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A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners

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arXiv 2019年

作者： Etxegarai, Urtats Portillo, Eva Irazusta, Jon Koefoed, Lucien Kasabov, Nikola Department of Automatic Control and System Engineering Faculty of Engineering University of the Basque Country UPV/EHU Bilbao Spain Department of Physiology Faculty of Medicine and Nursing University of the Basque Country UPV/EHU Leioa Spain Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

In this work, a heuristic as operational tool to estimate the lactate threshold and to facilitate its integration into the training process of recreational runners is proposed. To do so, we formalize the principles for the lactate threshold estimation from empirical data and an iterative methodology that enables experience based learning. This strategy arises as a robust and adaptive approach to solve data analysis problems. We compare the results of the heuristic with the most commonly used protocol by making a first quantitative error analysis to show its reliability. Additionally, we provide a computational algorithm so that this quantitative analysis can be easily performed in other lactate threshold protocols. With this work, we have shown that a heuristic (%60 of endurance running speed reserve), serves for the same purpose of the most commonly used protocol in recreational runners, but improving its operational limitations of accessibility and consistent use. Copyright © 2019, The Authors. All rights reserved.

关键词： Decision support systems

Quantized Deep Neural Network Based Optimal control of Greenhouses on a Microcontroller

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Quantized Deep Neural Network Based Optimal Control of Green...

European control Conference (ECC)

作者： Kiran Kumar Sathyanarayanan Philipp Sauerteig Pablo Zometa Stefan Streif Automatic Control and System Dynamics Lab Technische Universität Chemnitz Chemnitz Germany Faculty of Engineering German International University Berlin Germany Department of Bioresources Fraunhofer Institute for Molecular Biology and Applied Ecology Giessen Germany

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Growing crops in controlled-Environment Agriculture (CEA) farms, such as greenhouses and vertical farms, can help in meeting the demands of urban centers and achieving climate goals. Recently, many advanced control techniques like Model Predictive control (MPC) and its variants have been developed for energy-efficient operation and minimization of resource utilization. However, real-time implementation of these advanced strategies come along with certain computational hardware requirements, thus, increasing the operating costs. In this work, we propose to learn the MPC policy of a greenhouse control by means of a Deep Neural Network (DNN) in order to be implemented on a low-cost microcontroller. Additionally, we use a feedback law to reduce undesired quantization effects. The efficiency of our approach is exemplified by means of a simulation study for greenhouse control.

关键词： Quantization (signal) Microcontrollers Optimal control Greenhouses Artificial neural networks Minimization Real-time systems

High-Load Titanium Drilling Using an Accurate Robotic Machining system 9th

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High-Load Titanium Drilling Using an Accurate Robotic Machin...

9th IFIP International Precision Assembly Seminar, IPAS 2020

作者： Brownbill, Robert Silk, Philip Whiteside, Peter Hutabarat, Windo Burroughes, Harry Electroimpact UK Ltd. Manor Lane Hawarden DeesideCH5 3ST United Kingdom The Advanced Manufacturing Research Centre - The AMRC University of Sheffield Factory 2050 SheffieldS9 1ZA United Kingdom Department of Automatic Control and System Engineering University of Sheffield Portobello Street SheffieldS1 3JD United Kingdom

ISBN: (纸本)9783030726317

Robotic drilling systems have been used in the manufacture of large aerospace components for a number of years. systems have been developed by several systems integrators in order to accurately drill materials from CFRP to Titanium. These systems, however, have been unable to achieve large diameter holes in Titanium due to reduced structural stiffness and end effector capabilities. Typically, large holes are either drilled using large cartesian CNC-controlled machines or drilled using automated drilling units (ADU). However, there is a pull from aerospace OEMS to move away from large monolithic machines, in favour of flexible robotic system. Flexible robotic systems provide a number of benefits for large structure assembly. The following report primarily outlines drilling trials conducted on the Accurate Robotic Machining system, during which holes from 25 mm to 32 mm ID were drilled in titanium implementing an empirical test schedule. Additionally, a discussion on the benefits of drilling large diameter holes using flexible robotic platforms. © 2021, The Author(s).

