In this paper, we develop an algorithm to compute robust MPC explicit solutions for constrained MIMO systems with internal uncertainties and external disturbances. Our approach is based on a recursive closedloop prediction strategy to realize a finite horizon robust MPC regulator, which has the feature that only one-step state prediction is sufficient to realize robust MPC with an arbitrary pre...

When faced with making a decision, it is only natural that one would aim to select the course of action which results in the “best" possible outcome. However, the ability to arrive at a decision necessarily depends upon two things: a well-defined notion of what qualities make an outcome desirable, and a previous decision1 defining to what extent it is necessary to characterize the quality of in...

The paper addresses the problem of designing a robust parameter dependent quadratically stabilizing output/state feedback model predictive control for linear polytopic systems without constraints using original sequential approach. For the closed-loop uncertain system, the design procedure ensures stability, robustness properties and guaranteed cost.

This paper proposes a robust model predictive control for systems with stable and integrating poles. The approach combines the methods developed in Odloak (2004) and Carrapiço and Odloak (2005) to obtain a robust controller for integrating systems when multi-plant uncertainty is considered. The key idea in this development is to separate the control problem in two sub-problems, each of which ta...

In this paper, we develop a finite horizon model predictive control algorithm which is robust to modelling uncertainties. A moving average system matrix is constructed to capture modelling uncertainties and facilitate the future output prediction. The paper is mainly focused on the step tracking problem. Using linear matrix inequality techniques, the design is converted into a semi-definite opt...

Most automated systems operate in uncertain or adversarial conditions, and have to be capable of reliably reacting to changes in the environment. The focus of this paper is on automatically synthesizing reactive controllers for cyber-physical systems subject to signal temporal logic (STL) specifications. We build on recent work that encodes STL specifications as mixed integer linear constraints...

Matteo Rubagotti∗1, Davide Barcelli and Alberto Bemporad 1 Department of Robotics, Nazarbayev University, Kabanbay Batyr Ave 56, 010000 Astana, Kazakhstan 2 Department of Information Engineering, University of Siena, Via Roma 56, 53100 Siena, Italy 3 IMT Institute for Advanced Studies, Piazza S. Ponziano 6, 55100 Lucca, Italy e-mail: [email protected], [email protected], alberto.be...

In this paper we propose an on-line design technique for the target control problem of hybrid automata. First, we compute off-line the shortest path, which has the minimum discrete cost, from an initial state to the given target set. Next, we derive a controller which successfully drives the system from the initial state to the target set while minimizing a cost function. The (robust) model pre...

This thesis is concerned with the theoretical foundations of Robust Model Predictive Control and its application to tracking control problems. Its first part provides an introduction to MPC for constrained linear systems as well as a survey of different Robust MPC methodologies. The second part consists of a discussion of the recently developed Tube-Based Robust MPC framework and its extension ...