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Spiral-based Manta Ray Foraging Optimization to Optimize PID Control of a Flexible Manipulator

机译:基于螺旋的Manta射线觅食优化,优化柔性机械手的PID控制

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This paper presents a Spiral-based Manta Ray Foraging Algorithm (SMRFO). It is an improvement of Manta Ray Foraging Algorithm (MRFO). The original MRFO has a competitive performance in terms of its accuracy in locating an optimal solution. Its performance can be improved further provided the balanced exploration and exploitation strategies throughout a search operation are improved. A modification in the Somersault phase of the MRFO is proposed. A spiral strategy is incorporated into the Somersault phase of the MRFO. This is to guide all agents toward the best agent in spiral-based trajectory in every iteration. The spiral strategy also offers a dynamic step size scheme for all search agents during the operation. The proposed algorithm is tested on a set of benchmark functions that consist of various fitness landscapes. In terms of solving an engineering application, the proposed algorithm is applied to optimize a PID controller for a flexible manipulator system. Result of the accuracy performance test on benchmark functions shows that the proposed algorithm outperforms the original MRFO significantly. In solving the engineering problem, both SMRFO and MRFO optimize the PID control adequately good. The SMRFO-PID control tracks the bang-bang test input better than the MRFO-PID. It confirms the superiority of the SMRFO over the MRFO.
机译:本文介绍了一种基于螺旋的Manta射线觅食算法(SMRFO)。它是曼塔射线觅食算法(MRFO)的改进。原始MRFO在定位最佳解决方案方面具有竞争性能。它可以进一步提高其性能,提供了在搜索操作中的平衡勘探和开发策略得到改善。提出了MRFO的Somersaule阶段的修改。将螺旋策略纳入MRFO的糖箭阶段。这是在每次迭代中指导所有代理人朝向基于螺旋轨迹的最佳代理。螺旋策略还为操作期间提供所有搜索代理的动态步长方案。所提出的算法在一组基准函数上进行测试,该函数包括各种健身景观。在解决工程应用方面,应用了所提出的算法来优化用于柔性机械手系统的PID控制器。基准函数的精度性能测试的结果表明,所提出的算法显着优于原始的MRFO。在解决工程问题时,SMRFO和MRFO都充分优化了PID控制。 SMRFO-PID控制器比MRFO-PID更好地跟踪Bang-Bang测试输入。它证实了SMRFO对MRFO的优越性。

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