A Novel Hybrid Harris Hawk-Arithmetic Optimization Algorithm for Industrial Wireless Mesh Networks

Abstract

A novel hybrid Harris Hawk-Arithmetic Optimization Algorithm (HHAOA) for optimizing the Industrial Wireless Mesh Networks (WMNs) and real-time pressure process control was proposed in this research article. The proposed algorithm uses inspiration from Harris Hawk Optimization and the Arithmetic Optimization Algorithm to improve position relocation problems, premature convergence, and the poor accuracy the existing techniques face. The HHAOA algorithm was evaluated on various benchmark functions and compared with other optimization algorithms, namely Arithmetic Optimization Algorithm, Moth Flame Optimization, Sine Cosine Algorithm, Grey Wolf Optimization, and Harris Hawk Optimization. The proposed algorithm was also applied to a real-world industrial wireless mesh network simulation and experimentation on the real-time pressure process control system. All the results demonstrate that the HHAOA algorithm outperforms different algorithms regarding mean, standard deviation, convergence speed, accuracy, and robustness and improves client router connectivity and network congestion with a 31.7% reduction in Wireless Mesh Network routers. In the real-time pressure process, the HHAOA optimized Fractional-order Predictive PI (FOPPI) Controller produced a robust and smoother control signal leading to minimal peak overshoot and an average of a 53.244% faster settling. Based on the results, the algorithm enhanced the efficiency and reliability of industrial wireless networks and real-time pressure process control systems, which are critical for industrial automation and control applications.

Energy efficient optimal deployment of industrial wireless mesh networks using transient trigonometric Harris Hawks optimizer

“…These algorithms are iterative and heuristic-based approaches that employ exploration and exploitation techniques to search for optimal or near-optimal solutions [11] , [12] . By evaluating different node placement configurations and iteratively refining them, these algorithms can converge towards solutions that optimize energy consumption while ensuring adequate coverage and connectivity [13] , [12] , [14] .…”

A novel fractional-order dead-time compensating controller for the wireless networks

“…The evolution of control systems has led to the development of wireless digital controllers, which are currently at the forefront of this technological advancement. The state-of-the-art communication protocols have dramatically impacted industrial plants, which traditionally rely on wired communication protocols to connect controllers and other plant components 10 , 11 . However, wired networked control systems have limitations in scalability, distribution, self-organizing capabilities, and dynamic topology, which are critical for the efficient operation of modern industrial processes.…”

Design of PIDDα Controller for Robust Performance of Process Plants

“…However, their effectiveness must be improved to cater to more complex and higher-order systems [5]. Recent research suggests the integration of more complex PID controller configurations, such as fractional order calculus and higher-order derivative terms, such as PIDD 2 and proportional integral derivative acceleration controllers, to regulate more complex systems [1,3,[6][7][8]. The PIDD 2 controller has found extensive usage in power systems, power electronics, and control systems, and its recent developments and applications are discussed in the following sections.…”