Fractional Order Control Strategies for Delta Robot

Abstract

Parallel robots, such as the Delta robot, are increasingly used in demanding industrial applica- tions due to their exceptional performance in terms of speed, precision, and payload capacity. One of the main challenges in their use lies in the optimal management of their control to ensure enhanced stability and accuracy in the face of disturbances and system uncertainties. This thesis proposes an innovative approach using fractional-order control to improve the adap- tive control of this type of robot. Nonlinear fractional-order control techniques allow for finer regulation and better system responsiveness, while ensuring reinforced stability. Experimental results validate this approach, showing that it offers superior performance compared to tradi- tional methods. This work highlights the importance of evolving control strategies to meet the current challenges of robotic systems in modern industrial environments.