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Title: Adaptive critic based neurocontroller for autolanding of aircraft with varying glideslopes
Author (s): Saini, G.
Balakrishnan, S. N.
Department/Lab Affiliations: Mechanical & Aerospace Engineering
Keywords: adaptive critic
aircraft
aircraft landing guidance
attitude control
autolanding
closed loop system
closed loop systems
glideslopes
learning systems
longitudinal dynamics
neural networks
neurocontrollers
optimal control
optimal control
wind disturbances
Issue Date: 1997
Publisher: Institute of Electrical and Electronics Engineers
Citation: Saini, G.; Balakrishnan, S. N.; Person, C. "Adaptive critic based neurocontroller for autolanding of aircraft with varying glideslopes" International Conference on Neural Networks,1997. 9-12 Jun 1997 Pages:2288-2293 vol.4
Abstract: In this paper, adaptive critic based neural networks have been used to design a controller for a benchmark problem in aircraft autolanding. The adaptive critic control methodology comprises successive adaptations of two neural networks, namely `action' and `critic' networks until closed loop optimal control is achieved. The autolanding problem deals with longitudinal dynamics of an aircraft which is to be landed in a specified touchdown region in the presence of wind disturbances and gusts using elevator deflection as the control for glideslope and flare modes. The performance of the neurocontroller is compared to that of a conventional PID controller. Neurocontroller's capabilities are further explored by making it more generic and versatile in the sense that the glideslope angle can be changed at will during the landing process. Flight paths (trajectories) obtained for a wide range of glideslope angles in presence of wind gusts are compared with the optimal flight paths which are obtained by solving the linear quadratic regulator formulation using conventional optimal control theory
Type: Article - Conference proceedings
text
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titleAdaptive critic based neurocontroller for autolanding of aircraft with varying glideslopes
contributor.authorSaini, G.
contributor.authorBalakrishnan, S. N.
contributor.deptlabMechanical & Aerospace Engineering
subjectadaptive critic
subjectaircraft
subjectaircraft landing guidance
subjectattitude control
subjectautolanding
subjectclosed loop system
subjectclosed loop systems
subjectglideslopes
subjectlearning systems
subjectlongitudinal dynamics
subjectneural networks
subjectneurocontrollers
subjectoptimal control
subjectoptimal control
subjectwind disturbances
date.issued1997
date.submitted2007
publisherInstitute of Electrical and Electronics Engineers
identifier.citationSaini, G.; Balakrishnan, S. N.; Person, C. "Adaptive critic based neurocontroller for autolanding of aircraft with varying glideslopes" International Conference on Neural Networks,1997. 9-12 Jun 1997 Pages:2288-2293 vol.4
identifier.pub.URI
http://ieeexplore.ieee.org/iel3/4831/13362/00614409.pdf?arnumber=61440
description.abstractIn this paper, adaptive critic based neural networks have been used to design a controller for a benchmark problem in aircraft autolanding. The adaptive critic control methodology comprises successive adaptations of two neural networks, namely `action' and `critic' networks until closed loop optimal control is achieved. The autolanding problem deals with longitudinal dynamics of an aircraft which is to be landed in a specified touchdown region in the presence of wind disturbances and gusts using elevator deflection as the control for glideslope and flare modes. The performance of the neurocontroller is compared to that of a conventional PID controller. Neurocontroller's capabilities are further explored by making it more generic and versatile in the sense that the glideslope angle can be changed at will during the landing process. Flight paths (trajectories) obtained for a wide range of glideslope angles in presence of wind gusts are compared with the optimal flight paths which are obtained by solving the linear quadratic regulator formulation using conventional optimal control theory
typeArticle - Conference proceedings
type.DCMITypetext
type.statusFinal version
rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
rights.URI
http://www.ieee.org/web/publications/rights/policies.html
date.accessioned2007-04-05T14:02:29Z
date.available2007-04-05T14:02:29Z
identifier.persist.URI
http://scholarsmine.mst.edu/post_prints/00614409_09007dcc8030c04f.html
Full Text
00614409_09007dcc8030c054.pdf