Autonomous control reconfiguration

This article looks at autonomous control reconfiguration, particularly as it relates to fault accommodation and learning systems. To illustrate the types of difficulties encountered and to serve as a focus, two specific approaches are presented. The first approach uses multiple models to represent uncertain system characteristics. The example application is interceptor terminal guidance with unknown target maneuvers. The second approach uses a single model with adaptive techniques for updating uncertain system characteristics.

[1]  Ching-Fang Lin,et al.  Failure detection and isolation structure for global positioning system autonomous integrity monitoring , 1995 .

[2]  Gerald S. Nurre,et al.  Preservicing mission - On-orbit modifications to Hubble Space Telescope pointing control system , 1995 .

[3]  Emmanuel G. Collins,et al.  Linear-quadratic-Gaussian-based controller design for Hubble Space Telescope , 1995 .

[4]  Yoshimasa Ochi.  APPLICATION OF FEEDBACK LINEARIZATION METHOD IN A DIGITAL RESTRUCTURABLE FLIGHT CONTROL SYSTEM , 1993 .

[5]  Jonathan S. Litt,et al.  Sensor fault detection and diagnosis for a T700 turboshaft engine , 1995 .

[6]  Chin-Teng Lin,et al.  Neural-Network-Based Fuzzy Logic Control and Decision System , 1991, IEEE Trans. Computers.

[7]  Donald F. Specht,et al.  Probabilistic neural networks , 1990, Neural Networks.

[8]  M. Agarwal,et al.  A systematic classification of neural-network-based control , 1994, 1994 Proceedings of IEEE International Conference on Control and Applications.

[9]  H. E. Rauch,et al.  Augmentation of an extended Kalman filter with a neural network , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[10]  P.J. Antsaklis,et al.  Intelligent Learning Control , 1995, IEEE Control Systems.

[11]  Cuiping Li,et al.  Hybrid approach for damage detection in flexible structures , 1995 .

[12]  Angelia P. Bukley,et al.  Hubble Space Telescope Pointing Control System Design Improvement Study Results , 1995 .

[13]  Kevin M. Passino,et al.  Intelligent control for autonomous systems , 1995 .

[14]  S. Engell,et al.  Approximately time-optimal fuzzy control of a two-tank system , 1994, IEEE Control Systems.

[15]  R. Stenz,et al.  Automation of a batch distillation column using fuzzy and conventional control , 1995, IEEE Trans. Control. Syst. Technol..

[16]  Raphael T. Haftka,et al.  The cost of model reference adaptive control - Analysis, experiments, and optimization , 1994 .

[17]  Herbert Rauch,et al.  Fault detection, isolation, and reconfiguration for aircraft using neural networks , 1993 .

[18]  Marcello R. Napolitano,et al.  On-Line Learning Nonlinear Direct Neurocontrollers for Restructurable Control Systems , 1995 .

[19]  Tae W. Lim,et al.  Structural damage detection using constrained eigenstructure assignment , 1995 .

[20]  Kevin M. Passino,et al.  Fuzzy model reference learning control for cargo ship steering , 1993 .

[21]  Stephen Yurkovich,et al.  Fuzzy learning control for a flexible-link robot , 1995, IEEE Trans. Fuzzy Syst..

[22]  H.E. Rauch.  Intelligent fault diagnosis and control reconfiguration , 1994, IEEE Control Systems.

[23]  Douglas A. Lawrence,et al.  Analytically and numerically derived H-infinity controller designs for Hubble Space Telescope , 1995 .

[24]  C. Johnson,et al.  Dual-mode disturbance-accommodating pointing controller for Hubble Space Telescope , 1995 .

[25]  Jie Chen,et al.  Review of parity space approaches to fault diagnosis for aerospace systems , 1994 .

[26]  Y. Ochi.  Application of Restructurable Flight Control System to Large Transport Aircraft , 1995 .

[27]  Robert F. Stengel,et al.  Restructurable control using proportional-integral implicit model following , 1990 .

[28]  Ren Da,et al.  Failure detection of dynamical systems with the state chi-square test , 1994 .

[29]  Donald F. Specht,et al.  A general regression neural network , 1991, IEEE Trans. Neural Networks.

[30]  K. Grigoriadis,et al.  Covariance control design for Hubble Space Telescope , 1995 .

[31]  L X Wang,et al.  Fuzzy basis functions, universal approximation, and orthogonal least-squares learning , 1992, IEEE Trans. Neural Networks.

[32]  T. Arie,et al.  An adaptive steering system for a ship , 1986, IEEE Control Systems Magazine.

[33]  J. A. Leonard,et al.  Radial basis function networks for classifying process faults , 1991, IEEE Control Systems.

[34]  Kevin M. Passino,et al.  Expert supervision of fuzzy learning systems for fault tolerant aircraft control , 1995 .

[35]  Y. Abu-Mostafa.  Machines that Learn from Hints , 1995 .

[36]  Kumpati S. Narendra,et al.  Adaptation and learning using multiple models, switching, and tuning , 1995 .