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Corresponding Author

Shaymaa M. Mahdi

Document Type

Article

Keywords

Par-4 Delta Parallel Robot, PID controller, PSO algorithm, FPA algorithm, WOA algorithm

Abstract

The Par-4 Delta parallel robot is a powerful candidate in most pick-and-place applications that require high speed, high acceleration, and high precision. Improving the tracking accuracy of parallel robots primarily relies on control design, which is essential for achieving enhanced performance and precision. The PID controller includes proportional, integral, and derivative values. On the other hand, the process of optimum tuning for a PID controller is complex and time-consuming until optimization approaches are employed. The Particle Swarm Optimization (PSO), Flower Pollination Algorithm (FPA), and Whale Optimization Algorithm (WOA) algorithms are the three Nature-Inspired Optimization algorithms proposed in this research for tuning the controller settings. To achieve the global minimum of tracking errors, the purpose of these approaches is to optimize the tuning of the PID controller's parameters toward the ideal level. The Root Mean Square Error (RMSE) indicates that the Whale Optimisation Algorithm (WOA) outperforms other methods in terms of tracking accuracy. WOA outperforms the classical PID controller by 58.5% in the x-axis and 85% in the z-axis. It also improves tracking by 33.9% (x-axis) and 69.3 % (z-axis) over the PSO-PID controller, and by 33.9% (x-axis) and 77.2% (z-axis) compared to the FPA-PID controller.

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