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This paper focuses on sensor fault detection and compensation for robotic manipulators. The proposed method features a new adaptive observer and a new terminal sliding mode control law established on a second-order integral sliding surface.…

We present some new results on the dynamic regressor extension and mixing parameter estimators for linear regression models recently proposed in the literature. This technique has proven instrumental in the solution of several open problems…

Systems and Control · Electrical Eng. & Systems 2019-08-15 Romeo Ortega , Stanislav Aranovskiy , Anton A. Pyrkin , Alessandro Astolfi , Alexey A. Bobtsov

We present a novel class of methods to compute functions of matrices or their action on vectors that are suitable for parallel programming. Solving appropriate simple linear systems of equations in parallel (or computing the inverse of…

Numerical Analysis · Mathematics 2022-10-10 Sergio Blanes

Significant inaccuracy often occurs during the process of mathematical calculation due to the digit limitation of floating point, which may lead to catastrophic loss. Normally, people believe that adjustment of floating-point precision is…

Numerical Analysis · Computer Science 2015-12-07 Ran Wang , Xinrui He

Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present a theoretical analysis of the iterative hard thresholding…

Information Theory · Computer Science 2008-05-06 Thomas Blumensath , Mike E. Davies

This article aims to derive a practical tracking control algorithm for flexible air-breathing hypersonic vehicles (FAHVs) with lumped disturbances, unmeasurable states and actuator failures. Based on the framework of the backstepping…

Systems and Control · Electrical Eng. & Systems 2025-04-15 Tianlong Zhao , Fei Hao

Various spacecraft have sensors that repeatedly perform a prescribed scanning maneuver, and one may want high precision. Iterative Learning Control (ILC) records previous run tracking error, adjusts the next run command, aiming for zero…

Systems and Control · Electrical Eng. & Systems 2023-08-01 Richard W. Longman , Shuo Liu , Tarek A. Elsharhawy

This paper proposes an algorithmic framework for solving parametric optimization problems which we call adjoint-based predictor-corrector sequential convex programming. After presenting the algorithm, we prove a contraction estimate that…

Optimization and Control · Mathematics 2011-09-14 Q. Tran Dinh , C. Savorgnan , M. Diehl

This paper is about a real-time model predictive control (MPC) algorithm for a particular class of model based controllers, whose objective consists of a nominal tracking objective and an additional learning objective. Here, the…

Optimization and Control · Mathematics 2016-11-09 Xuhui Feng , Boris Houska

Optimization problems in engineering and applied mathematics are typically solved in an iterative fashion, by systematically adjusting the variables of interest until an adequate solution is found. The iterative algorithms that govern these…

Optimization and Control · Mathematics 2022-05-31 Laurent Lessard

We propose a new paradigm for designing efficient p-adaptive arbitrary high order methods. We consider arbitrary high order iterative schemes that gain one order of accuracy at each iteration and we modify them in order to match the…

Numerical Analysis · Mathematics 2023-11-09 Lorenzo Micalizzi , Davide Torlo , Walter Boscheri

In distributed model predictive control (DMPC), where a centralized optimization problem is solved in distributed fashion using dual decomposition, it is important to keep the number of iterations in the solution algorithm, i.e. the amount…

Optimization and Control · Mathematics 2013-07-11 Pontus Giselsson , Anders Rantzer

An experimental comparison of two or more optimization algorithms requires the same computational resources to be assigned to each algorithm. When a maximum runtime is set as the stopping criterion, all algorithms need to be executed in the…

Performance · Computer Science 2024-02-09 Etor Arza , Josu Ceberio , Ekhiñe Irurozki , Aritz Pérez

We introduce a tool for simulation and optimization of gas pipeline networks coupled to power grids by gas-to-power plants. The model under consideration consists of the isentropic Euler equations to describe the gas flow coupled to the AC…

Optimization and Control · Mathematics 2019-03-25 Eike Fokken , Simone Göttlich , Oliver Kolb

The comparison of different medical treatments from observational studies or across different clinical studies is often biased by confounding factors such as systematic differences in patient demographics or in the inclusion criteria for…

Methodology · Statistics 2025-05-15 Ekkehard Glimm , Lillian Yau

Monitoring software systems at runtime is key for understanding workloads, debugging, and self-adaptation. It typically involves collecting and storing observable software data, which can be analyzed online or offline. Despite the…

Software Engineering · Computer Science 2023-05-03 Jhonny Mertz , Ingrid Nunes

In this paper, an enhancement to the well known Phasor Power Oscillation Damper is proposed, aiming to increase its performance. Fundamental to the functioning of this controller is the estimation of a phasor representing oscillatory…

Systems and Control · Electrical Eng. & Systems 2021-11-10 Hallvar Haugdal , Kjetil Uhlen , Hjörtur Jóhannsson

The operation and maintenance costs of wind parks make up a major fraction of a park's overall lifetime costs. They also include opportunity costs of lost revenue from avoidable power generation underperformance. We present a…

Systems and Control · Electrical Eng. & Systems 2020-05-04 Angela Meyer , Bernhard Brodbeck

Runtime verification is checking whether a system execution satisfies or violates a given correctness property. A procedure that automatically, and typically on the fly, verifies conformance of the system's behavior to the specified…

Software Engineering · Computer Science 2013-03-06 Mikhail Chupilko , Alexander Kamkin

To deploy machine learning models on-device, practitioners use compression algorithms to shrink and speed up models while maintaining their high-quality output. A critical aspect of compression in practice is model comparison, including…

Human-Computer Interaction · Computer Science 2025-01-27 Angie Boggust , Venkatesh Sivaraman , Yannick Assogba , Donghao Ren , Dominik Moritz , Fred Hohman