Abstract: In many control problems, not all states can be measured and the system is subject to parametric uncertainties, measurement noise, and hard input ...
Abstract—In many control problems, not all states can be measured and the system is subject to parametric uncertainties, measurement noise, and hard input ...
To tackle such problems for linear systems, we propose to combine a recursive parameter and state estimator (based on Bayes' theorem) with a stochastic model ...
Apr 28, 2024 · This paper is devoted to study the observer-based robust H∞ dynamical output feedback control problem for a class of linear switched systems ...
Missing: probabilistic | Show results with:probabilistic
Output feedback model predictive control with probabilistic uncertainties for linear systems ; Sprache, Englisch ; Identifikator, ISBN: 978-1-4673-8682-1 KITopen- ...
Jun 27, 2017 · This paper studies the output-feedback model predictive control (MPC) design problem for linear systems with multiplicative and additive ...
Robust Output Feedback Model Predictive Control for Constrained Linear Systems under Uncertainty Based on Feed Forward and Positive Invariant Feedback Control.
In this paper a novel Stochastic Model Predictive Control algorithm is developed for systems characterized by multiplicative and possibly unbounded model ...
Distributed Model Predictive Control of Linear Systems with Stochastic ...
epubs.siam.org › doi › abs
This paper investigates the distributed stochastic model predictive control (DSMPC) for multiple constrained dynamically decoupled subsystems subject to ...
Stochastic Model Predictive Control of constrained linear systems with additive uncertainty · Lalo Magni. 2009, 2009 European Control Conference (ECC). Download ...