In this paper, we propose an approach for computing invariant sets of discrete-time nonlinear systems by lifting the nonlinear dynamics into a higher dimensional linear model. In particular, we focus on the \emph{maximal admissible invariant set} contained in some given constraint set. For special types of nonlinear systems, which can be exactly immersed into higher dimensional linear systems with state transformations, invariant sets of the original nonlinear system can be characterized using the higher dimensional linear representation. For general nonlinear systems without the immersibility property, \emph{approximate immersions} are defined in a local region within some tolerance and linear approximations are computed by leveraging the ...
Abstract: New sequences of monotonically increasing sets are introduced, for linear discrete-time sy...
In this paper, we consider the problem of computing the maximal invariant set of linear systems with...
This paper presents a novel approach to synthesizing positive invariant sets for unmodeled nonlinear...
In this paper, we propose a method for computing invariant sets of discrete-time nonlinear systems b...
Given a nonlinear discrete-time system, previous works exist that compute invariant sets as finite u...
This paper proposes a data-driven immersion approach to obtain linear equivalents or approximations ...
This paper deals with the computation of control invariant sets for constrained nonlinear systems. T...
We propose to compute approximations to invariant sets in dynamical systems by minimizing an appropr...
This paper addresses safety verification of nonlinear systems through invariant set computation. Mor...
We consider the problem of computing the maximal invariant set of discrete-time linear systems subje...
The main topic of this paper is the controllability/reachabilityproblems of the maximal invariant se...
This paper presents new methods for set-valued state estimation of discrete-time nonlinear systems w...
We characterize the maximum controlled invariant (MCI) set for discrete-time systems as the solution...
In this paper, we show that a basic fixed point method used to enclose the greatest fixed point in a...
The qualitative theory of dynamical systems is concerned with studying the long time behavior discre...
Abstract: New sequences of monotonically increasing sets are introduced, for linear discrete-time sy...
In this paper, we consider the problem of computing the maximal invariant set of linear systems with...
This paper presents a novel approach to synthesizing positive invariant sets for unmodeled nonlinear...
In this paper, we propose a method for computing invariant sets of discrete-time nonlinear systems b...
Given a nonlinear discrete-time system, previous works exist that compute invariant sets as finite u...
This paper proposes a data-driven immersion approach to obtain linear equivalents or approximations ...
This paper deals with the computation of control invariant sets for constrained nonlinear systems. T...
We propose to compute approximations to invariant sets in dynamical systems by minimizing an appropr...
This paper addresses safety verification of nonlinear systems through invariant set computation. Mor...
We consider the problem of computing the maximal invariant set of discrete-time linear systems subje...
The main topic of this paper is the controllability/reachabilityproblems of the maximal invariant se...
This paper presents new methods for set-valued state estimation of discrete-time nonlinear systems w...
We characterize the maximum controlled invariant (MCI) set for discrete-time systems as the solution...
In this paper, we show that a basic fixed point method used to enclose the greatest fixed point in a...
The qualitative theory of dynamical systems is concerned with studying the long time behavior discre...
Abstract: New sequences of monotonically increasing sets are introduced, for linear discrete-time sy...
In this paper, we consider the problem of computing the maximal invariant set of linear systems with...
This paper presents a novel approach to synthesizing positive invariant sets for unmodeled nonlinear...