Min-max model predictive control (MPC) is one of the few techniques suitable for robust
stabilization of uncertain nonlinear systems subject to constraints. Stability issues as well as …

l\lany systems encountered in practice involve a coupling between contin uous dynamics
and discrete events. Systems in which these two kinds of dynamics coexist and interact are …

The analysis and design of nonlinear feedback systems has recently undergone an
exceptionally rich period of progress and maturation, fueled, to a great extent, by (1) the …

Deals with several notions of incremental stability. In other words, the focus is on stability of
trajectories with respect to one another, rather than with respect to some attractor. The aim is …

The notion of input-to-state stability (ISS) is now recognized as a central concept in
nonlinear systems analysis. It provides a nonlinear generalization of finite gains with respect …

The construction of strict Lyapunov functions is a challenging problem that is of significant
ongoing research interest. Although converse Lyapunov function theory guarantees the …

We present stability results for unconstrained discrete-time nonlinear systems controlled
using finite-horizon model predictive control (MPC) algorithms that do not require the …

According to the Hartman–Grobman Theorem, a nonlinear system can be linearized in a
neighborhood of a hyperbolic stationary point. Here, we extend this linearization around …

This paper develops a unified framework for studying robustness of the input-to-state
stability (ISS) property and presents new results on robustness of ISS to slowly varying …

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