Data processing: artificial intelligence – Fuzzy logic hardware – Digital fuzzy computer
Reexamination Certificate
2000-10-17
2004-07-06
Khatri, Anil (Department: 2121)
Data processing: artificial intelligence
Fuzzy logic hardware
Digital fuzzy computer
C701S019000, C701S020000
Reexamination Certificate
active
06760712
ABSTRACT:
BACKGROUND OF THE INVENTION
The application relates generally to a rail-based transportation system and more particularly to an automatic train handling controller that smoothly handles the locomotive controls while staying within prescribed speed limits.
A rail-based transportation system such as a freight train typically comprises at least one locomotive and about one hundred rail-cars connected together by inter-car couplers. Most of the couplers that are currently used are connected to the rail-cars by a hydraulically damped spring. Since each of the couplers are connected to a hydraulically damped spring at opposite ends, there is a slack zone that allows the rail-cars to move relative to each other while in motion, allowing the train to change length by as much as 50-100 feet. For example, the slack zone will decrease to zero while the train is traveling downhill and using dynamic braking and will expand to its maximum length while the train is traveling uphill. The amount of movement allowed by the couplers depends on the handling of the locomotive controls. Typically, the couplers are subjected to two types of forces (i.e., static and dynamic) that may lead to breakage of the couplers, the brake pipe that prevents the rail-cars from banging in to each other, and the train. Accordingly, the train operator has to be careful in the handling of the locomotive controls so that these forces are not exceeded. In addition, the train operator has to control the locomotive so that the train travels within prescribed speed limits without excess acceleration and braking. Violation of the prescribed speed limits and excess acceleration and braking may lead to derailments and severe cargo damage. Therefore, it is imperative that the train operator handle the locomotive controls smoothly while staying within the prescribed speed limits.
Currently, most locomotives are equipped with only a very simplistic cruise control that uses a linear Proportional Integral (PI) controller. This type of cruise control can only be used below speeds of 10 mph and is primarily used for uniform loading and yard movement and cannot prescribe a braking action. In addition, this type of PI controller does not take into account the slack or distributed dynamics of the couplers in any manner and is not applicable for extended trains traveling at cruising speeds over a variety of terrain. Accordingly, there is a need for a train handling controller that can smoothly manage the slack of the couplers while keeping the train within prescribed speed limits over a varying terrain.
SUMMARY OF THE INVENTION
In one embodiment, there is disclosed a train handling controller that can smoothly manage the slack of the couplers while keeping the train within prescribed speed limits over a varying terrain. In particular, there is disclosed a system and method for tracking a rail-based transportation velocity profile using fuzzy logic that enables this embodiment to manage slack and comply with a prescribed speed limit. In this invention there is a velocity profiler containing a predetermined velocity profile for operating a rail-based transportation system over a specified track profile. In addition, there is a train simulator for simulating an operation of the rail-based transportation system over the specified track profile. A fuzzy logic controller controls the operation of the train simulator in accordance with the predetermined velocity profile. In particular, the fuzzy logic controller tracks error and change in error between the train simulator operation and the predetermined velocity profile and provides a control action to the train simulator that minimizes the error. A safety constraint enforcer which is coupled to the fuzzy logic controller ensures that the control action provided by the fuzzy logic controller is in compliance with a set of predetermined safety constraints.
In a second embodiment, there is disclosed a train handling controller that can smoothly manage the slack of the couplers while keeping the train within prescribed speed limits over a varying terrain. In particular, there is disclosed a train handling controller for controlling operation of a rail-based transportation system according to a predetermined velocity profile and a specified track profile. The train handling controller comprises a look-ahead error module that is responsive to the rail-based transportation system and the predetermined velocity profile. The look-ahead error module determines the look-ahead error and change in look-ahead error. A fuzzy logic control module coupled to the look-ahead error module provides a train handling control action in response to the look-ahead error and change in look-ahead error. A fuzzy terrain matcher determines the rate of change for changing the train handling control action provided by the fuzzy logic control module according to the terrain in the specified track profile. A control scheduler, responsive to the fuzzy logic control module and the fuzzy terrain matcher, generates a schedule for changing the train handling control action according to the determined rate of change.
REFERENCES:
patent: 5436631 (1995-07-01), Magori et al.
patent: 5459665 (1995-10-01), Hikita et al.
patent: 5544059 (1996-08-01), Hikita et al.
patent: 5983144 (1999-11-01), Bonissone et al.
patent: 5995737 (1999-11-01), Bonissone et al.
patent: 6125311 (2000-09-01), Lo
patent: 6243694 (2001-06-01), Bonissone et al.
Automated fuzzy knowledge base generation and tuning Burkhardt, D.G.; Bonissone, P.P.; Fuzzy Systems, 1992., IEEE International Conference on , Mar. 8-12, 1992, pp.: 179-188.*
Fuzzy logic controllers: from development to deployment Bonissone, P.P.; Chiang, K.H.; Neural Networks, 1993., IEEE International Conference on , Mar. 28-Apr. 1, 1993, pp.: 610-619 vol. 1.*
Genetic algorithms for automated tuning of fuzzy controllers: a transportation application Bonissone, P.P.; Khedkar, P.S.; Chen, Y.; Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on , vol.: 1 , 1996 pp.: 674-680□□.*
Industrial applications of fuzzy logic at General Electric Bonissone, P.P.; Badami, V.; Chiang, K.H.; Khedkar, P.S.; Marcelle, K.W.; Schutten, M.J.; Proceedings of the IEEE , vol.: 83 , Issue: 3 , Mar. 1995 pp.: 450-465.*
An antislipping fuzzy logic controller for a railway traction system Garcia-Rivera, M.; Sanz, R.; Perez-Rodriguez, J.A.; Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on , vol.: 1 , Jul. 1-5, 1997 pp.: 119-124 vol. 1.
Bonissone Piero Patrone
Chen Yu-To
Houpt Paul Kenneth
Khedkar Pratap Shankar
Schneiter John Lewis
General Electric Company
Goldman David C.
Holmes Michael B.
Khatri Anil
Patnode Patrick K.
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