Robust Estimation with Partial Gain-Scheduling Through Convex Optimization

Veenman, Joost; Scherer, Carsten W.; Köse, İ. Emre

doi:10.1007/978-1-4614-1833-7_10

Cited by 3 publications

(3 citation statements)

References 21 publications

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“…The results in this paper also complement the recent robust performance results obtained for LPV systems whose state matrices have rational dependence on the scheduling parameters [12], [13], [14], [15]. In contrast to [12], [13], [14], [15], an arbitrary dependence on the parameters is assumed in this work and a finite-dimensional approximation based approach is taken. As noted above, this will enable applications to systems, e.g.…”

Section: Introductionsupporting

confidence: 74%

“…The robust performance analysis conditions can thus be viewed as generalizations of those given for nominal (not-uncertain) LPV systems in [4], [5]. The results in this paper also complement the recent robust performance results obtained for LPV systems whose state matrices have rational dependence on the scheduling parameters [12], [13], [14], [15]. In contrast to [12], [13], [14], [15], an arbitrary dependence on the parameters is assumed in this work and a finite-dimensional approximation based approach is taken.…”

Section: Introductionsupporting

confidence: 67%

“…The uncertainty is described by the integral quadratic constraints (Ψ, M ) with Ψ = I and M = b 2 0 0 −1 . The gain of the channel from the reference signal d to the control error e is used as performance measurement and γ is an upper bound on the worst case gain as defined by (15).…”

Section: Numerical Examplementioning

confidence: 99%

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Robustness analysis of linear parameter varying systems using integral quadratic constraints

Pfifer

Seiler

2014

2014 American Control Conference

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A general approach is presented to analyze the worst case input/output gain for an interconnection of a linear parameter varying (LPV) system and an uncertain or nonlinear element. The input/output behavior of the nonlinear/uncertain block is described by an integral quadratic constraint (IQC). A dissipation inequality is proposed to compute an upper bound for this gain. This worst-case gain condition can be formulated as a semidefinite program and the result can be interpreted as a Bounded Real Lemma for uncertain LPV systems. The paper shows that this new condition is a generalization of the well known Bounded Real Lemma for LPV systems. The effectiveness of the proposed method is demonstrated on a simple numerical example.

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