This article introduces recurrent equilibrium networks (RENs), a new class of nonlinear
dynamical models for applications in machine learning, system identification, and control …

We provide a novel robust stability analysis for moving horizon estimation (MHE) using a
Lyapunov function. In addition, we introduce linear matrix inequalities (LMIs) to verify the …

This tutorial paper provides an introduction to recently developed tools for machine learning,
especially learning dynamical systems (system identification), with stability and robustness …

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 …

In this paper, we study the notion of incremental stability for continuous-time nonlinear
systems forced by some external input. Thanks to the notion of “Killing vector field”, we …

This paper focuses on the asynchronous self-triggered control scheme for a dynamic
positioning ship considering the hysteresis input. A novel self-triggered mechanism is …

In this article, we propose a suboptimal moving horizon estimator for a general class of
nonlinear systems. For the stability analysis, we transfer the “feasibility-implies …

The conventional tracking control of mechanical systems is generally based on the
stabilization of error dynamics and most of the results can only guarantee asymptotic …

We present a framework to design nonlinear robust output feedback model predictive control
(MPC) schemes that ensure constraint satisfaction under noisy output measurements and …

Convergence speed is one of the most important features of an equilibrium-seeking
algorithm. In this article, we address the problem of algorithm acceleration for distributed …