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Offset-free reference tracking with model predictive control
Automatica, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Urban Maeder, Manfred Morari
exaly +2 more sources
An $${\mathscr {H}}_{\infty }$$ Approach to Data-Driven Offset-Free Tracking
Journal of Control, Automation and Electrical Systems, 2020Data-driven controllers also called model-free controllers were invented in order to omit plant modeling step of model-based controllers. Design procedure of these controllers is directly based on experimental I/O data collected from real plant. It can ensure their reliability in real world applications, where the exact model is not available in most ...
Mina Salim
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Offset-free reference tracking for predictive controllers
2007 46th IEEE Conference on Decision and Control, 2007We discuss the offset-free reference tracking problem for linear constrained systems in the presence of disturbances and plant-model mismatch. Introducing disturbance models, we show how to construct a controller/observer combination, such that zero offset is achieved.
Urban Maeder, Manfred Morari
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Offset-free tracking MPC: A tutorial review and comparison of different formulations [PDF]
2015 European Control Conference (ECC), 2015 Offset-free Model Predictive Control formulations refer to a class of algorithms that are able to achieve output tracking of reference signals despite the presence of plant/model mismatch or unmeasured nonzero mean disturbances. The general approach is to augment the nominal system with disturbances, i.e.
Gabriele Pannocchia
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ARX-Model based Model Predictive Control with Offset-Free Tracking
Computer Aided Chemical Engineering, 2010ARX models, is a suitable model class for linear control implementations. The parameter estimation problem is convex and easily handed for both SISO and MIMO system in contrast to ARMAX or State Space model. Model predictive control implementations insuring offset-free tracking are discussed and related.
John Bagterp Jørgensen +2 more
exaly +2 more sources
Robust Offset-Free Speed Tracking Controller of Permanent Magnet Synchronous Generator for Wind Power Generation Applications [PDF]
Electronics (Switzerland), 2018 This article presents a robust speed tracking algorithm for a permanent magnet synchronous generator utilized for wind power generation systems, considering the machine parameter and load uncertainties. There are two major contributions: (a) a disturbance observer is designed to exponentially estimate disturbances from the model-plant mismatches and ...
Kyo-Beum Lee +2 more
exaly +2 more sources
Journal of Process Control, 2019
Abstract This paper presents a stochastic-tube model predictive control (MPC) strategy that systematically handles plant-model mismatch, guarantees stability in the presence of changing operating conditions, and ensures offset-free tracking for all reachable operating conditions.
Ali Mesbah
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Abstract This paper presents a stochastic-tube model predictive control (MPC) strategy that systematically handles plant-model mismatch, guarantees stability in the presence of changing operating conditions, and ensures offset-free tracking for all reachable operating conditions.
Ali Mesbah
exaly +2 more sources
A Robust MPC Algorithm for Offset-Free Tracking of Constant Reference Signals
IEEE Transactions on Automatic Control, 2013A robust model predictive control algorithm solving the tracking and the infeasible reference problems for constrained systems subject to bounded disturbances is presented in this technical note. The proposed solution relies on three main concepts: 1) the reformulation of the system in the so-called velocity form to obtain offset-free tracking when ...
BETTI, GIULIO +2 more
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Automatica, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gang Feng +2 more
exaly +4 more sources
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gang Feng +2 more
exaly +4 more sources
Stochastic Model Predictive Control with Enlarged Domain of Attraction for Offset-Free Tracking
2018 Annual American Control Conference (ACC), 2018The domain of attraction is central to stability and recursive feasibility of model predictive control (MPC). For stochastic linear systems, this paper addresses the problem of enlarging the domain of attraction of stochastic MPC (SMPC) for offset-free tracking. The proposed SMPC strategy relies on using an artificial steady-state target to enlarge the
Tito L. M. Santos +2 more
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