Showing papers by "Hüseyin Akçay published in 2010"
TL;DR: Two simple subspace-based identification algorithms to identify stable linear-time-invariant systems from corrupted phase samples of frequency response function are developed and promise results when the algorithms are applied to simulated data.
Abstract: In this paper, two simple subspace-based identification algorithms to identify stable linear-time-invariant systems from corrupted phase samples of frequency response function are developed. The first algorithm uses data sampled at nonuniformly spaced frequencies and is strongly consistent if corruptions are zero-mean additive random variables with a known covariance function. However, this algorithm is biased when corruptions are multiplicative, yet it exactly retrieves finite-dimensional systems from noise-free phase data using a finite amount of data. The second algorithm uses phase data sampled at equidistantly spaced frequencies and also has the same interpolation and strong consistency properties if corruptions are zero-mean additive random variables. The latter property holds also for the multiplicative noise model provided that some noise statistics are known a priori. Promising results are obtained when the algorithms are applied to simulated data.
10 citations
TL;DR: A particular algorithm, which does not require noise covariance function to be known a priori is shown to be strongly consistent provided that disturbances have uniformly bounded second-order moments and the frequencies satisfy a certain regularity condition.
8 citations
TL;DR: In this paper, the root-mean-square response of a half-car model following a random road profile is studied and it is demonstrated that the effect of tire damping on the rms response of actively controlled halfcar suspension system can be significant, in particular at high vehicle velocities.
Abstract: In this note, the root-mean-square response of a half-car model following a random road profile is studied. Road excitation at the front wheel is modeled by a first-order linear shape filter driven by white-noise and the temporal correlation between the front and the rear wheels is predicted by a second-order Pade filter. It is demonstrated that the effect of tire damping on the rms response of actively controlled half-car suspension system can be significant, in particular at high vehicle velocities.
6 citations
14 Mar 2010
TL;DR: In this article, the active suspension problem is formulated as a mixed H 2 /H ∞ synthesis problem and solved using linear matrix inequalities, and the influence of tire damping on the closed-loop performance can be significant.
Abstract: In this paper, multi-objective control of a quarter-car suspension system subjected to random road disturbances is studied. The active suspension problem is formulated as a mixed H 2 /H ∞ synthesis problem and solved using linear matrix inequalities. It is first demonstrated that the influence of tire damping on the closed-loop performance can be significant. Then, this result is extended to suspension models with polytopic tire damping uncertainties.
3 citations
29 Jul 2010
TL;DR: In this article, two simple subspace-based identification algorithms to identify stable linear-time-invariant systems from corrupted phase samples of frequency response function are developed, which is strongly consistent if corruptions are zero-mean additive random variables with a known covariance function.
Abstract: In this paper, two simple subspace-based identification algorithms to identify stable linear-time-invariant systems from corrupted phase samples of frequency response function are developed. The first algorithm uses data sampled at nonuniformly spaced frequencies and is strongly consistent if corruptions are zero-mean additive random variables with a known covariance function. However, this algorithm is biased when corruptions are multiplicative, yet it exactly retrieves finite-dimensional systems from noise-free phase data using a finite amount of data. The second algorithm uses phase data sampled at equidistantly spaced frequencies and also has the same interpolation and strong consistency properties if corruptions are zero-mean additive random variables. The latter property holds also for the multiplicative noise model provided that some noise statistics are known a priori. Promising results are obtained when the algorithms are applied to simulated data.
14 Mar 2010
TL;DR: In this paper, the authors studied instrumental variable subspace identification of multi-input/multi-output linear-time-invariant, discrete-time systems from non-uniformly spaced frequency response measurements.
Abstract: In this paper, we study instrumental variable subspace identification of multi-input/multi-output linear-time-invariant, discrete-time systems from non-uniformly spaced frequency response measurements. A particular algorithm, which does not require noise covariance function to be known a priori is shown to be strongly consistent provided that disturbances have uniformly bounded second-order moments and the frequencies satisfy a certain regularity condition. Interpolation properties of this algorithm and a related one are also studied. A numerical example illustrating the properties of the studied algorithms is presented.