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Gabriele Pannocchia

Bio: Gabriele Pannocchia is an academic researcher from University of Pisa. The author has contributed to research in topics: Model predictive control & Optimization problem. The author has an hindex of 24, co-authored 128 publications receiving 2741 citations. Previous affiliations of Gabriele Pannocchia include Wisconsin Alumni Research Foundation.


Papers
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Journal ArticleDOI
TL;DR: In this article, it was shown that a number of integrating disturbances equal to the number of measured variables is sufficient to guarantee zero offset in the controlled variables, and the results apply to square and nonsquare, open-loop stable, integrating and unstable systems.
Abstract: Model predictive control algorithms achieve offset-free control objectives by adding integrating disturbances to the process model. The purpose of these additional disturbances is to lump the plant-model mismatch and/or unmodeled disturbances. Its effectiveness has been proven for particular square cases only. For systems with a number of measured variables (p) greater than the number of manipulated variables (m), it is clear that any controller can track without offset at most m controlled variables. One may think that m integrating disturbances are sufficient to guarantee offset-free control in the m controlled variables. We show this idea is incorrect and present general conditions that allow zero steady-state offset. In particular, a number of integrating disturbances equal to the number of measured variables are shown to be sufficient to guarantee zero offset in the controlled variables. These results apply to square and nonsquare, open-loop stable, integrating and unstable systems.

585 citations

Journal ArticleDOI
TL;DR: This paper establishes exponential stability of suboptimal model predictive control and shows that the proposed cooperative control strategy is in this class, and establishes that under perturbation from a stable state estimator, the origin remains exponentially stable.

466 citations

Journal ArticleDOI
TL;DR: Small tables with only 25-200 entries were used to obtain this performance, while full enumeration is intractable for this example, and Versions of PE are shown to be closed-loop stable.

136 citations

Journal ArticleDOI
TL;DR: It is shown that, when offset-free control is sought, the dynamic observer is equivalent to choosing an integrating disturbance model and an observer for the augmented system.
Abstract: This note presents a method for the combined design of an integrating disturbance model and of the observer (for the augmented system) to be used in offset-free model predictive controllers. A dynamic observer is designed for the original (nonaugmented) system by solving an Hprop control problem aimed at minimizing the effect of unmeasured disturbances and plant/model mismatch on the output prediction error. It is shown that, when offset-free control is sought, the dynamic observer is equivalent to choosing an integrating disturbance model and an observer for the augmented system. An example of a chemical reactor shows the main features and benefits of the proposed method.

126 citations

Journal ArticleDOI
TL;DR: This study proves robust exponential stability with respect to small, but otherwise arbitrary, additive process disturbances and state measurement/estimation errors, and establishes nominal exponential stability of the equilibrium.

111 citations


Cited by
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Journal ArticleDOI
TL;DR: This article gives an up-to-date and accessible introduction to the CasADi framework, which has undergone numerous design improvements over the last 7 years.
Abstract: We present CasADi, an open-source software framework for numerical optimization. CasADi is a general-purpose tool that can be used to model and solve optimization problems with a large degree of flexibility, larger than what is associated with popular algebraic modeling languages such as AMPL, GAMS, JuMP or Pyomo. Of special interest are problems constrained by differential equations, i.e. optimal control problems. CasADi is written in self-contained C++, but is most conveniently used via full-featured interfaces to Python, MATLAB or Octave. Since its inception in late 2009, it has been used successfully for academic teaching as well as in applications from multiple fields, including process control, robotics and aerospace. This article gives an up-to-date and accessible introduction to the CasADi framework, which has undergone numerous design improvements over the last 7 years.

2,056 citations

Book
01 Dec 2004
TL;DR: This paper recalls a few past achievements in Model Predictive Control, gives an overview of some current developments and suggests a few avenues for future research.
Abstract: This paper recalls a few past achievements in Model Predictive Control, gives an overview of some current developments and suggests a few avenues for future research.

1,897 citations

Journal ArticleDOI
TL;DR: In this article, the authors reviewed some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006 and proposed several promising research directions along with some open problems that are deemed important for further investigations.
Abstract: This paper reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles, and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.

1,814 citations

Book ChapterDOI
11 Dec 2012

1,704 citations

Posted Content
TL;DR: In this paper, the authors reviewed some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006, and proposed several promising research directions along with some open problems that are deemed important for further investigations.
Abstract: This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.

1,655 citations