关键词： Titanium

Multistability Analysis and Adaptive Feedback control on a New Financial Risk system

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International Journal of Applied and Computational Mathematics 2023年第5期9卷 1-16页

作者： Johansyah, Muhamad Deni Sambas, Aceng Vaidyanathan, Sundarapandian Benkouider, Khaled Sulaiman, Ibrahim Mohammed Department of Mathematics Universitas Padjadjaran Jatinangor Sumedang 45363 Indonesia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut Terengganu Besut 22200 Malaysia Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Tamansari Gobras Tasikmalaya 46196 Indonesia Center for Control System Vel Tech University Avaddi Chennai 60062 India Department of Non-Destructive Automatic Testing Laboratory Jijel University Rue Rouikha Mokhta Jijel 1800 Algeria School of Quantitative Science University Utara Malaysia Sintok Kedah Bukit Kayu Hitam 06010 Malaysia

This study presents the findings of a new financial risk system with one absolute function and two quadratic nonlinearities. The rich dynamic behaviors of the new financial risk system are discussed analytically and numerically through stability analysis, phase portrait, bifurcation diagram, Lyapunov exponent, multistability and coexisting attractors. In addition, a new financial risk system with two quadratic nonlinearities and one absolute function shows multistability and coexistence of chaotic attractors. Using adaptive feedback control, we established a new control law for fully synchronising the proposed chaotic financial systems with itself. To conclude, some numerical simulation was presented using MATLAB to illustrate the efficiency of the designed method. © 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Backstepping control Chaos Financial chaotic system Synchronisation

Distributed Nonconvex Optimization: Gradient-free Iterations and ϵ-Globally Optimal Solution

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arXiv 2020年

作者： He, Zhiyu He, Jianping Chen, Cailian Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Automatic Control Laboratory ETH Zurich Zurich8092 Switzerland

Distributed optimization utilizes local computation and communication to realize a global aim of optimizing the sum of local objective functions. This article addresses a class of constrained distributed nonconvex optimization problems involving univariate objectives, aiming to achieve global optimization without requiring local evaluations of gradients at every iteration. We propose a novel algorithm named CPCA, exploiting the notion of combining Chebyshev polynomial approximation, average consensus, and polynomial optimization. The proposed algorithm is i) able to obtain ϵ-globally optimal solutions for any arbitrarily small given accuracy ϵ, ii) efficient in both zeroth-order queries (i.e., evaluations of function values) and inter-agent communication, and iii) distributed terminable when the specified precision requirement is met. The key insight is to use polynomial approximations to substitute for general local objectives, distribute these approximations via average consensus, and solve an easier approximate version of the original problem. Due to the nice analytic properties of polynomials, this approximation not only facilitates efficient global optimization, but also allows the design of gradient-free iterations to reduce cumulative costs of queries and achieve geometric convergence for solving nonconvex problems. We provide a comprehensive analysis of the accuracy and complexities of the proposed algorithm. © 2020, CC BY-NC-SA.

关键词： Polynomial approximation

Mobil Mechatronic system with Applications in Agriculture and Sylviculture

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IFAC Proceedings Volumes 2002年第2期35卷 865-870页

作者： Ion Ion Ion Simionescu Adrian Curaj Technology of Machine Manufacturing Dept POLITEHNICA University Splaiul Independentei no. 313 Bucharest Romania Mechanism Robot Theory Dept POLITEHNICA University Splaiul Independentei no. 313 Bucharest Romania Automatic Control and System Engineering Department POLITEHNICA University Splaiul Independentei no. 313 Bucharest Romania

Walking mechatronic systems protected much better the environment when their contact with the soil is discrete, a fact that limits appreciately the area that is crushed. In order to make and to control a walking robot, one needs the knowledge of all walking potentialities since the choice of the number of legs as well as of their structures depend on the type of gait that has been selected. In the Mobil Robots Laboratory of the POLITEHNICA University of Bucharest, a four-legged modular mechatronic system has been built and tested, while a hexapod one is being tested.

