34 citations · 210 across the 68 of their papers we have counts for
13 papers · 1 filter
Youla-REN: Learning Nonlinear Feedback Policies with Robust Stability Guarantees
Ruigang Wang, Ian R. Manchester
This paper presents a parameterization of nonlinear controllers for uncertain systems building on a recently developed neural network architecture, called the recurrent equilibrium…
Globally convergent visual-feature range estimation with biased inertial measurements
Bowen Yi, Chi Jin, Ian R. Manchester
The design of a globally convergent position observer for feature points from visual information is a challenging problem, especially for the case with only inertial measurements a…
Learning over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System
Ruigang Wang, Nicholas H. Barbara, Max Revay +1
This paper proposes a nonlinear policy architecture for control of partially-observed linear dynamical systems providing built-in closed-loop stability guarantees. The policy is ba…
Multi-Stage Sparse Resource Allocation for Control of Spreading Processes over Networks
Vera L. J. Somers, Ian R. Manchester
In this paper we propose a method for sparse dynamic allocation of resources to bound the risk of spreading processes, such as epidemics and wildfires, using convex optimization an…
Learning Stable Koopman Embeddings
Fletcher Fan, Bowen Yi, David Rye +2
In this paper, we present a new data-driven method for learning stable models of nonlinear systems. Our model lifts the original state space to a higher-dimensional linear manifold…
Contraction-Based Methods for Stable Identification and Robust Machine Learning: a Tutorial
Ian R. Manchester, Max Revay, Ruigang Wang
This tutorial paper provides an introduction to recently developed tools for machine learning, especially learning dynamical systems (system identification), with stability and rob…
Distributed Identification of Contracting and/or Monotone Network Dynamics
Max Revay, Jack Umenberger, Ian R. Manchester
This paper proposes methods for identification of large-scale networked systems with guarantees that the resulting model will be contracting -- a strong form of nonlinear stability…
Minimizing the Risk of Spreading Processes via Surveillance Schedules and Sparse Control
Vera L. J. Somers, Ian R. Manchester
In this paper, we propose an optimization framework that combines surveillance schedules and sparse control to bound the risk of spreading processes such as epidemics and wildfires…
Nonlinear parameter-varying state-feedback design for a gyroscope using virtual control contraction metrics
Ruigang Wang, Patrick J. W. Koelwijn, Ian R. Manchester +1
In this paper, we present a virtual control contraction metric (VCCM) based nonlinear parameter-varying (NPV) approach to design a state-feedback controller for a control moment gy…
Recurrent Equilibrium Networks: Flexible Dynamic Models with Guaranteed Stability and Robustness
Max Revay, Ruigang Wang, Ian R. Manchester
This paper introduces recurrent equilibrium networks (RENs), a new class of nonlinear dynamical models} for applications in machine learning, system identification and control. The…
An almost globally convergent observer for visual SLAM without persistent excitation
Bowen Yi, Chi Jin, Lei Wang +2
In this paper we propose a novel observer to solve the problem of visual simultaneous localization and mapping (SLAM), only using the information from a single monocular camera and…
On the equivalence of contraction and Koopman approaches for nonlinear stability and control
Bowen Yi, Ian R. Manchester
In this paper we prove new connections between two frameworks for analysis and control of nonlinear systems: the Koopman operator framework and contraction analysis. Each method, i…
Differentially Private Distributed Computation via Public-Private Communication Networks
Lei Wang, Yang Liu, Ian Manchester +1
This paper studies the problem of multi-agent computation under the differential privacy requirement of the agents' local datasets against eavesdroppers having node-to-node communi…