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Mediterranean Conference on control and automation (MED)

作者： Alexandros Nikou Christos K. Verginis Shahab Heshmati-Alamdari Ericsson Research Stockholm Sweden Department of Electrical Engineering Division of Signals and Systems Uppsala University Sweden Department of Electronic Systems Section of Automation &amp Control Aalborg University Denmark

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

This paper proposes a low-complexity feedback control law that is updated aperiodically, in an event-triggered manner, and guarantees prescribed transient and steady state performance for uncertain nonlinear systems affine in the control. By prescribed performance, we mean that the closed-loop error trajectory converges to a predefined arbitrarily small residual set, with convergence rate no less than a certain prespecified value, having maximum overshoot less than a preassigned level. The proposed novel control design is performed in the transformed normalized error, and the triggering mechanism is extracted by guaranteed that these errors always lead to bounded closed loop signals. Moreover, the approach provides a scheme of designing and tuning the control parameters in order to achieve stabilization in a desire state in a pre-defined time T >0. The efficiency of the proposed approach is verified with numerical simulations in MATLAB.

关键词： control design Numerical simulation Trajectory Steady-state Feedback control Nonlinear systems Transient analysis

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Discrete control algorithms for systems with big dead time for control101 MATLAB toolbox

Discrete control algorithms for systems with big dead time f...

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Cybernetics & Informatics (K&I)

作者： Ruth Bars Gyula Max J. Anthony Rossiter László Keviczky Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary School of Electrical and Electronic Engineering University of Sheffield Sheffield UK Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

ISBN: (数字)9798331541811

ISBN: (纸本)9798331541828

The first course of control is under a critical review. Both the teaching material covered and the teaching methods require new considerations. Introducing interactivity in the education process makes the learning more successful and enjoyable. MATLAB provides an effective environment for learning and applying different disciplines. control101 is a new MATLAB toolbox under development which provides tools for interactive learning of control disciplines. This paper presents the framework for teaching discrete control algorithms applied for processes containing large dead times.

关键词： Visualization Systematics PI control Reviews Education Laboratories Process control Prediction algorithms PD control MATLAB

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Sensor Fusion for Glucose Monitoring systems

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IFAC-PapersOnLine 2023年第2期56卷 11527-11532页

作者： Mohamad Al Ahdab Karim Davari Benam Hasti Khoshamadi Anders Lyngvi Fougner Sebastien Gros Section of Automation and Control Department of Electronic Systems Aalborg University Aalborg Øst Denmark Department of Engineering Cybernetics Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology (NTNU) O. S. Bragstads Plass 2D 7034 Trondheim Norway

A fully automated artificial pancreas (AP) requires accurate blood glucose (BG) readings. However, many factors can affect the accuracy of commercially available sensors. These factors include sensor artifacts due to the pressure on surrounding tissues, connection loss, and poor calibration. The AP may administer an incorrect insulin bolus due to inaccurate sensor data when the patient is not supervising the system. The situation can be even worse in animal experiments because animals are eager to play with the sensor and apply pressure. In this study, we propose and derive a Multi-Model Kalman Filter with Forgetting Factor (MMKFF) for the problem of fusing information from redundant subcutaneous glucose sensors. The performance of the developed MMKFF was assessed by comparing it against other Kalman Filter (KF) strategies on experimental data obtained in two different animals. The developed MMKFF was shown to provide a reliable fused glucose reading. Additionally, compared to the other KF approaches, the MMKFF was shown to be better able to adjust to changes in the accuracy of the glucose sensors.

关键词： Developments in measurement signal processing Diabetes

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Emergency Landing Decision Method for Unmanned Aircraft

Emergency Landing Decision Method for Unmanned Aircraft

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2021 International Conference on Unmanned Aircraft systems, ICUAS 2021

作者： Gomez, Aitor Ramirez La Cour-Harbo, Anders Aalborg University Automation and Control Department of Electronic Systems Fredrik Bajers Vej 7C Aalborg9220 Denmark

ISBN: (纸本)9780738131153

This paper describes a framework to generate a computationally low-cost decision function to automate emergency landings for drones. Specifically, this function makes a choice of which is the most suitable location to land an unmanned aircraft from a given list of candidate ground locations. The candidate ground locations are described by a distance metric from the aircraft to the landing location and by a probability safety measure associated to how safe it is to land in that particular location. In addition, an urgency level, associated with the current healthy status of the unmanned aircraft, and a tuning parameter that models its robustness are included in the decision function. These four parameters are assumed to be given and to have some particular properties, which are described further in the paper. © 2021 IEEE.

