A
Achim Ilchmann
Researcher at Technische Universität Ilmenau
Publications - 161
Citations - 4302
Achim Ilchmann is an academic researcher from Technische Universität Ilmenau. The author has contributed to research in topics: Adaptive control & Linear system. The author has an hindex of 34, co-authored 156 publications receiving 3819 citations. Previous affiliations of Achim Ilchmann include University of Exeter & University of Bremen.
Papers
More filters
Book
Non-identifier-based high-gain adaptive control
TL;DR: High-gain stabilizability, almost strict positive realness, Universal adaptive stabilization,Universal adaptive tracking, and Exponential stability of the terminal system.
Journal ArticleDOI
Tracking with prescribed transient behaviour
TL;DR: In this article, a universal tracking control for M-input, M-output dynamical systems modelled by Functional Differential Equations (FDE) is investigated. But the control objective is to ensure that, for an arbitrary -valued reference signal of class W 1,∞ (absolutely continuous and bounded with essentially bounded derivative) and every system of class S, the tracking error e between plant output and reference signal evolves within a prespecified performance envelope or funnel.
Journal ArticleDOI
Universal l-tracking for nonlinearly-perturbed systems in the presence of noise
Achim Ilchmann,E. P. Ryan +1 more
TL;DR: The following servomechanism problem is solved: Determine a l-universal adaptive strategy to control the output to track any reference signal in W 1,∞, with tracking error asymptotic to a ball of arbitrary prescribed radius λ >0.
Journal ArticleDOI
The quasi-Weierstraß form for regular matrix pencils
TL;DR: In this paper, the Wong sequences of subspaces are investigated and invoked to decompose the K n into V � ⊕ W �, where any bases of the linear spaces V � and W transform the matrix pencil into the Quasi-Weierstras form.
Journal ArticleDOI
Tracking with Prescribed Transient Behavior for Nonlinear Systems of Known Relative Degree
TL;DR: The first control objective is tracking, by the output $y$, with prescribed accuracy: determine a feedback strategy which ensures that, for every reference signal $r$ and every system of class $\Sigma_{\rho}$, the tracking error is ultimately bounded by l.