State estimator design for a nonlinear discrete-time system is a challenging problem, further
complicated when additional physical insight is available in the form of inequality constraints …

A highly accessible and unified approach to the design and analysis of intelligent control
systems Adaptive Approximation Based Control is a tool every control designer should have …

A moving-horizon state estimation problem is addressed for a class of nonlinear discrete-
time systems with bounded noises acting on the system and measurement equations. As the …

In this work, a sampled-data nonlinear observer is designed using a continuous-time design
coupled with an inter-sample output predictor. The proposed sampled-data observer is a …

The problem of estimating the state of a discrete-time linear system can be addressed by
minimizing an estimation cost function dependent on a batch of recent measure and input …

This paper presents a novel distributed estimation algorithm based on the concept of moving
horizon estimation. Under weak observability conditions we prove convergence of the state …

Quadratic boundedness is used to deal with stability and design of receding-horizon
estimators. Upper bounds on the norm of the estimation error have been found by means of …

Many scientific and technological areas of major interest require one to solve infinite-
dimensional optimization problems, also called functional optimization problems. In such a …

This paper presents three novel moving-horizon estimation (MHE) methods for discrete-time
partitioned linear systems, ie, systems decomposed into coupled subsystems with non …

Receding-horizon state estimation is addressed for a class of discrete-time systems that may
switch among different modes taken from a finite set. The system and measurement …