Abstract
This paper presents the implementation of the hybrid spiral-dynamic bacteria-chemotaxis (HSDBC) approach to control two different configurations of a two-wheeled vehicle. The HSDBC is a combination of bacterial chemotaxis used in bacterial forging algorithm (BFA) and the spiral-dynamic algorithm (SDA). BFA provides a good exploration strategy due to the chemotaxis approach. However, it endures an oscillation problem near the end of the search process when using a large step size. Conversely; for a small step size, it affords better exploitation and accuracy with slower convergence. SDA provides better stability when approaching an optimum point and has faster convergence speed. This may cause the search agents to get trapped into local optima which results in low accurate solution. HSDBC exploits the chemotactic strategy of BFA and fitness accuracy and convergence speed of SDA so as to overcome the problems associated with both the SDA and BFA algorithms alone. The HSDBC thus developed is evaluated in optimizing the performance and energy consumption of two highly nonlinear platforms, namely single and double inverted pendulum-like vehicles with an extended rod. Comparative results with BFA and SDA show that the proposed algorithm is able to result in better performance of the highly nonlinear systems.
Highlights
Optimization algorithms play a dominant role in solving real problems [38, 58]
Nasir et al [33, 34, 36] proposed linear and nonlinear adaptive Bacterial foraging algorithm (BFA) where the bacteria step size is varied based on the combination of bacteria and iteration index
This paper presents an extended study of the proposed algorithm in solving complex problem of two-wheeled inverted pendulum systems
Summary
Optimization algorithms play a dominant role in solving real problems [38, 58]. Bacterial foraging algorithm (BFA) [42] and spiral-dynamics algorithm (SDA) [50, 51] are well-known optimization techniques in solving realworld problems. Nasir et al [33, 34, 36] proposed linear and nonlinear adaptive BFA where the bacteria step size is varied based on the combination of bacteria and iteration index. Supriyono and Tokhi [49] developed various versions of BFA based on linear and nonlinear mathematical formulations to establish relationship between bacteria step size and their current fitness value. SDA is a relatively new and a simple algorithm developed inspired from natural spiral phenomena on earth It has a relatively fast convergence speed which can complement the drawback of BFA performance. Hybrid spiral‐dynamic bacteria‐chemotaxis A hybrid bacteria-chemotaxis spiral-dynamic algorithm (HSDBC) has been proposed by Nasir et al [30,31,32] to synergize the chemotactic strategy of bacteria and ASDA.
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