Assessment of a Robust Algorithm for the Detection and Diagnosis of Additive Faults

2006 ◽  
Author(s):  
Vasilis K. Dertimanis ◽  
Dimitris V. Koulocheris ◽  
Constantinos N. Spentzas
Keyword(s):  
System Identification ◽  
Input Output ◽  
Detection Problem ◽  
Identification Procedure ◽  
Single Input Single Output ◽  
Single Output ◽  
Robustness To Noise ◽  
Single Input ◽  
Detection And Diagnosis ◽  
Identification Techniques

This paper addresses the problem of additive faults (such as input/output sensor and actuator) in a dynamic system, from the view of system identification techniques. The relation between the residuals of the model–based fault diagnosis and the innovations of the system identification procedure is implemented and corresponding algorithms are extracted for the tracking of additive faults, while robustness to noise and disturbances is issued. The study is initiated using single input-single output models and extended to multiple inputs-multiple outputs structures. Furthermore, the detection problem of additive faults for systems with unobservable excitation is examined.

Series-Parallel and Parallel Identification Schemes for a Class of Continuous Nonlinear Systems

1977 ◽  
Vol 99 (2) ◽  
pp. 137-140
Author(s):  
Masayoshi Tomizuka
Keyword(s):  
Identification Algorithm ◽  
Input Output ◽  
Single Input Single Output ◽  
Identification Schemes ◽  
Linear Dynamic ◽  
Single Output ◽  
Single Input ◽  
Static Part ◽  
Nonlinear Static ◽  
The Stability

This technical brief deals with the identification of a single-input, single-output nonlinear system which is composed of a nonlinear static part and a linear dynamic part. A series-parallel identification algorithm and a parallel identification algorithm are presented; they require the input, output, and the order of the linear dynamic portion of the system. The stability of the algorithms is assured by Popov’s hyperstability theorem. The effectiveness of the identification schemes developed is demonstrated by computer simulation.

System Identification and Multivariate Controller Design for a Satellite Ultraquiet Isolation Technology Experiment (SUITE)

2002 ◽  
Author(s):  
Alok A. Joshi ◽  
Won-jong Kim
Keyword(s):  
Vibration Isolation ◽  
Transfer Functions ◽  
Controller Design ◽  
Input Output ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Single Input Single Output ◽  
Single Output ◽  
Single Input ◽  
Six Degree Of Freedom

A mathematical model of a six-degree-of-freedom hexapod system for vibration isolation was derived in the discrete-time domain on the basis of the experimental data obtained from a satellite. Using Box-Jenkins model structure, the transfer functions between six piezoelectric actuator input voltages and six geophone sensor output voltages are identified empirically. The 6×6 transfer function matrix is symmetric, and its off-diagonal terms indicate the coupling among different input/output channels. Though the coupling was observed among various input/output channels up to 10 Hz, the single-input single-output (SISO) controllers were designed neglecting the effect of coupling. The SISO controllers demonstrated limited performance in vibration attenuation. Using multi-input multi-output (MIMO) control techniques such as Linear Quadratic Gaussian (LQG) and H∞, high-order controllers were developed. The simulation results using these controllers obtain 33 dB, and 12 dB attenuation at 5, and 25 Hz corner frequencies, respectively.

scholarly journals A representation theorem for linear discrete-space systems

1998 ◽  
Vol 4 (5) ◽  
pp. 369-375 ◽  
Author(s):  
Irwin W. Sandberg
Keyword(s):  
Linear Systems ◽  
Discrete Time ◽  
Representation Theorem ◽  
Additional Term ◽  
Discrete Space ◽  
Space Systems ◽  
Input Output ◽  
Single Input Single Output ◽  
Single Output ◽  
Single Input

The cornerstone of the theory of discrete-time single-input single-output linear systems is the idea that every such system has an input–output mapHthat can be represented by a convolution or the familiar generalization of a convolution. This thinking involves an oversight which is corrected in this note by adding an additional term to the representation.

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