关键词: Artificial potential field Black hole Galactic swarm optimization Gravitational search algorithm Multi-verse optimizer Nature-inspired control Nonlinear control Optimization

来  源:   DOI:10.1016/j.heliyon.2024.e31771   PDF(Pubmed)

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.
摘要:
控制算法是基于与自然启发机制相关的知识提出的,包括那些基于生物行为的。本文提出了一项综述,重点是在受物体之间引力启发的应用控制范围内取得的重大突破。确定了一种专注于人工势场的控制方法,以及四种优化元启发式算法:引力搜索算法,黑洞算法,多版本优化器,和银河群优化。对91篇相关论文进行了彻底的分析,以突出它们的性能,并确定引力和吸引力的基础,以及支持它们的宇宙法则。包括他们的标准配方,以及他们的改进,已修改,混合动力车,级联,模糊,混乱和自适应版本。此外,这篇综述还深入探讨了宇宙启发算法对动态系统控制问题的影响,提供与控制相关的应用程序的广泛列表,以及它们固有的优势和局限性。强有力的证据表明,引力启发和黑洞动态驱动算法可以胜过控制工程中其他著名的算法,即使它们不是根据现实的天体物理现象设计的,也不是根据天体物理学定律制定的。即便如此,它们支持未来的研究方向,以发展受牛顿/爱因斯坦物理学启发的高度复杂的控制定律,这样,有效的控制天体物理学桥梁可以建立和应用在广泛的应用。
公众号