IIoT-based Automatic FOPID Tuning for AVR Systems Using a Customized Chaotic Whale Optimization

https://www.sciencedirect.com/journal/computer-science-review

This paper presents a new trend toward Artificial Intelligent Engineering by replacing a stand-alone control with remotely real-time control for users by using the Industrial Internet of Things to enhance AVR system tunning. The AVR is optimized by a new version of the Proportional-Integral-Derivative (PID) controller called FOPID which used the Fractional-Order calculus. The PID control is same FOPID while using external parameter that provide new and good performance extension. The five parameters of controller are tuned by a new version of the most popular metaheuristic algorithm which is Whale Optimization Algorithm (WOA). The usage of classical Whale algorithm is a clear algorithm but noneffective for tuning Fractional order controller in a wide range of optimization issues. Therefore, a Customized Chaotic-WOA (CCWOA) is proposed that is developed by mathematical equations and applied chaotic logistic map, which improves the algorithm convergence rate and precision by permitting it to minimize local minima stagnation. The performance of the proposed algorithm is evaluated with unimodal and multimodal benchmark functions. There are 13 benchmark functions with different characteristics are presented. On the other hand, the efficiency and superiority of the proposed algorithm with some recent algorithms and compare the response of the proposed controller with the classical PID to Justify the reason for switching from PID to FOPID Controller. Additionally, the optimal solutions of the comparison analysis are displayed. Numerical results and robustness analysis verify that CCWOA based on FOPID has effective tuning capability to enhance the step response of the AVR system compared to various existing algorithms.