H ∞ Detection Filter Design for Linear Systems: Comparison of Two Approaches

Edelmayer, András; Bokor, József; Keviczky, László

doi:10.1016/s1474-6670(17)58701-7

Cited by 34 publications

(20 citation statements)

References 7 publications

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“…It has to be noted, that this method is often referred to, see e.g. in [1], [2] and [20], [21], but we have not found any algorithm about it. This has been the motivation for its description.…”

Section: Solution Of the Mfare By A Gamma-iteration Algorithmmentioning

confidence: 76%

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Solving of the Modified Filter Algebraic Riccati Equation for H-infinity fault detection filtering

Horváth

Edelmayer

2017

Acta Universitatis Sapientiae Electrical and Mechanical Engineering

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Abstract:The objective of this paper is solving of the Modified Filter Algebraic Riccati Equation (MFARE) for calculating of the filter gain. The results are used for model-based fault detection filtering of faults in the air path of diesel engines. The Hinfinity optimization approach requires the solution of a linear-quadratic optimization problem that leads to the solution of MFARE. In our paper two basic concepts for solving MFARE are examined, namely the analytically implemented gamma-iteration and casting the problem as a convex optimization problem based on Linear Matrix Inequalities (LMIs).The algorithms are implemented in MATLAB. Each algorithm has to ensure the condition for a global convergence and also has to deliver an optimal solution. Not at least, the computational cost has to be as small as possible.

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Section: Solution Of the Mfare By A Gamma-iteration Algorithmmentioning

confidence: 76%

“…This method requires the solution of a linear-quadratic optimization problem that leads to the solution of the Modified Filter Algebraic Riccati Equation (MFARE), see e.g. in [1], [2], [3] and [4].…”

Section: Introductionmentioning

confidence: 99%

Solving of the Modified Filter Algebraic Riccati Equation for H-infinity fault detection filtering

Horváth

Edelmayer

2017

Acta Universitatis Sapientiae Electrical and Mechanical Engineering

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“…In Reference [9] a different approach was presented which, with certain assumptions, requires the solution of a single Riccati equation. Reference [10] gives the comparison of the two ideas by showing that the different approaches share the common concept of using an auxiliary representation of the original system (1). The auxiliary representation is based on a generalized model of the plant.…”

Section: The Basic Solution To H 1 Filteringmentioning

confidence: 99%

Optimal H_∞ scaling for sensitivity optimization of detection filters

Edelmayer

Bokor

2002

Intl J Robust & Nonlinear

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SUMMARYThe paper deals with the sensitivity optimization of detection filters in linear time-varying (LTV) systems which are subject to multiple simultaneous faults and disturbances. The robust fault detection filter design problem as a scaled H 1 filtering problem is considered. The effect of two different input scaling approaches to the optimization process is investigated. The objective is to provide the smallest scaled L 2 gain of the unknown input of the system that is guaranteed to be less than a prespecified level, i.e., to produce a filter with optimal disturbance suppression capability in such a way that sufficient sensitivity to failure modes should still be maintained. It is shown how to obtain bounds on the scaled L 2 gain by transforming the standard H 1 filtering problem into a convex feasibility problem, specifically, a structured, linear matrix inequality (LMI). Numerical examples demonstrating the effect of the scaled optimization with respect to conventional H 1 filtering is presented.

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“…Using X, optimization for the design of the residual generator H in (6) or in (7) is an attractive method, [2,3,8,12]. However, in the case where G f include nonminimum phase zeros, the % , optimization method will not in general result in a useful residual generator.…”

Section: E = Z -Imentioning

confidence: 99%

Fault diagnosis for non-minimum phase systems using /spl Hscr//sub /spl infin// optimization

Niemann

Stoustrup²

2001

Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148)

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H ∞ Detection Filter Design for Linear Systems: Comparison of Two Approaches

Cited by 34 publications

References 7 publications

Solving of the Modified Filter Algebraic Riccati Equation for H-infinity fault detection filtering

Solving of the Modified Filter Algebraic Riccati Equation for H-infinity fault detection filtering

Optimal H_∞ scaling for sensitivity optimization of detection filters

Fault diagnosis for non-minimum phase systems using /spl Hscr//sub /spl infin// optimization

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H ∞ Detection Filter Design for Linear Systems: Comparison of Two Approaches

Cited by 34 publications

References 7 publications

Solving of the Modified Filter Algebraic Riccati Equation for H-infinity fault detection filtering

Solving of the Modified Filter Algebraic Riccati Equation for H-infinity fault detection filtering

Optimal H∞ scaling for sensitivity optimization of detection filters

Fault diagnosis for non-minimum phase systems using /spl Hscr//sub /spl infin// optimization

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Product

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Optimal H_∞ scaling for sensitivity optimization of detection filters