NDLI: Expert rule based time optimal control of crane loads

Content Provider	IEEE Xplore Digital Library
Author	Moon, M.S. VanLandingham, H.F. Beliveau, Y.J.
Copyright Year	1996
Description	Author affiliation: Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA (Moon, M.S.)
Abstract	A fourth-order model is developed for a crane-load system. From this model a time optimal control scheme with input constraints is investigated for transferring the crane load with swing angle regulation. Rather than following a conventional numerical method approach for solving the two point boundary value problem, a rule-based approach inspired by the manual crane operation is proposed. It is shown that the time optimal control problem becomes the determination of the switching times. Based on the heuristics obtained, a set of expert rules is generated for the adjustment of the switching times. A simple iteration method for obtaining the optimal switching times is presented which provides an alternative solution when there is no analytical expression for a solution. From collected data a lookup table is generated. By incorporating an interpolation algorithm it is possible to transfer the crane load an arbitary distance without load pendulation at the destination in minimum time.
Starting Page	602
Ending Page	607
File Size	658141
Page Count	6
File Format	PDF
ISBN	0780329759
DOI	10.1109/CCA.1996.558928
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-09-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimal control Cranes Artificial neural networks Control systems Boundary value problems Interpolation Safety Moon Manuals Table lookup
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Fuzzy time optimal control of crane load

On the neuro-genetic approach for determining optimal control of a rotary crane

Research and Design of Tower Crane Condition Monitoring and Fault Diagnosis System

Genetic algorithms solution for unconstrained optimal crane control

Research on Control Method of Neural Network for Stacker Crane

Timing specification and rule-based systems

Development of Soft Sensor for Sensorless Automatic Gantry Crane Using RBF Neural Networks

Time optimal control of mobile robot motion using neural nets

Neural network based decoupling control of lifting of 7500t floating crane vessel

Expert rule based time optimal control of crane loads

Similar Documents

Fuzzy time optimal control of crane load

On the neuro-genetic approach for determining optimal control of a rotary crane

Research and Design of Tower Crane Condition Monitoring and Fault Diagnosis System

Genetic algorithms solution for unconstrained optimal crane control

Research on Control Method of Neural Network for Stacker Crane

Timing specification and rule-based systems

Development of Soft Sensor for Sensorless Automatic Gantry Crane Using RBF Neural Networks

Time optimal control of mobile robot motion using neural nets

Neural network based decoupling control of lifting of 7500t floating crane vessel

Expert rule based time optimal control of crane loads