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The use of available disturbance predictions within a nominal model predictive control formulation is studied. The main challenge that arises is the loss of recursive feasibility and stability guarantees when a persistent disturbance is…

Systems and Control · Computer Science 2018-07-31 Pablo R Baldivieso-Monasterios , Paul A. Trodden

The apparent stability of population oscillations in ecological systems is a long-standing puzzle. A generic solution for this problem is suggested here. The stabilizing mechanism involves the combined effect of spatial migration,…

Populations and Evolution · Quantitative Biology 2007-05-23 Refael Abta , Marcelo Schiffer , Avishag Ben-Ishay , Nadav M. Shnerb

This paper studies the emulation-based stabilization of nonlinear networked control systems with two time scales. We address the challenge of using a single communication channel for transmitting both fast and slow variables between the…

Optimization and Control · Mathematics 2025-02-27 Weixuan Wang , Alejandro I. Maass , Dragan Nešić , Ying Tan , Romain Postoyan , W. P. M. H. Heemels

The current series of papers is concerned with stochastic stability of monotone dynamical systems by identifying the basic dynamical units that can survive in the presence of noise interference. In the first of the series, for the…

Dynamical Systems · Mathematics 2025-11-18 Jifa Jiang , Xi Sheng , Yi Wang

This paper is concerned with a characterization of the observability for a continuous-time hidden Markov model where the state evolves as a general continuous-time Markov process and the observation process is modeled as nonlinear function…

Probability · Mathematics 2020-02-25 Jin W. Kim , Prashant G. Mehta

The problem of remotely stabilizing a noisy linear time invariant plant over a Gaussian relay network is addressed. The network is comprised of a sensor node, a group of relay nodes and a remote controller. The sensor and the relay nodes…

Optimization and Control · Mathematics 2013-07-30 Ali A. Zaidi , Tobias J. Oechtering , Serdar Yuksel , Mikael Skoglund

We provide a technique to obtain provably optimal control sequences for quantum systems under the influence of time-correlated multiplicative control noise. Utilizing the circuit-level noise model introduced in [Phys. Rev. Research 3,…

In this paper we study a non strictly systems of conservation law by stochastic perturbation. We show the existence and uniqueness of the solution. We do not assume that $BV$-regularity for the initial conditions. The proofs are based on…

Analysis of PDEs · Mathematics 2017-10-04 Christian Olivera

The effect of multiplicative stochastic perturbations on Hamiltonian systems on the plane is investigated. It is assumed that perturbations fade with time and preserve a stable equilibrium of the limiting system. The paper investigates…

Dynamical Systems · Mathematics 2022-10-12 O. A. Sultanov

We introduce a new coordination problem in distributed computing that we call the population stability problem. A system of agents each with limited memory and communication, as well as the ability to replicate and self-destruct, is…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-03-09 Shafi Goldwasser , Rafail Ostrovsky , Alessandra Scafuro , Adam Sealfon

This paper addresses the classical problem of determining the sets of possible states of a linear discrete-time system subject to bounded disturbances from measurements corrupted by bounded noise. These so-called uncertainty sets evolve…

Optimization and Control · Mathematics 2014-05-08 Robin Hill , Yousong Luo , Uwe Schwerdtfeger

This paper studies a class of random nonlinear systems with time-varying delay, in which the $r$-order moment ($r\geq1$) of the random disturbance is finite. Firstly, some general conditions are proposed to guarantee the existence and…

Optimization and Control · Mathematics 2018-06-22 Yao Liqiang , Zhang Weihai

The effect of small noise in a smooth dynamical system is negligible on any finite time interval. Here we study situations when it persists on intervals increasing to infinity. Such asymptotic regime occurs when the system starts from…

Probability · Mathematics 2026-01-14 J. Baker , P. Chigansky , K. Hamza , F. C. Klebaner

Non-stationary signals are ubiquitous in real life. Many techniques have been proposed in the last decades which allow decomposing multi-component signals into simple oscillatory mono-components, like the groundbreaking Empirical Mode…

Numerical Analysis · Mathematics 2024-01-30 Giovanni Barbarino , Antonio Cicone

This paper presents a computationally efficient robust model predictive control law for discrete linear time invariant systems subject to additive disturbances that may depend on the state and/or input norms. Despite the dependency being…

Optimization and Control · Mathematics 2019-08-12 Danylo Malyuta , Behcet Acikmese , Martin Cacan

Multipliers can be used to guarantee both the Lyapunov stability and input-output stability of Lurye systems with time-invariant memoryless slope-restricted nonlinearities. If a dynamic multiplier is used there is no guarantee the…

Systems and Control · Electrical Eng. & Systems 2024-03-20 William P. Heath , Joaquin Carrasco

This thesis is concerned with the rejection of time-varying disturbances in linear model predictive control of discrete-time systems. In the literature, disturbances are widely rejected by using velocity models, disturbance model with…

Systems and Control · Electrical Eng. & Systems 2022-10-04 Isah Abdulrasheed Jimoh

Self-stabilization ensures that, after any transient fault, the system recovers in a finite time and eventually exhibits a correct behaviour. Speculation consists in guaranteeing that the system satisfies its requirements for any execution…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-04-26 Swan Dubois , Rachid Guerraoui

We develop an interpolation-based framework for noisy linear systems with unknown system matrix with bounded norm (implying bounded growth or non-increasing energy), and bounded process noise energy. The proposed approach characterizes all…

Systems and Control · Electrical Eng. & Systems 2025-11-17 Martina Vanelli , Nima Monshizadeh , Julien M. Hendrickx

Deterministic models are approximations of reality that are easy to interpret and often easier to build than stochastic alternatives. Unfortunately, as nature is capricious, observational data can never be fully explained by deterministic…

Machine Learning · Computer Science 2020-03-31 Andrew Warrington , Saeid Naderiparizi , Frank Wood