Bounding set calculation for neural network-based output feedback adaptive control systems

Evaluating the bounding set of dynamic systems subject to direct neural-adaptive control is a critical issue in applications where the control system must undergo a rigorous verification process in order to comply with certification standards. In this paper, the boundedness problem is addressed for...

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Bibliographic Details
Published in:Neural computing & applications 2011-04, Vol.20 (3), p.373-387
Main Authors: Campa, Giampiero, Fravolini, Mario Luca, Mammarella, Marco, Napolitano, Marcello R.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial Intelligence
Combinatorics
Combinatorics. Ordered structures
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer science
control theory
systems
Data Mining and Knowledge Discovery
Designs and configurations
Exact sciences and technology
Experimental design
Image Processing and Computer Vision
Inference from stochastic processes
time series analysis
Learning and adaptive systems
Mathematics
Original Article
Probability and statistics
Probability and Statistics in Computer Science
Sciences and techniques of general use
Statistics
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Summary:Evaluating the bounding set of dynamic systems subject to direct neural-adaptive control is a critical issue in applications where the control system must undergo a rigorous verification process in order to comply with certification standards. In this paper, the boundedness problem is addressed for a comprehensive class of uncertain dynamic systems. Several common but unnecessary approximations that are typically performed to simplify the Lyapunov analysis have been avoided in this effort. This leads to a more accurate and general formulation of the bounding set for the overall closed loop system. The conditions under which boundedness can be guaranteed are carefully analyzed; additionally, the interactions between the control design parameters, the ‘Strictly Positive Realness’ condition, and the shape and dimensions of the bounding set are discussed. Finally, an example is presented in which the bounding set is calculated for the neuro-adaptive control of an F/A-18 aircraft, along with a numerical study to evaluate the effect of several design parameters.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-010-0404-6