Model Weight Estimation for Fdi Using Convex Fault Models

Hallouzi, Redouane; Verhaegen, Michel; Kanev, Stoyan

doi:10.3182/20060829-4-cn-2909.00132

Cited by 8 publications

(8 citation statements)

References 10 publications

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“…which defines the solution of (6a) at t = (k + 1)T d as (8) Assume that A c (p) is invertible (to compute the resulting matrix functions of this discretisation approach, A c (p) is not required to be invertible, but if it is, we can write the resulting DT description of the sate-evolution conveniently as (9a)). By substituting…”

Section: Complete Methodsmentioning

confidence: 99%

“…3.3.3 Trapezoidal (Tustin) method: An alternative way of providing a better approximation than the rectangular method is to use a different approximative evaluation of integral (8). By using a trapezoidal evaluation, we obtain…”

Section: Polynomial (Hanselmann) Methodmentioning

confidence: 99%

“…The derived results can also be compared with the existing error characterisation of the rectangular method given in [8]. In this work an upperbound on the matrix approximation error of (10) has been introduced using basic algebra.…”

Section: Rectangular Methodmentioning

confidence: 99%

“…The latter is necessary to derive useful criteria for choosing adequate sampling periods (see Section 4.3). Therefore the error concept of [8] is not considered here.…”

Section: Rectangular Methodmentioning

confidence: 99%

“…However, the discussion on the discretisation error and applicability of these methods for specific LPV systems was very limited. Only in [8] an attempt was made to characterise the discretisation error of the Euler method in a matrix-approximation setting. Many applications of the methods introduced in [7] have been investigated with respect to linear fractional representation of LPV systems, [9 -12], even making preliminary steps towards a mixed first-order hold discretisation setting [13,14].…”

Section: Introductionmentioning

confidence: 99%

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Discretisation of linear parameter-varying state-space representations

Tóth

Heuberger

Hof

2010

IET Control Theory Appl.

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Discretisation of linear parameter-varying (LPV) systems is a relevant, but insufficiently investigated problem of both LPV control design and system identification. In this contribution, existing results on the discretisation of LPV state-space models with static dependence (without memory) on the scheduling signal are surveyed and new methods are introduced. These approaches are analysed in terms of approximation error, considering ideal zero-order hold actuation and sampling of the input-output signals and scheduling variables of the system. Criteria to choose appropriate sampling periods with respect to the investigated methods are also presented. The application of the considered approaches on state-space representations with dynamic dependence (with memory) on the scheduling is investigated in a higherorder hold sense.

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Section: Complete Methodsmentioning

confidence: 99%

Section: Polynomial (Hanselmann) Methodmentioning

confidence: 99%

Section: Rectangular Methodmentioning

confidence: 99%

“…The latter is necessary to derive useful criteria for choosing adequate sampling periods (see Section 4.3). Therefore the error concept of [8] is not considered here.…”

Section: Rectangular Methodmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Discretisation of linear parameter-varying state-space representations

Tóth

Heuberger

Hof

2010

IET Control Theory Appl.

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RECOVER: A Benchmark for Integrated Fault Tolerant Flight Control Evaluation

Smaili

Breeman

Lombaerts

et al. 2010

Lecture Notes in Control and Information Sciences

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Modeling and Identification of Linear Parameter-Varying Systems

Tóth

2010

Lecture Notes in Control and Information Sciences

455

573

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so swiftly that it feels like yesterday when I first walked the corridors of the Delft Center for Systems and Control (DCSC). At the same time, I cherish all the countless memories that bound my heart to this place and to the people whom I worked with and walked those corridors with day by day. I owe many people a lot for their support, encouragement, and advice, which have contributed directly or indirectly to this thesis and the scientific research associated with it.Besides these general words of gratitude, a number of people deserves special attention. First, I would like to express my thanks towards my supervisors Paul Van den Hof and Peter Heuberger for their excellent guidance and friendship over the years. They were always there helping to find the missing wheel or rejoicing in the success of a breakthrough. Their support both in terms of research and personal matters made my life a lot easier. I also would like to thank Carsten Scherer for many discussions. His ability to understand abstract ideas sharply from half words or bad notation always amazes me.However, my greatest thanks go to my wife Andrea, whose tender love has been a miracle in my life. She was always there in these years, in every moment, supporting me to accomplish all that I was aiming at. She is more than I could ever wish for, as she is all that I would ever need. Last but not least, I thank our son Sándor for all the drawings and stamps he made on my manuscripts to make his father happy and also our daughter Lujza for the smiles to warm my heart. They always worked. It is to them whom I dedicate this thesis.

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Model Weight Estimation for Fdi Using Convex Fault Models

Cited by 8 publications

References 10 publications

Discretisation of linear parameter-varying state-space representations

Discretisation of linear parameter-varying state-space representations

RECOVER: A Benchmark for Integrated Fault Tolerant Flight Control Evaluation

Modeling and Identification of Linear Parameter-Varying Systems

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