关键词： Location

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Online Optimization Approach for Calculating Basal Insulin Doses for Individuals With Type-2 Diabetes

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IEEE Transactions on control systems Technology 2025年

作者： Al Ahdab, Mohamad Knudsen, Torben Stoustrup, Jakob Leth, John Aalborg University Section of Automation and Control Department of Electronic Systems Aalborg9220 Denmark

This article presents a novel and computationally efficient approach for determining long-acting insulin doses in individuals with type-2 diabetes (T2D) without relying on a specific physiological model. The main objective is maintaining safe blood glucose (BG) levels within a targeted range. To achieve this, the strategy optimizes the parameters of a designated control law through an online optimization method combined with a gradient estimation technique that relies on noisy evaluations of an objective function. Two distinct control laws are employed and compared, along with two gradient estimation methods: recursive least squares (RLSs) and a one-point residual feedback method. Moreover, we explore the potential advantages of integrating continuous glucose monitoring (CGM) readings into the proposed framework for basal insulin dosing in T2D individuals. This approach is compared with the use of self-monitored BG (SMBG) devices alone. Through simulations with three different models, the proposed insulin calculation framework's performance surpasses existing strategies from the literature. The results also show that using CGM readings as feedback for long-acting insulin dose calculations significantly lowers the risk of hypoglycemia. Furthermore, the one-point residual feedback method outperformed RLS while. Finally, through the simulation results, we highlight the importance of the choice of the control law in the online optimization framework. © 1993-2012 IEEE.

关键词： Physiological models

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A Parkinson's Bradykinesia Recognition System Based on Deep Learning Method 12

A Parkinson's Bradykinesia Recognition System Based on Deep ...

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12th International Conference on CYBER Technology in automation, control, and Intelligent systems, CYBER 2022

作者： Tong, Lina Liu, Daisong Zhang, Mingjia Peng, Liang Department of State Key Laboratory of Management and Control for Complex Systems Institute of Automation China Academy of Science Beijing China School of Mechanical Electronic and Information Engineering Chinese University of Mining and Technology-Beijing Beijing China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Parkinson's disease is a neurodegenerative disease common in middle-aged and elderly people, and bradykinesia is one of the most obvious symptoms. In this study, A deep learning-based Parkinson's bradykinesia recognition system is designed which has an inertial sensor-based data acquisition system. It can wirelessly collect bradykinesia kinematic information by wearing it on the wrist and ankle of Parkinson's patients. In addition, a method for identifying the symptom of Parkinson's bradykinesia based on Long Short Term Memory (LSTM) Network is proposed, with an accuracy of 98.6%. It provides a feasible method to identify Parkinson bradykinesia to assist the diagnosis and treatment. © 2022 IEEE.

关键词： Neurodegenerative diseases

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An Experimental Research on Temperature Accuracy Algorithm in Fan Coil Thermostat 6

An Experimental Research on Temperature Accuracy Algorithm i...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Ari, Yunus Cücük, Ergün Karateke, Seda Institute of Graduate Studies Istanbul University - Cerrahpaşa Electric and Electronic Engineering Istanbul34320 Turkey Control and Automation Systems Industry and Trade Inc. Department of Research and Development Ges Teknik Air Conditioning Istanbul34852 Turkey Istanbul Topkapi University Faculty of Engineering Department of Computer Engineering Istanbul34087 Turkey

ISBN: (纸本)9798350346671

The efficient operation of HVAC&R systems are based on keeping indoor temperature and air quality at an optimum level without disturbing comfort. Starting from this point, in this experimental research, the factors affecting the measurement accuracy during the room temperature detection of a wall mount fan coil thermostat were examined. Among the external effects, the effect of the device components on the measurement was focused and the solution of the measurement deviations occurred in this extent was investigated. Based on the experiments, the algorithm that must be applied to reach the optimum temperature measurement of a room thermostat developed for Fan Coil systems was proposed. © 2023 IEEE.

