Robust Control Optimized with Particle Swarm Optimization for Robot Manipulators

  • 1 Faculty of Engineering, Department of Mechanical Engineering, Istanbul University - Cerrahpaşa, Türkiye


The integration of robotic systems is widespread across diverse industries, notably in defence, automotive, and industrial sectors. These systems are endowed with the capability to execute precise movements via software programming, facilitating object manipulation and trajectory adjustments. Nonetheless, careful oversight is imperative during operations to avert undesirable outcomes stemming from mishandling. Consequently, the management of robotic systems has emerged as a pivotal concern in contemporary industrial practices. The parameters governing robotic systems are subject to fluctuations contingent upon the loads they bear. Robust control, a methodology geared towards adapting the control system to accommodate such parameter variations, stands as a cornerstone for ensuring stability and optimal performance. This approach enables the maintenance of desired control levels even amidst shifting system parameters. To refine controller parameters, an objective function derived from error functions of the first and second robot arms was minimized. In this endeavour, the particle swarm optimization (PSO) method, renowned for its efficacy, was employed. The efficacy of this proposed control methodology is substantiated through graphical representations, underscoring its utility and effectiveness in real-world applications.



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