On hybrid intelligence-based control approach with its application to flexible robot system

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• 作者：E. Khoobjou ; A. H. Mazinan
• 关键词：Flexible robot system ; Intelligence ; based control approach ; Particle swarm optimization
• 刊名：Human-centric Computing and Information Sciences
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：7
• 期：1
• 全文大小：3213KB
• 刊物主题：Computer Systems Organization and Communication Networks; Communications Engineering, Networks; Information Systems and Communication Service; Information Systems Applications (incl.Internet); User In
• 出版者：Springer Berlin Heidelberg
• ISSN：2192-1962
• 卷排序：7

文摘

Flexible robot system is in general taken into real consideration as most important process in a number of academic and industrial environments. Due to the fact that the aforementioned system is so applicable in real domains, the novel ideas with respect to state-of-the-art in outperforming its performance are always valuable. With this purpose, a number of the soft computing techniques can be preferred with reference to the traditional ones to predict and optimize the overall performance of the above-captioned process. The approach proposed here is in fact organized in line with the integration of the fuzzy-based approach in association with the neural networks, in order to enable the process under control to be capable of learning and adapting to be matched, in a number of real environments. It can be shown that the outcomes tolerate the imprecise circumstances, as one of advantages regarding the fuzzy-based approach. In the present investigation, a new hybrid approach is proposed to deal with the arm of flexible robot system through the neural networks, the fuzzy-based approach and also the particle swarm optimization. It should be noted that the objective of the proposed research is to control the claw of robot system including two-degree-of-freedom movable arms. The results indicate that the mean-square error and the root-mean-square error are accurately outperformed with reference to the traditional ones, tangibly.