NDLI: Application of neuro-genetic techniques in solving Industrial Crane kinematic control problem

Content Provider	IEEE Xplore Digital Library
Author	Valera, J. Irigoyen, E. Gomez-Garay, V. Artaza, F.
Copyright Year	2009
Description	Author affiliation: Automotive Unit, ROBOTIKER Tecnalia, Zamudio, Spain (Valera, J.) \|\| System Engineering and Automation Dept., University of the Basque Country, UPV/EHU, Bilbao, Spain (Irigoyen, E.; Gomez-Garay, V.; Artaza, F.)
Abstract	This work presents a solution to solve Industrial Cranes kinematic control problem also called Automatic Travel Control (ATC) [10]. Aspects such as optimal trajectory reference calculation considering: process cycle time and distance travelled minimization, improvements in mechanical transmission systems useful life, prohibited areas and obstacles in the crane workspace, etc., and load position control with close tracking of trajectory reference avoiding excessive load swinging angles too, are analyzed and tackled applying Intelligent Control Techniques based on Genetic Algorithms and Neural Networks. The use of numerical and Hardware in the Loop (HiL) simulations, together with rapid prototyping advanced tools make quick changes and fast iterations between conceptual, preliminary, detailed, prototyping and validation design stages possible, allowing to reduce embedded control system development time and also increasing industrial crane overall quality.
Starting Page	1
Ending Page	7
File Size	10429527
Page Count	7
File Format	PDF
ISBN	9781424441945
DOI	10.1109/ICMECH.2009.4957204
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-14
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Industrial control Cranes Kinematics Electrical equipment industry Automatic control Trajectory Virtual prototyping Minimization methods Position control Algorithm design and analysis Rapid Prototyping component Kinematic Control Trajectory calculation Multiobjective Optimization Genetic Algorithms Predictive Control Neural Network Embedded system
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
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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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