关键词： Thermostats

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Online Maximum Likelihood Parameter Estimation for Continuously-Monitored Quantum systems

arXiv

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arXiv 2024年

作者： Clausen, Henrik Glavind Rouchon, Pierre Wisniewski, Rafal Section of Automation and Control Department of Electronic Systems Aalborg University Aalborg ØstDK-9220 Denmark Laboratoire de Physique de l'Ecole Normale Supérieure Mines Paris-PSL Inria ENS-PSL Université PSL CNRS Paris France

In this work, we consider the problem of online (real-time, single-shot) estimation of static or slow-varying parameters along quantum trajectories in quantum dynamical systems. Based on the measurement signal of a continuously-monitored quantum system, we propose a recursive algorithm for computing the maximum likelihood estimate of unknown parameters using an approach based on stochastic gradient ascent on the log-likelihood function. We formulate the algorithm in both discrete-time and continuous-time and illustrate the performance of the algorithm through simulations of a simple two-level system undergoing homodyne measurement from which we are able to track multiple parameters simultaneously. © 2024, CC BY-NC-ND.

关键词： Dynamical systems

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HAVOK Model Predictive control for Time-Delay systems with Applications to District Heating

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IFAC-PapersOnLine 2023年第2期56卷 2238-2243页

作者： Christian M. Jensen Mathias C. Frederiksen Carsten S. Kallesøe Jeppe N. Jensen Laurits H. Andersen Roozbeh Izadi-Zamanabadi Department of Electronic Systems Automation and Control Aalborg University 9210 Aalborg Denmark Grundfos A/S Poul Due Jensens Vej Bjerringbro Denmark Danfoss A/S Nordborgvej 81 Nordborg Denmark

A computationally efficient Model-Predictive control (MPC) approach is proposed for systems with unknown delay using only input/output data. We use the Koopman operator framework and the related Hankel Alternative View of Koopman (HAVOK) algorithm to identify a model in a basis of projected time-delay coordinates and demonstrate a novel MPC structure that reduces and bounds the computational complexity. The proposed HAVOK-MPC approach is validated experimentally on a laboratory-scale District Heating System (DHS), demonstrating excellent prediction and tracking performance while only requiring knowledge of a conservative upper bound on the system delay.

关键词： Modelling and system identification Delay systems District heating systems Dynamic Mode Decomposition Koopman operator Model Predictive control

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Learning-Based Predictive control with Gaussian Processes: An Application to Urban Drainage Networks

Learning-Based Predictive Control with Gaussian Processes: A...

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2022 American control Conference, ACC 2022

作者： Balla, Krisztian Mark Eringis, Deividas Al Ahdab, Mohamad Dimon Bendtsen, Jan Kallesoe, Carsten Skovmose Ocampo-Martinez, Carlos Aalborg University Section for Automation and Control Department of Electronic Systems Fredrik Bajers vej 7c AalborgDK-9220 Denmark Grundfos Holding A/S Technology Innovation Controls Department Poul Due Jensens vej 7 BjerringbroDK-8850 Denmark Universitat Politècnica de Catalunya Automatic Control Department Llorens i Artigas 4-6 Planta 2 Barcelona08028 Spain

ISBN: (数字)9781665451963

ISBN: (纸本)9781665451963

Many traditional control solutions in urban drainage networks suffer from unmodelled nonlinear effects such as rain and wastewater infiltrating the system. These effects are challenging and often too complex to capture through physical modelling without using a high number of flow sensors. In this article, we use level sensors and design a stochastic model predictive controller by combining nominal dynamics (hydraulics) with unknown nonlinearities (hydrology) modelled as Gaussian processes. The Gaussian process model provides residual uncertainties trained via the level measurements and captures the effect of the hydrologic load and the transport dynamics in the network. To show the practical effectiveness of the approach, we present the improvement of the closed-loop control performance on an experimental laboratory setup using real rain and wastewater flow data. © 2022 American Automatic control Council.

关键词： Stochastic models

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