Novel metaheuristic hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation

Abstract

This paper presents hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation and their application to control of a flexible manipulator system. Spiral dynamic algorithm (SDA) has faster convergence speed and good exploitation strategy. However, the incorporation of constant radius and angular displacement in its spiral model causes the exploration strategy to be less effective hence resulting in low accurate solution. Bacteria chemotaxis on the other hand, is the most prominent strategy in bacterial foraging algorithm. However, the incorporation of a constant step-size for the bacteria movement affects the algorithm performance. Defining a large step-size results in faster convergence speed but produces low accuracy while defining a small step-size gives high accuracy but produces slower convergence speed. The hybrid algorithms proposed in this paper synergise SDA and bacteria chemotaxis and thus introduce more effective exploration strategy leading to higher accuracy, faster convergence speed and low computation time. The proposed algorithms are tested with several benchmark functions and statistically analysed via nonparametric Friedman and Wilcoxon signed rank tests as well as parametric t-test in comparison to their predecessor algorithms. Moreover, they are used to optimise hybrid Proportional-Derivative-like fuzzy-logic controller for position tracking of a flexible manipulator system. The results show that the proposed algorithms significantly improve both convergence speed as well as fitness accuracy and result in better system response in controlling the flexible manipulator.

PID Tuning Method Using Chaotic Safe Experimentation Dynamics Algorithm for Elastic Joint Manipulator

“…Some authors [8,9] had combined SDA with the bacterial foraging algorithm (BFA) to generate the optimal proportional-derivative controller of the flexible manipulator system, and the hybrid of SDA-BFA produced better control and higher accuracy than the original SDA. A similar hybrid algorithm was used for tuning the fuzzy-logic-control parameters of the flexible manipulator system [10,11]. These hybrid algorithms showed the best performance, achieving the highest accuracy while obtaining relatively faster convergence.…”

Adaptive task allocation for multi-UAV systems based on bacteria foraging behaviour

“…In the same year, the bacterial chemotaxis (BC) heuristic simulated the movement of a single bacterium and evolutionary concepts to improve optimisation strategies and problem-solving capabilities. Since the development of BFO and BC, there has been a growing number of extensions that attempt to hybridise the algorithms with other metaheuristics and computational intelligence algorithms (e.g., [31,32,33,34,15]).…”

Hybrid spiral-dynamic bacteria-chemotaxis algorithm with application to control two-wheeled machines

“…Our previous study showed that the algorithm outperformed both BFA and SDA algorithms in terms of accuracy in finding a global optima solution. Compared to BFA, the total computation time has been significantly reduced and its convergence speed has been considerably increased [ 31 , 37 ].…”

“…2 . The HSDBC algorithm has been tested to model and control nonlinear systems including flexible robot manipulator and a twin rotor system using a PD-like FLC [ 35 , 37 ].

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“…We will implement HSDBC algorithm to control two different configurations of two-wheeled machines. A detailed simulation study of the HSDBC algorithm using several unimodal and multimodal benchmark functions can be found in the work of Nasir and Tokhi [ 37 ]. A hybrid fuzzy-like PD and I controller is designed and implemented on the two systems.…”