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A novel hybrid bacteria-chemotaxis spiral-dynamic algorithm with application to modelling of flexible systems

机译:一种新颖的细菌趋化混合动力学算法及其在柔性系统建模中的应用

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This paper presents a novel hybrid optimisation algorithm namely HBCSD, which synergises a bacterial foraging algorithm (BFA) and spiral dynamics algorithm (SDA). The main objective of this strategy is to develop an algorithm that is capable to reach a global optimum point at the end of the final solution with a faster convergence speed compared to its predecessor algorithms. The BFA is incorporated into the algorithm to act as a global search or exploration phase. The solutions from the exploration phase then feed into SDA, which acts as a local search or exploitation phase. The proposed algorithm is used in dynamic modelling of two types of flexible systems, namely a flexible robot manipulator and a twin rotor system. The results obtained show that the proposed algorithm outperforms its predecessor algorithms in terms of fitness accuracy, convergence speed, and time-domain and frequency-domain dynamic characterisation of the two flexible systems.
机译:本文提出了一种新颖的混合优化算法,即HBCSD,它可以协同细菌觅食算法(BFA)和螺旋动力学算法(SDA)。此策略的主要目标是开发一种算法,该算法与最终算法相比,能够以更快的收敛速度在最终解决方案的末尾达到全局最佳点。 BFA被合并到算法中以充当全局搜索或探索阶段。探索阶段的解决方案然后馈入SDA,SDA作为本地搜索或利用阶段。所提出的算法用于两种类型的柔性系统的动态建模,即柔性机器人操纵器和双转子系统。结果表明,该算法在两个系统的适应度,收敛速度,时域和频域动态特性方面均优于其前代算法。

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