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Issue title: Recent Advances in Soft Computing: Theories and Applications
Article type: Research Article
Authors: Roy, Shibendu Shekhar | Pratihar, Dilip Kumar
Affiliations: Department of Mechanical Engineering, National Institute of Technology, Durgapur, India | Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, India
Note: [] Corresponding author. Shibendu Shekhar Roy, Department of Mechanical Engineering, National Institute of Technology, Durgapur, India. E-mails: ssroy99@yahoo.com (Shibendu Shekhar Roy) and dkpra@mech.iitkgp.ernet.in (Dilip Kumar Pratihar).
Abstract: In this paper, adaptive neuro-fuzzy expert systems have been designed to predict specific energy consumption and normalized energy stability margin for crab walking of a six-legged robot. The application of this technique for crab gait generation of the six-legged robot is new, to the best of the authors' knowledge. Three approaches based on adaptive neuro-fuzzy inference system have been developed and their performances are compared with each other. Genetic algorithm-tuned multiple adaptive neuro-fuzzy inference systems are found to perform better than other approaches. This could be due to a more exhaustive search carried out by the genetic algorithm compared to back-propagation algorithm and the use of two separate adaptive neuro-fuzzy inference systems for two different outputs.
Keywords: Expert systems, adaptive neuro-fuzzy systems, six-legged robot, specific energy consumption, stability margin
DOI: 10.3233/IFS-2012-0567
Journal: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 3, pp. 467-482, 2013
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