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

机译:混合螺旋-动态细菌趋化算法在控制两轮机中的应用

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摘要

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.
机译:本文介绍了混合螺旋动力细菌趋化(HSDBC)方法的实现,以控制两轮车的两种不同配置。 HSDBC是在细菌锻造算法(BFA)和螺旋动力学算法(SDA)中使用的细菌趋化性的组合。由于趋化性,BFA提供了良好的勘探策略。但是,当使用大步长时,它会在搜索过程即将结束时承受振荡问题。反过来;对于较小的步长,它提供了更好的利用和准确性,同时收敛速度较慢。接近最佳点时,SDA具有更好的稳定性,并且收敛速度更快。这可能会导致搜索代理陷入局部最优状态,从而导致解决方案的准确性较低。 HSDBC利用BFA的趋化策略以及SDA的适合度和收敛速度来克服仅与SDA和BFA算法相关的问题。对由此开发的HSDBC进行了评估,以优化两个高度非线性平台的性能和能耗,即具有延长杆的单倒置双摆式车辆。与BFA和SDA的比较结果表明,该算法能够使高度非线性系统具有更好的性能。

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