34 citations · 210 across the 68 of their papers we have counts for
6 papers · 1 filter
Contracting Implicit Recurrent Neural Networks: Stable Models with Improved Trainability
Max Revay, Ian R. Manchester
Stability of recurrent models is closely linked with trainability, generalizability and in some applications, safety. Methods that train stable recurrent neural networks, however,…
Continuous-time Dynamic Realization for Nonlinear Stabilization via Control Contraction Metrics
Ruigang Wang, Ian R. Manchester
Nonlinear stabilization using control contraction metric (CCM) method usually involves an online optimization problem to compute a minimal geodesic (a shortest path) between pair o…
A Comparison of LPV Gain Scheduling and Control Contraction Metrics for Nonlinear Control
Ruigang Wang, Roland Tóth, Ian R. Manchester
Gain-scheduled control based on linear parameter-varying (LPV) models derived from local linearizations is a widespread nonlinear technique for tracking time-varying setpoints. Rec…
Priority Maps for Surveillance and Intervention of Wildfires and other Spreading Processes
Vera L. J. Somers, Ian R. Manchester
Unmanned Aerial Vehicle (UAV) path planning algorithms often assume a knowledge reward function or priority map, indicating the most important areas to visit. In this paper we prop…
Robust Contraction Analysis of Nonlinear Systems via Differential IQC
Ruigang Wang, Ian R. Manchester
We present a new approach to verifying contraction and -gain of uncertain nonlinear systems, extending the well-known method of integral quadratic constraints. The uncertain s…
Dynamical Privacy in Distributed Computing -- Part I: Privacy Loss and PPSC Mechanism
Yang Liu, Junfeng Wu, Ian R. Manchester +1
A distributed computing protocol consists of three components: (i) Data Localization: a network-wide dataset is decomposed into local datasets separately preserved at a network of…