Intelligent failure-tolerant control

An overview of failure-tolerant control is presented, focusing on the control of continuous-time dynamic systems (or plants) whose motions can be represented by integrals of nonlinear ordinary differential equations. Failure tolerance may be called upon to improve system reliability, maintainability, and survivability, and the issues attached to achieving these goals are examined. Robustness, which is required in some degree by all failure-tolerant systems, is discussed. The use of parallel redundancy is examined. Analytical redundancy, the principal functions of which are failure detection, failure identification, and control-system reconfiguration, is also considered. The use of expert systems and neural networks is discussed.<<ETX>>

[1]  Robert F. Stengel,et al.  PERSPECTIVES ON THE USE OF RULE-BASED CONTROL , 1989 .

[2]  Robert F. Stengel,et al.  Rule-Based Mechanisms of Learning for Intelligent Adaptive Flight Control , 1988, 1988 American Control Conference.

[3]  Robert F. Stengel,et al.  Perspectives on the Use of Rule-Based Control , 1988 .

[4]  Robert F. Stengel,et al.  Neural Networks for Function Approximation in Nonlinear Control , 1990, 1990 American Control Conference.

[5]  Marvin Minsky,et al.  Perceptrons: An Introduction to Computational Geometry , 1969 .

[6]  Michael G. Safonov,et al.  Correction to "Feedback properties of multivariable systems: The role and use of the return difference matrix" , 1982 .

[7]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[8]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[9]  A. Willsky,et al.  Analytical redundancy and the design of robust failure detection systems , 1984 .

[10]  A. Laub,et al.  Feedback properties of multivariable systems: The role and use of the return difference matrix , 1981 .

[11]  E. Zafiriou,et al.  Use of neural networks for sensor failure detection in a control system , 1990, IEEE Control Systems Magazine.

[12]  Michèle Basseville,et al.  Detection of Changes in Signals and Systems , 1987 .

[13]  John E. Freund,et al.  Probability and statistics for engineers , 1965 .

[14]  R. Stengel,et al.  Technical notes and correspondence: Stochastic robustness of linear time-invariant control systems , 1991 .

[15]  R. E. Kalman,et al.  When Is a Linear Control System Optimal , 1964 .

[16]  J. Searle,et al.  Is the brain's mind a computer program? , 1990, Scientific American.

[17]  S. Osder.  The DC-9-80 digital flight guidance system's monitoring techniques , 1979 .

[18]  T Poggio,et al.  Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks , 1990, Science.

[19]  U. Shaked,et al.  On the robustness of LQ regulators , 1984 .

[20]  S. Bhattacharyya,et al.  Robust control , 1987, IEEE Control Systems Magazine.

[21]  William C. Carter,et al.  Reliability Modeling for Fault-Tolerant Computers , 1971, IEEE Transactions on Computers.

[22]  K.M. Passino,et al.  Neural computing for numeric-to-symbolic conversion in control systems , 1989, IEEE Control Systems Magazine.

[23]  Alan S. Willsky,et al.  A survey of design methods for failure detection in dynamic systems , 1976, Autom..

[24]  Pamela McCorduck,et al.  Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence , 1979 .

[25]  Dan T. Horak.  Failure detection in dynamic systems with modeling errors , 1988 .

[26]  D.A. Handelman,et al.  Integrating neural networks and knowledge-based systems for intelligent robotic control , 1990, IEEE Control Systems Magazine.

[27]  Lawrence Birnbaum,et al.  The Organization of Expert Systems, A Tutorial , 1982, Artif. Intell..

[28]  R. Stengel.  Stochastic Optimal Control: Theory and Application , 1986 .

[29]  Robert F. Stengel,et al.  Stochastic Stability and Performance Robustness of Linear Multivariable Systems , 1990, 1990 American Control Conference.

[30]  Robert F. Stengel.  COMBINING QUANTITATIVE AND QUALITATIVE REASONING IN AIRCRAFT FAILURE DIAGNOSIS. , 1985 .

