34 citations · 210 across the 68 of their papers we have counts for
4 papers · 1 filter
Contracting Nonlinear Observers: Convex Optimization and Learning from Data
Ian R. Manchester
A new approach to design of nonlinear observers (state estimators) is proposed. The main idea is to (i) construct a convex set of dynamical systems which are contracting observers…
An Amendment to "Control Contraction Metrics: Convex and Intrinsic Criteria for Nonlinear Feedback Design"
Ian R. Manchester, Thomas L. Chaffey
We provide an amendment to the first theorem of "Control Contraction Metrics: Convex and Intrinsic Criteria for Nonlinear Feedback Design" by Manchester & Slotine in the form of an…
On Existence of Separable Contraction Metrics for Monotone Nonlinear Systems
Ian R. Manchester, Jean-Jacques E. Slotine
Finding separable certificates of stability is important for tractability of analysis methods for large-scale networked systems. In this paper we consider the question of when a no…
Convex Parameterizations and Fidelity Bounds for Nonlinear Identification and Reduced-Order Modelling
Mark M. Tobenkin, Ian R. Manchester, Alexandre Megretski
Model instability and poor prediction of long-term behavior are common problems when modeling dynamical systems using nonlinear "black-box" techniques. Direct optimization of the l…