关键词： robot mobile robots walking robot robot control controller

Private and Robust Distributed Nonconvex Optimization via Polynomial Approximation

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arXiv 2021年

There has been work that exploits polynomial approximation to solve distributed nonconvex optimization problems involving univariate objectives. This idea facilitates arbitrarily precise global optimization without requiring local evaluations of gradients at every iteration. Nonetheless, there remains a gap between existing guarantees and practical requirements, e.g., privacy preservation and robustness to network imperfections. To fill this gap and keep the above strengths, we propose a Private and Robust Chebyshev-Proxy-based distributed Optimization Algorithm (PR-CPOA). Specifically, to ensure both the accuracy of solutions and the privacy of local objectives, we design a new privacy-preserving mechanism. This mechanism leverages the randomness in blockwise insertions of perturbed vector states and hence provides a stronger privacy guarantee in the scope of (α, β)-data-privacy. Furthermore, to gain robustness against network imperfections, we use the push-sum consensus protocol as a backbone and discuss its specific enhancements. Thanks to the purely consensus-type iterations, we avoid the privacy-accuracy trade-off and the bother of selecting proper step sizes in different settings. We rigorously analyze the accuracy, privacy, and complexity of the proposed algorithm. We show that the advantages brought by introducing polynomial approximation are maintained when all the above requirements exist. © 2021, CC BY-NC-SA.

关键词： Polynomial approximation

Model-Free Nonlinear Feedback Optimization

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arXiv 2022年

作者： He, Zhiyu Bolognani, Saverio He, Jianping Dörfler, Florian Guan, Xinping Automatic Control Laboratory ETH Zürich Zürich8092 Switzerland Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

Feedback optimization is a control paradigm that enables physical systems to autonomously reach efficient operating points. Its central idea is to interconnect optimization iterations in closed-loop with the physical plant. Since iterative gradient-based methods are extensively used to achieve optimality, feedback optimization controllers typically require the knowledge of the steady-state sensitivity of the plant, which may not be easily accessible in some applications. In contrast, in this paper, we develop a model-free feedback controller for efficient steady-state operation of general dynamical systems. The proposed design consists of updating control inputs via gradient estimates constructed from evaluations of the nonconvex objective at the current input and at the measured output. We study the dynamic interconnection of the proposed iterative controller with a stable nonlinear discrete-time plant. For this setup, we characterize the optimality and stability of the closed-loop behavior as functions of the problem dimension, the number of iterations, and the rate of convergence of the physical plant. To handle general constraints that affect multiple inputs, we enhance the controller with Frank-Wolfe-type updates. © 2022, CC BY-SA.

关键词： Feedback control

Plant Uncertainty Contribution to QFT Tracking control Design

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IFAC Proceedings Volumes 2003年第11期36卷 517-522页

作者： M. Gil-Martínez M. García-Sanz System Engineering and Automation Group Electrical Engineering Department University of La Rioja. Luis de Ulloa 20 26004 Logroño SPAIN. Tf.:+34 941 299496 Automatic Control and Computer Science Department Public University of Navarra. Campus Arrosadía s/n 31006 Pamplona SPAIN Tf.:+34 948 16938

Tracking feedback control trade-offs increase dangerously with arbitrarily large uncertainties in the process model. This is shown by the bounds in the QFT domain. In this context, the paper develops a theory on the contribution of the plant uncertainty to the tracking QFT bounds through a serious study of tracking bound formulas. From this, a methodology for uncertainty fragmentation is developed. It hopes to loosen the bound toughness, or the control design trade-offs. Better feedback benefits can be achieved while reducing the high-frequency amplification of noises and disturbances at the plant input at the same time. Different QFT controllers in a controller-scheduler structure should drive different uncertainty boundaries.

关键词： Quantitative Feedback Theory Robust control Uncertain Dynamical systems