[31]  John C. Doyle,et al.  Guaranteed margins for LQG regulators , 1978 .

[32]  Robert F. Stengel.  Some effects of bias errors in redundant flight control systems. , 1972 .

[33]  R. M. Tong,et al.  A control engineering review of fuzzy systems , 1977, Autom..

[34]  Michèle Basseville,et al.  Detecting changes in signals and systems - A survey , 1988, Autom..

[35]  Derrick H. Nguyen,et al.  Neural networks for self-learning control systems , 1990 .

[36]  Robert F. Stengel,et al.  Combining expert system and analytical redundancy concepts for fault-tolerant flight control , 1989 .

[37]  G. Stein,et al.  Multivariable feedback design: Concepts for a classical/modern synthesis , 1981 .

[38]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[39]  John C. Doyle.  Analysis of Feedback Systems with Structured Uncertainty , 1982 .

[40]  Robert F. Stengel,et al.  Failure Model Determination in a Knowledge-Based Control System , 1987, 1987 American Control Conference.

[41]  Sharad Singhal,et al.  Training feed-forward networks with the extended Kalman algorithm , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[42]  Keung-Chi Ng,et al.  Uncertainty management in expert systems , 1990, IEEE Expert.

[43]  A. Willsky,et al.  A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems , 1976 .

[44]  Robert F. Stengel,et al.  Some Effects of Parameter Variations on the Lateral-Directional Stability of Aircraft , 1980 .

[45]  Robert F. Stengel,et al.  An Architecture for Real-Time Rule-Based Control , 1987, 1987 American Control Conference.

[46]  Michael Athans,et al.  The stochastic control of the F-8C aircraft using a multiple model adaptive control (MMAC) method--Part I: Equilibrium flight , 1977 .

[47]  Drew McDermott,et al.  Introduction to artificial intelligence , 1986, Addison-Wesley series in computer science.

[48]  Walter C. Merrill,et al.  Advanced detection, isolation and accommodation of sensor failures: Real-time evaluation , 1988 .

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

[50]  Robert F. Stengel,et al.  Effects of displacement and rate saturation on the control of statically unstable aircraft , 1981 .

[51]  Robert F. Stengel,et al.  Probabilistic reasoning for intelligent wind shear avoidance , 1992 .

[52]  J. S. Levey,et al.  The New Columbia encyclopedia , 1975 .

[53]  Robert F. Stengel,et al.  Stability boundaries for aircraft with unstable lateral-directional dynamics and control saturation , 1989 .

[54]  M.S. Fadali,et al.  Minimum-Time Control of Robotic Manipulators using a Back Propagation Neural Network , 1990, 1990 American Control Conference.

[55]  Masahiro Abe,et al.  Incipient fault diagnosis of chemical processes via artificial neural networks , 1989 .

[56]  T. F. Westermeier.  Redundancy management of digital fly-by-wire systems , 1977 .

[57]  G. Enderlein,et al.  Miller, I., and J. E. Freund: Probability and Statistics for Engineers. Prentice‐Hall, Englewood Cliffs, New Jersey 1965. 432 S., Preis 96. s. , 1968 .

[58]  Robert F. Stengel,et al.  Quantitative knowledge acquisition for expert systems , 1990 .

[59]  Robert F. Stengel,et al.  System Identification for Nonlinear Control Using Neural Networks , 1990 .

[60]  W. Thomas Miller,et al.  Sensor-based control of robotic manipulators using a general learning algorithm , 1987, IEEE J. Robotics Autom..

[61]  Ken-ichi Funahashi,et al.  On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.

[62]  B. Anderson,et al.  Linear Optimal Control , 1971 .

[63]  Michael Athans,et al.  Closed-loop structural stability for linear-quadratic optimal systems , 1976, 1976 IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes.

[64]  James S. Albus,et al.  New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1 , 1975 .

[65]  M. Athans,et al.  Robustness results in linear-quadratic Gaussian based multivariable control designs , 1981 .

[66]  Thomas Ross.  Machines who think. , 1933, Science.