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This paper considers discrete-time linear systems with bounded additive disturbances, and studies the convergence properties of the backward reachable sets of robust controlled invariant sets (RCIS). Under a simple condition, we prove that…

Systems and Control · Electrical Eng. & Systems 2023-09-28 Zexiang Liu , Necmiye Ozay

We study a class of projective transformations of spectraplexes associated with self-dual cones and, on this basis, propose a polynomial-time algorithm for convex feasibility problems with positive definite constraints. At each iteration of…

Optimization and Control · Mathematics 2025-06-19 Sergei Chubanov

Approximations of functions with finite data often do not respect certain "structural" properties of the functions. For example, if a given function is non-negative, a polynomial approximation of the function is not necessarily also…

Numerical Analysis · Mathematics 2020-08-20 Vidhi Zala , Robert M. Kirby , Akil Narayan

In the past couple of decades, non-quadratic convex penalties have reshaped signal processing and machine learning; in robust control, however, general convex costs break the Riccati and storage function structure that make the design…

Systems and Control · Electrical Eng. & Systems 2025-08-21 Joudi Hajar , Reza Ghane , Babak Hassibi

Under a regularity assumption we prove that reachability in fixed time for nonlinear control systems is robust under control sampling.

Optimization and Control · Mathematics 2020-06-22 Loïc Bourdin , Emmanuel Trélat

We consider the problem of minimizing convex combinations of the first two eigenvalues of the Dirichlet-Laplacian among open sets of $R^N$ of fixed measure. We show that, by purely elementary arguments, based on the minimality condition, it…

Analysis of PDEs · Mathematics 2016-07-29 Dario Mazzoleni , Davide Zucco

The convex restriction of the power flow feasible sets identifies the convex subset of power injections where the solution for power flow is guaranteed to exist and satisfy the operational constraints. In contrast to convex relaxations, the…

Optimization and Control · Mathematics 2020-03-03 Dongchan Lee , Hung D. Nguyen , Krishnamurthy Dvijotham , Konstantin Turitsyn

The push-forward operation enables one to redistribute a probability measure through a deterministic map. It plays a key role in statistics and optimization: many learning problems (notably from optimal transport, generative modeling, and…

Machine Learning · Statistics 2025-05-19 Lucas de Lara , Mathis Deronzier , Alberto González-Sanz , Virgile Foy

Nonsmooth composite optimization problems under uncertainty are prevalent in various scientific and engineering applications. We consider risk-neutral composite optimal control problems, where the objective function is the sum of a…

Optimization and Control · Mathematics 2026-03-02 Johannes Milz , Daniel Walter

A fundamental concept in control theory is that of controllability, where any system state can be reached through an appropriate choice of control inputs. Indeed, a large body of classical and modern approaches are designed for controllable…

Optimization and Control · Mathematics 2022-06-13 Yonathan Efroni , Sham Kakade , Akshay Krishnamurthy , Cyril Zhang

In discrete convex analysis, the scaling and proximity properties for the class of L$^\natural$-convex functions were established more than a decade ago and have been used to design efficient minimization algorithms. For the larger class of…

Combinatorics · Mathematics 2017-12-13 Satoko Moriguchi , Kazuo Murota , Akihisa Tamura , Fabio Tardella

This paper investigates the near optimal control for a kind of linear stochastic control systems governed by the forward backward stochastic differential equations, where both the drift and diffusion terms are allowed to depend on controls…

Optimization and Control · Mathematics 2015-01-23 Liangquan Zhang , Jianhui Huang , Xun Li

The effectiveness of projection methods for solving systems of linear inequalities is investigated. It is shown that they have a computational advantage over some alternatives and that this makes them successful in real-world applications.…

Optimization and Control · Mathematics 2009-12-23 Y. Censor , W. Chen , P. L. Combettes , R. Davidi , G. T. Herman

Reachability problems in infinite-state systems are often subject to extremely high complexity. This motivates the investigation of efficient overapproximations, where we add transitions to obtain a system in which reachability can be…

Formal Languages and Automata Theory · Computer Science 2022-06-28 Moses Ganardi , Rupak Majumdar , Georg Zetzsche

This paper proposes novel approaches for designing control Lyapunov functions (CLFs) for constrained linear systems. We leverage recent configuration-constrained polyhedral computing techniques to devise piecewise affine convex CLFs.…

Optimization and Control · Mathematics 2025-03-21 Boris Houska , Matthias A. Müller , Mario E. Villanueva

Convex geometries form a subclass of closure systems with unique criticals, or $UC$-systems. We show that the $F$-basis introduced in [1] for $UC$-systems, becomes optimum in convex geometries, in two essential parts of the basis: right…

Optimization and Control · Mathematics 2016-02-02 Kira Adaricheva

This paper presents a new control approach for guaranteed safety (remaining in a safe set) subject to actuator constraints (the control is in a convex polytope). The control signals are computed using real-time optimization, including…

Systems and Control · Electrical Eng. & Systems 2023-10-13 Pedram Rabiee , Jesse B. Hoagg

The paper concerns optimal control of discontinuous differential inclusions of the normal cone type governed by a generalized version of the Moreau sweeping process with control functions acting in both nonconvex moving sets and additive…

Optimization and Control · Mathematics 2017-11-08 Tan H. Cao , B. S. Mordukhovich

A linear quadratic Dirichlet control problem posed on a possibly non-convex polygonal domain is analyzed. Detailed regularity results are provided in classical Sobolev (Slobodetskii) spaces. In particular, it is proved that in the presence…

Numerical Analysis · Mathematics 2018-05-03 Thomas Apel , Mariano Mateos , Johannes Pfefferer , Arnd Rösch

In this article, we survey the primary research on polyhedral computing methods for constrained linear control systems. Our focus is on the modeling power of convex optimization, featured to design set-based robust and optimal controllers.…

Optimization and Control · Mathematics 2024-12-18 Boris Houska , Matthias A. Müller , Mario E. Villanueva