-06-06T02:00:53Z http://umpir.ump.edu.my/id/eprint/41474/ Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm Addie Irawan, Hashim Mohd Herwan, Sulaiman Mohd Syakirin, Ramli Mohd Iskandar Putra, Azahar TK Electrical engineering. Electronics Nuclear engineering Pneumatic servo systems face challenges such as friction, compressibility, and nonlinear dynamics, necessitating advanced control techniques. Research suggests model-based, model-free, hybrid, and optimization-based methods have their strengths. Therefore, this study presents an optimal control strategy using Adaptive Domain Prescribed Performance Control (AD-PPC) cascaded with PID and optimized using the Evolutionary Mating Algorithm (EMA) for a pneumatic servo system (PSS). The goal is to achieve faster transient control and stable rod-piston positioning with minimal friction through the hysteresis phenomenon of the targeted proportional valve-controlled double-acting pneumatic cylinder (PPVDC) representing the PSS. The novel EMA optimizes the cascaded controller based on the tracking error as its objective function. Simulation studies verify the proposed AD-PPC-PID controller with the PPVDC model plant, iteratively optimized by the EMA. The analytical study compares this setup's control system and optimization model with the same control system model using alternative optimization methods. The testing employs step and multi-step signals for PPVDC's rod-piston position input. Results show that the EMA-tuned AD-PPC-PID outperforms AD-PPC-PID controller with other optimizers. For both input trajectory tests, EMA-tuned AD-PPC-PID shows faster response times, with average improvements of 30 % in settling times and 70 % in tracking performance metrics compared to other optimizers, making it robust for nonlinear system applications like PPVDC rod-piston positioning. Elsevier B.V. 2024-06 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/41474/1/Pneumatic%20servo%20position%20control%20optimization%20using%20adaptive-domain.pdf Addie Irawan, Hashim and Mohd Herwan, Sulaiman and Mohd Syakirin, Ramli and Mohd Iskandar Putra, Azahar (2024) Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm. Results in Control and Optimization, 15 (100434). pp. 1-16. ISSN 2666-7207. (Published) https://doi.org/10.1016/j.rico.2024.100434 https://doi.org/10.1016/j.rico.2024.100434
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Addie Irawan, Hashim
Mohd Herwan, Sulaiman
Mohd Syakirin, Ramli
Mohd Iskandar Putra, Azahar
Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm
description Pneumatic servo systems face challenges such as friction, compressibility, and nonlinear dynamics, necessitating advanced control techniques. Research suggests model-based, model-free, hybrid, and optimization-based methods have their strengths. Therefore, this study presents an optimal control strategy using Adaptive Domain Prescribed Performance Control (AD-PPC) cascaded with PID and optimized using the Evolutionary Mating Algorithm (EMA) for a pneumatic servo system (PSS). The goal is to achieve faster transient control and stable rod-piston positioning with minimal friction through the hysteresis phenomenon of the targeted proportional valve-controlled double-acting pneumatic cylinder (PPVDC) representing the PSS. The novel EMA optimizes the cascaded controller based on the tracking error as its objective function. Simulation studies verify the proposed AD-PPC-PID controller with the PPVDC model plant, iteratively optimized by the EMA. The analytical study compares this setup's control system and optimization model with the same control system model using alternative optimization methods. The testing employs step and multi-step signals for PPVDC's rod-piston position input. Results show that the EMA-tuned AD-PPC-PID outperforms AD-PPC-PID controller with other optimizers. For both input trajectory tests, EMA-tuned AD-PPC-PID shows faster response times, with average improvements of 30 % in settling times and 70 % in tracking performance metrics compared to other optimizers, making it robust for nonlinear system applications like PPVDC rod-piston positioning.
format Article
author Addie Irawan, Hashim
Mohd Herwan, Sulaiman
Mohd Syakirin, Ramli
Mohd Iskandar Putra, Azahar
author_facet Addie Irawan, Hashim
Mohd Herwan, Sulaiman
Mohd Syakirin, Ramli
Mohd Iskandar Putra, Azahar
author_sort Addie Irawan, Hashim
title Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm
title_short Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm
title_full Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm
title_fullStr Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm
title_full_unstemmed Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm
title_sort pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm
publisher Elsevier B.V.
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/41474/1/Pneumatic%20servo%20position%20control%20optimization%20using%20adaptive-domain.pdf
http://umpir.ump.edu.my/id/eprint/41474/
https://doi.org/10.1016/j.rico.2024.100434
https://doi.org/10.1016/j.rico.2024.100434
_version_ 1822924380836986880
score 13.232414

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