Design and Analysis of an Intelligent Control System for Collaborative Robots Using Model Predictive Control (MPC) and Particle Swarm Optimization (PSO)"
Year: 2025
Type: article
Abstract: Background: Collaborative robots require accurate and adaptive control strategies to operate effectively in dynamic environments. Goal: This work aims to improve trajectory tracking accuracy and system efficiency using a hybrid control strategy. Method: We propose a novel integration of Model Predictive Control (MPC) with Particle Swarm Optimization (PSO), where PSO is used to optimize MPC parameters in real-time. Results: Simulations show that the hybrid MPC+PSO system outperforms traditional MPC, reducing RMSE by 57.8% and energy consumption by 22%. Conclusion: The proposed method enhances the accuracy and robustness of collaborative robotic control and is suitable for real-world deployment.
Author: Fadhil A. Ghlaim
Institution: Shahid Chamran University of Ahvaz
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7126034483
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