Universe-inspired algorithms for Control Engineering: A review

TL;DR

This review explores universe-inspired algorithms, especially gravitational and black-hole based methods, highlighting their applications and potential to outperform traditional control algorithms in dynamic systems.

Contribution

It provides a comprehensive analysis of universe-inspired control algorithms, including formulations, variants, and their impact on control engineering applications.

Findings

Universe-inspired algorithms can outperform traditional methods in control tasks.

Many variants and hybrid versions enhance algorithm performance.

Potential for future physics-inspired control laws to advance the field.

Abstract

Control algorithms have been proposed based on knowledge related to nature-inspired mechanisms, including those based on the behavior of living beings. This paper presents a review focused on major breakthroughs carried out in the scope of applied control inspired by the gravitational attraction between bodies. A control approach focused on Artificial Potential Fields was identified, as well as four optimization metaheuristics: Gravitational Search Algorithm, Black-Hole algorithm, Multi-Verse Optimizer, and Galactic Swarm Optimization. A thorough analysis of ninety-one relevant papers was carried out to highlight their performance and to identify the gravitational and attraction foundations, as well as the universe laws supporting them. Included are their standard formulations, as well as their improved, modified, hybrid, cascade, fuzzy, chaotic and adaptive versions. Moreover, this review also deeply delves into the impact of universe-inspired algorithms on control problems of dynamic systems, providing an extensive list of control-related applications, and their inherent advantages and limitations. Strong evidence suggests that gravitation-inspired and black-hole dynamic-driven algorithms can outperform other well-known algorithms in control engineering, even though they have not been designed according to realistic astrophysical phenomena and formulated according to astrophysics laws. Even so, they support future research directions towards the development of high-sophisticated control laws inspired by Newtonian/Einsteinian physics, such that effective control-astrophysics bridges can be established and applied in a wide range of applications.