NDLI: Hybridisation of neural networks and genetic algorithms for time-optimal control

Content Provider	IEEE Xplore Digital Library
Author	Chaiyaratana, N. Zalzala, A.M.S.
Copyright Year	1999
Description	Author affiliation: Dept. of Production Eng., King Mongkut's Inst. of Technol., Bangkok, Thailand (Chaiyaratana, N.)
Abstract	This paper presents the use of neural networks and genetic algorithms in time-optimal control of a closed-loop robotic system. Radial-basis function networks are used in conjunction with PID controllers in an independent joint position control to reduce tracking errors. The results indicate that using neural network controllers is more effective than using the trajectory pre-shaping scheme, reported in early literature. Subsequently, a genetic algorithm with a weighted-sum approach and a multi-objective genetic algorithm (MOGA) are used to solve a multi-objective optimisation problem related to time-optimal control. The results indicate that the MOGA is the best method in terms of the Pareto front coverage while the genetic algorithm with a weighted-sum approach is more effective in terms of finding the best individual according to the weighted-sum criteria. As a result of using both neural networks and genetic algorithms in this application, an idea of a task hybridisation between neural networks and genetic algorithms for use in a control system is also effectively demonstrated.
Starting Page	389
Ending Page	396
File Size	819704
Page Count	8
File Format	PDF
ISBN	0780355369
DOI	10.1109/CEC.1999.781951
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-07-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Genetic algorithms Robots Control systems Actuators Shape control Torque Open loop systems Motion control Optimal control
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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