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Initially introduced in the framework of quantum control, the so-called "monotonic algorithms" have demonstrated excellent numerical performance when dealing with bilinear optimal control problems. This paper presents a unified formulation…

Optimization and Control · Mathematics 2010-11-11 Julien Salomon , Gabriel Turinici

In this paper, we develop high-order splitting methods for linear port-Hamiltonian systems, focusing on preserving their intrinsic structure, particularly the dissipation inequality. Port-Hamiltonian systems are characterized by their…

Mathematical Physics · Physics 2024-09-16 Marius Mönch , Nicole Marheineke

This paper deals with the systematic development of structure-preserving approximations for a class of nonlinear partial differential equations on networks. The class includes, for example, gas pipe network systems described by barotropic…

Numerical Analysis · Mathematics 2022-03-25 Björn Liljegren-Sailer , Nicole Marheineke

The main contribution of this paper is the extension of the well-known boundary-control strategy based on structural invariants to the control of infinite-dimensional systems with in-domain actuation. The systems under consideration,…

Optimization and Control · Mathematics 2021-04-20 Tobias Malzer , Hubert Rams , Markus Schöberl

In this paper we extend the previously introduced class of boundary port-Hamiltonian systems to boundary control systems where the variational derivative of the Hamiltonian functional is replaced by a pair of reciprocal differential…

Optimization and Control · Mathematics 2023-12-04 Bernhard Maschke , Arjan van der Schaft

Model Predictive Control (MPC) is a versatile approach capable of accommodating diverse control requirements that holds significant promise for a broad spectrum of industrial applications. Noteworthy challenges associated with MPC include…

Systems and Control · Electrical Eng. & Systems 2025-04-28 Ryuta Moriyasu , Sho Kawaguchi , Kenji Kashima

Many dynamical systems -- from robots interacting with their surroundings to large-scale multiphysics systems -- involve a number of interacting subsystems. Toward the objective of learning composite models of such systems from data, we…

Machine Learning · Computer Science 2023-05-16 Cyrus Neary , Ufuk Topcu

The present work is a successor of [Ilchmann, Kirchhoff 2022] on generic controllability and of [Ilchmann, Kirchhoff 2023] on relative generic controllability of linear differential-algebraic equations. We extend the result from general,…

Optimization and Control · Mathematics 2023-03-06 Achim Ilchmann , Jonas Kirchhoff , Manuel Schaller

This letter investigates the design of a class of infinite-dimensional observers for one dimensional (1D) boundary controlled port-Hamiltonian systems (BC-PHS) defined by differential operators of order $N \geq 1$. The convergence of the…

Systems and Control · Electrical Eng. & Systems 2023-05-18 Jesus-Pablo Toledo-Zucco , Yongxin Wu , Hector Ramirez , Yann Le Gorrec

We introduce an efficient first-order primal-dual method for the solution of nonsmooth PDE-constrained optimization problems. We achieve this efficiency through not solving the PDE or its linearisation on each iteration of the optimization…

Optimization and Control · Mathematics 2024-06-11 Bjørn Jensen , Tuomo Valkonen

This paper proposes a port-Hamiltonian framework for angle-based formation stabilization and maneuvers using bearing and velocity measurements with an underlying triangulated Laman graph. The corresponding port-Hamiltonian controller is…

Systems and Control · Electrical Eng. & Systems 2023-05-18 Ningbo Li , Pablo Borja , Arjan van der Schaft , Jacquelien M. A. Scherpen

In this article, we present the structure-preserving discretization of linear one-dimensional port-Hamiltonian (PH) systems of two conservation laws using discontinuous Galerkin (DG) methods. We recall the DG discretization procedure which…

Systems and Control · Electrical Eng. & Systems 2022-12-19 Tobias Thoma , Paul Kotyczka

This paper presents a systematic methodology for the discretization and reduction of a class of one-dimensional Partial Differential Equations (PDEs) with inputs and outputs collocated at the spatial boundaries. The class of system that we…

Numerical Analysis · Mathematics 2024-07-02 Jesus-Pablo Toledo-Zucco , Denis Matignon , Charles Poussot-Vassal , Yann Le Gorrec

This work proposes PH-based metrics for benchmarking impedance control. A causality-consistent PH model is introduced for mass-spring-damper impedance in Cartesian space. Based on this model, a differentiable, force-torque…

This paper develops a distributed model predictive control (DMPC) strategy for a class of discrete-time linear systems with consideration of globally coupled constraints. The DMPC under study is based on the dual problem concerning all…

Optimization and Control · Mathematics 2019-07-25 Yanxu Su , Yang Shi , Changyin Sun

In recent years, nonlinear dynamic system identification using artificial neural networks has garnered attention due to its broad potential applications across science and engineering. However, purely data-driven approaches often struggle…

Machine Learning · Computer Science 2025-11-06 Fabian J. Roth , Dominik K. Klein , Maximilian Kannapinn , Jan Peters , Oliver Weeger

In this paper, we consider linear time-invariant continuous control systems which are bounded real, also known as scattering passive. Our main theoretical contribution is to show the equivalence between such systems and port-Hamiltonian…

Optimization and Control · Mathematics 2025-01-22 Karim Cherifi , Nicolas Gillis , Punit Sharma

We consider the problem of minimizing the entropy, energy, or exergy production for state transitions of irreversible port-Hamiltonian systems subject to control constraints. Via a dissipativity-based analysis we show that optimal solutions…

Optimization and Control · Mathematics 2022-02-21 Bernhard Maschke , Friedrich Philipp , Manuel Schaller , Karl Worthmann , Timm Faulwasser

This paper examines the problem of real-time optimization of networked systems and develops online algorithms that steer the system towards the optimal trajectory without explicit knowledge of the system model. The problem is modeled as a…

Optimization and Control · Mathematics 2019-10-01 Yue Chen , Andrey Bernstein , Adithya Devraj , Sean Meyn

This paper presents a new method for solving a class of nonlinear optimal control problems with a quadratic performance index. In this method, first the original optimal control problem is transformed into a nonlinear two-point boundary…

Optimization and Control · Mathematics 2014-09-18 Amin Jajarmi , Hamidreza Ramezanpour , Arman Sargolzaei , Pouyan Shafaei
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