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Enhanced artificial satellite search algorithm with memory and evolutionary operator for PID controller parameter estimation
Faculty
Engineering
Year:
2025
Type of Publication:
ZU Hosted
Pages:
Authors:
Mohammed Alsayed MohamedAli
Staff Zu Site
Abstract In Staff Site
Journal:
Scientific Reprots Springer
Volume:
Keywords :
Enhanced artificial satellite search algorithm with
Abstract:
The effective tuning of Proportional-Integral-Derivative (PID) controllers is crucial for industrial process control, but achieving optimal parameters for complex systems remains challenging. The recent Artificial Satellite Search Algorithm (ASSA) is strong in exploration but suffers from an imbalance between global and local search and a greedy selection strategy, leading to premature convergence. To overcome these limitations, this paper proposes an enhanced variant, MEASSA (Memory-based and Evolutionary-enhanced ASSA), which integrates a memory mechanism to preserve elite solutions, an evolutionary operator for guided population dynamics, and a stochastic local search for intensive refinement. Experimental evaluations on three dynamic systems are a DC motor, a three-tank liquid level system, and a fourth-order system which demonstrate MEASSA’s superior performance. The algorithm achieved the lowest Integral Absolute Error (IAE) values of 9.977, 9.0781, and 9.697, respectively, outperforming several benchmark metaheuristics. Time-domain and frequency-domain analyses further confirm its ability to minimize overshoot, improve settling time, and enhance system stability, validating MEASSA as a robust and accurate method for complex PID controller tuning.
Author Related Publications
Mohammed Alsayed MohamedAli, "PID Controller Tuning Parameters Using Meta-heuristics Algorithms: Comparative Analysis", Springer, Cham, 2018
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Mohammed Alsayed MohamedAli, "Digital Image Watermarking Performance Improvement using Bio-inspired Algorithms", Springer, 2018
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Mohammed Alsayed MohamedAli, "ASCA-PSO: Adaptive sine cosine optimization algorithm integrated with particle swarm for pairwise local sequence alignment", Elsevier, 2018
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Mohammed Alsayed MohamedAli, "Memory-based quadratic interpolation optimization with reinforcement learning for robust PV parameter estimation", Springer, 2026
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Mohammed Alsayed MohamedAli, "A novel reinforcement learning-based reptile search algorithm for solving optimization problems", Springer, 2023
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Department Related Publications
Ahmed Mahmoud Abdelrahman Elanany, "Recursive subspace identification with prior information using the constrained least squares approach", Elsevier, 2013
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Mahmoud Ali Abdelnabi Mosa, "Optimal Control for Multi-mode Systems with Discrete Costs", International Conference on Formal Modeling and Analysis of Timed Systems - FOMATS2017, 2017
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Ahmed Mahmoud Abdelrahman Elanany, "Comparative diesel engine performance and emission forecasting using extreme learning and quadratic regression techniques burning waste cooking biodiesel", ُElsevier, 2024
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Besher Mohamed Nassef Abdelaziz Abdelaty, "Activated Carbon Fabricated from Biomass for Adsorption/Bio-Adsorption of 2,4-D and MCPA: Kinetics, Isotherms, and Artificial Neural Network Modeling", MDPI, 2023
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