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An Evolutionary Optimal Fuzzy System With Information Fusion of Heterogeneous Distributed Computing and Polar-Space Dynamic Model for Online Motion Control of Swedish Redundant Robots

机译:瑞典冗余机器人在线运动控制的融合异构分布信息和极空间动态模型的进化最优模糊系统

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摘要

This paper presents an evolutionary optimal fuzzy system with information fusion of heterogeneous distributed computing and polar-space dynamic model for online motion control of Swedish redundant robots. The intelligent fuzzy system incorporated with the parallel metaheuristic Bacteria Foraging Optimization (BFO)-Artificial Immune System (AIS), called FS-PBFOAIS and its field-programmable gate array (FPGA) realization to optimal polar-space online motion control of four-wheeled redundant mobile robots. This hybrid paradigm gains the benefits of Taguchi quality method, BFO, AIS, distributed processing, and FPGA technique. Experimental results are conducted to present effective optimization and high accuracy of the proposed FPGA-based FS-PBFOAIS tracking controller. Finally, the comparative works are provided to demonstrate the superiority of the FPGA-based FS-PBFOAIS polar-space redundant controller over other conventional control methods.
机译:提出了一种融合异构分布信息和极空间动态模型信息融合的进化最优模糊系统,用于瑞典冗余机器人的在线运动控制。结合了并行元启发式细菌觅食优化(BFO)-人工免疫系统(AIS)的智能模糊系统,称为FS-PBFOAIS,其现场可编程门阵列(FPGA)实现可实现最佳的四轮极地空间在线运动控制多余的移动机器人。这种混合范例获得了Taguchi质量方法,BFO,AIS,分布式处理和FPGA技术的好处。进行实验结果以提出所建议的基于FPGA的FS-PBFOAIS跟踪控制器的有效优化和高精度。最后,提供了比较工作来证明基于FPGA的FS-PBFOAIS极空冗余控制器相对于其他常规控制方法的优越性。

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