Tight estimation of the Lipschitz constant for deep neural networks (DNNs) is useful in many
applications ranging from robustness certification of classifiers to stability analysis of closed …

In this paper, the problem of fault diagnosis for a satellite formation flight is considered. A
scheme is investigated for fault detection, isolation, and estimation of a class of nonlinear …

High-gain observers play an important role in the design of feedback control for nonlinear
systems. This article overviews the essentials of this technique, starting with motivating …

This work is concerned with a compositional technique for the construction of finite
abstractions (aka, finite Markov decision processes (MDPs)) for networks of discrete-time …

This paper presents a secure chaotic communication scheme using observer-based
synchronization of chaotic systems. A class of chaotic systems satisfying incremental …

A systematic design methodology for state observers for a large class of nonlinear systems
with bounded exogenous inputs (disturbance inputs and sensor noise) is proposed. The …

A new LMI design technique is developed to address the problem of circle criterion-based
ℋ∞ observer design for nonlinear systems. The developed technique applies to both locally …

This paper develops a new high-gain observer design method for nonlinear systems that
has a lower gain compared to the standard high-gain observer. This new observer, called …

This paper presents a new design approach to nonlinear observers for Itô stochastic
nonlinear systems with guaranteed stability. A stochastic contraction lemma is presented …

This paper focuses on the development and use of a nonlinear observer for tracking of
vehicle motion trajectories while using a radar sensor. Previous results on vehicle tracking …