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In this paper, we investigate the problem of controlling multiple unmanned aerial vehicles (UAVs) to enclose a moving target in a distributed fashion based on a relative distance and self-displacement measurements. A relative localization…

Systems and Control · Electrical Eng. & Systems 2023-07-31 Xueming Liu , Kunda Liu , Tianjiang Hu , Qingrui Zhang

We consider the internal control of linear parabolic equations through on-off shape controls, i.e., controls of the form $M(t)\chi_{\omega(t)}$ with $M(t) \geq 0$ and $\omega(t)$ with a prescribed maximal measure. We establish small-time…

Optimization and Control · Mathematics 2024-01-09 Camille Pouchol , Emmanuel Trélat , Christophe Zhang

This work addresses the robust reconstruction problem of a sparse signal from compressed measurements. We propose a robust formulation for sparse reconstruction which employs the $\ell_1$-norm as the loss function for the residual error and…

Information Theory · Computer Science 2017-03-30 Fei Wen , Yuan Yang , Ling Pei , Wenxian Yu , Peilin Liu

In this work we deal with the optimal design and optimal control of structures undergoing large rotations. In other words, we show how to find the corresponding initial configuration and the corresponding set of multiple load parameters in…

Neural and Evolutionary Computing · Computer Science 2009-02-10 A. Ibrahimbegovic , C. Knopf-Lenoir , A. Kucerova , P. Villon

Aircraft failures alter the aircraft dynamics and cause maneuvering flight envelope to change. Such envelope variations are nonlinear and generally unpredictable by the pilot as they are governed by the aircraft's complex dynamics. Hence,…

Systems and Control · Computer Science 2019-10-22 Ramin Norouzi , Amirreza Kosari , Mohammad Hossein Sabour

We design sparse and block sparse feedback gains that minimize the variance amplification (i.e., the $H_2$ norm) of distributed systems. Our approach consists of two steps. First, we identify sparsity patterns of feedback gains by…

Optimization and Control · Mathematics 2013-12-30 Fu Lin , Makan Fardad , Mihailo R. Jovanović

The collision avoidance constraints are prominent as non-convex, non-differentiable, and challenging when defined in optimization-based motion planning problems. To overcome these issues, this paper presents a novel non-conservative…

Robotics · Computer Science 2024-04-16 Siavash Tavana , Sepideh Faghihi , Anton de Ruiter , Krishna Dev Kumar

Morphing aerial vehicles offer enhanced maneuverability and fuel efficiency compared to fixed-wing configurations. However, the trade-off between performance gains and control cost in dynamic, unsteady maneuvers remains under-explored. This…

Systems and Control · Electrical Eng. & Systems 2026-05-05 Subarna Pudasaini , Parker Smith , Daning Huang

We consider linear model reduction in both the control and state variables for unconstrained linear-quadratic optimal control problems subject to time-varying parabolic PDEs. The first-order optimality condition for a state-space reduced…

Optimization and Control · Mathematics 2025-10-17 Michael Kartmann , Stefan Volkwein

Aircraft failures alter dynamics, diminishing manoeuvrability. Such manoeuvring flight envelope variations, governed by the aircraft's complex nonlinear dynamics, are unpredictable by pilots and existing flight management systems. To…

Systems and Control · Electrical Eng. & Systems 2024-08-06 Ramin Norouzi , Amirreza Kosari , Mark H. Lowenberg

We present a systematic approach to the optimal placement of finitely many sensors in order to infer a finite-dimensional parameter from point evaluations of the solution of an associated parameter-dependent elliptic PDE. The quality of the…

Optimization and Control · Mathematics 2021-03-30 Ira Neitzel , Konstantin Pieper , Boris Vexler , Daniel Walter

We consider an elliptic optimal control problem where the objective functional contains evaluations of the state at a finite number of points. In particular, we use a fidelity term that encourages the state to take certain values at these…

Numerical Analysis · Mathematics 2014-11-19 C. Brett , A. S. Dedner , C. M. Elliott

Compressed sensing of sparse sources can be improved by incorporating prior knowledge of the source. In this paper we demonstrate a method for optimal selection of weights in weighted $L_1$ norm minimization for a noiseless reconstruction…

Information Theory · Computer Science 2013-09-17 Toshiyuki Tanaka , Jack Raymond

Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. While naturally cast as a combinatorial optimization problem, variable or feature selection admits a convex relaxation through the…

Machine Learning · Computer Science 2012-04-23 Francis Bach , Rodolphe Jenatton , Julien Mairal , Guillaume Obozinski

The dynamical response of an aircraft subject to gust perturbations is a key element in a preliminary design phase. In particular, the loads induced by gusts along the wing should not exceed some limit values and should even ideally be…

Systems and Control · Electrical Eng. & Systems 2021-07-05 Pierre Vuillemin , David Quero Martin , Charles Poussot-Vassal

We consider a linear-quadratic elliptic optimal control problem with point evaluations of the state variable in the cost functional. The state variable is discretized by conforming linear finite elements. For control discretization, three…

Numerical Analysis · Mathematics 2018-02-09 Niklas Behringer , Dominik Meidner , Boris Vexler

The presence of outliers can significantly degrade the performance of ellipse fitting methods. We develop an ellipse fitting method that is robust to outliers based on the maximum correntropy criterion with variable center (MCC-VC), where a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-17 Wei Wang , Gang Wang , Chenlong Hu , K. C. Ho

Modern control designs in robotics, aerospace, and cyber-physical systems rely heavily on real-world data obtained through system outputs. However, these outputs can be compromised by system faults and malicious attacks, distorting critical…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Hiroyasu Tsukamoto , Joudi Hajar , Soon-Jo Chung , Fred Y. Hadaegh

This paper presents an end-to-end framework for robust structure/control optimization of an industrial benchmark. When dealing with space structures, a reduction of the spacecraft mass is paramount to minimize the mission cost and maximize…

Systems and Control · Electrical Eng. & Systems 2023-11-28 Francesco Sanfedino , Daniel Alazard , Andy Kiley , Mark Watt , Pedro Simplicio , Finn Ankersen

In compressed sensing, in order to recover a sparse or nearly sparse vector from possibly noisy measurements, the most popular approach is $\ell_1$-norm minimization. Upper bounds for the $\ell_2$- norm of the error between the true and…

Machine Learning · Statistics 2015-12-31 M. Eren Ahsen , M. Vidyasagar