Showing papers by "Ron J. Patton published in 1994"

Review of parity space approaches to fault diagnosis for aerospace systems

Abstract: This paper provides a tutorial review of the state of the art in parity space fault diagnosis approaches with particular emphasis on aerospace systems. The basic concepts and definitions are given and a consistent framework is presented to draw together the important links amongst the known methods for fault diagnosis. Residual generation in the parity space has been recognized as a core element in this framework. The robustness and isolation problems are the main focus of the paper. Recent research topics on robust fault diagnosis are outlined, and new ideas as to how the parity space approach can be used to deal with robustness are discussed.

Fault diagnosis in nonlinear dynamic systems via neural networks

Abstract: This paper proposes a new approach for detecting and isolating faults in nonlinear dynamic processes using neural networks. Two stages are involved. The first is to generate residual signals based on a comparison between the actual and predicated states. A multilayer perceptron network is trained to predict the future system states based on the current system inputs and states. The paper shows that a satisfactory accurate state prediction for the nonlinear dynamic system can be achieved in this way. In the second stage of fault detection and isolation, a neural network is trained to classify characteristics contained in the residuals. Hence, based on the classification given by the network, faults can be detected and isolated. The developed techniques are demonstrated in a laboratory 3-tanks system and promising results are described.< >

Robust control design via eigenstructure assignment, genetic algorithms and gradient-based optimisation

Abstract: The paper presents a new approach for robust control design of multivariable systems via eigenstructure assignment, genetic algorithms and gradient-based optimisation. It takes the combination of the sensitivity and the complementary sensitivity functions of the closed-loop system as the robust control performance index. The gradient calculation of the performance index is described in detail for the closed-loop system with real and complex eigenvalues. The paper makes full use of the freedom provided by eigenstructure assignment to find a controller which stabilises the closed-loop system and minimises the performance index via the combination of genetic algorithms and gradient-based optimisation. The simulation results for the design of a lateral flight control system provide a tutorial demonstration of the power of the method.

Robust fault diagnosis of stochastic systems with unknown disturbances

Abstract: This paper studies the robust fault diagnosis of stochastic systems with unknown disturbances based on a full order observer. This observer can give disturbance decoupling minimum variance state estimation for time-varying systems with both noise and unknown disturbances. The existence condition and the design procedure are presented in the paper. The output estimation error with disturbance decoupling and minimum variance properties is used as a residual signal to diagnose faults. The developed method is applied to an illustrative example and simulation results show that the approach taken is able to detect faults reliably in the presence of both modelling errors and noise. >

Detecting incipient sensor faults in flight control systems

Abstract: This paper develops a new approach to the design of optimal observer-based residual generators for detecting incipient faults in flight control systems To reduce false and missed alarm rates in fault detection, a number of performance indices are introduced into the observer design These indices are ezpressed in the frequency domain to take account of the frequency distributions of faults, noise and modelling uncertainty To solve the design problem, these performance indices are niized together using diflerent weighting factors as a single performance index The genetic algorithm is thus used to search an optimal solution to minimize this design objective The approach developed is applied to a flight control system example and simulation results show that incipient sensor faults can be detected reliably in the presence of modelling uncertainty