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Iterative Learning control for Switched Systems in the Presence of Input Saturation ⁎

IFAC-PapersOnLine 2020年第2期53卷 1444-1449页

作者： Pavel Pakshin Julia Emelianova Eric Rogers Krzysztof Galkowski Arzamas Polytechnic Institute of R.E. Alekseev Nizhny Novgorod State Technical University 19 Kalinina Street Arzamas 607227Russia School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ UK Institute of Control and Computation Engineering Universityof Zielona Góra ul. Szafrana 2 65-516 Zielona Góra Poland

The paper considers iterative learning control for differential and discrete switched linear systems with control input saturation. A new design is developed based on the use of common vector Lyapunov functions. An ex... 详细信息

关键词： iterative learning control switched systems input saturation repetitive processes stability vector Lyapunov function

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HIV and COVID-19 co-infection: A mathematical model and optimal control

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Informatics in Medicine Unlocked 2022年 31卷 100978页

作者： Ringa, N. Diagne, M.L. Rwezaura, H. Omame, A. Tchoumi, S.Y. Tchuenche, J.M. Data and Analytic Services British Columbia Centre for Disease Control 655 W 12th Ave Vancouver BC V5Z 4R4 Canada School of Population and Public Health University of British Columbia 2329 West Mall Vancouver BC V6T 1Z4 Canada Département de Mathématiques UFR des Sciences et Technologies Université de Thiès Thiès BP 967 Senegal Mathematics Department University of Dar es Salaam P.O. Box 35062 Dar es Salaam Tanzania Department of Mathematics Federal University of Technology Owerri Nigeria Abdus Salam School of Mathematical Sciences Government College University Lahore Pakistan Department of Mathematics and Computer Sciences ENSAI University of Ngaoundéré P.O. Box 455 Ngaoundéré Cameroon School of Computer Science and Applied Mathematics University of the Witwatersrand Private Bag 3 Wits 2050 Johannesburg South Africa School of Computational and Communication Sciences and Engineering Nelson Mandela African Institution of Science and Technology P.O. Box 447 Arusha Tanzania

A new mathematical model for COVID-19 and HIV/AIDS is considered to assess the impact of COVID-19 on HIV dynamics and vice-versa. Investigating the epidemiologic synergy between COVID-19 and HIV is important. The dynamics of the full model is driven by that of its sub-models;therefore, basic analysis of the two sub-models;HIV-only and COVID-19 only is carried out. The basic reproduction number is computed and used to prove local and global asymptotic stability of the sub-models’ disease-free and endemic equilibria. Using the fmincon function in the Optimization Toolbox of MATLAB, the model is fitted to real COVID-19 data set from South Africa. The impact of intervention measures, namely, COVID-19 and HIV prevention interventions and COVID-19 treatment are incorporated into the model using time-dependent controls. It is observed that HIV prevention measures can significantly reduce the burden of co-infections with COVID-19, while effective treatment of COVID-19 could reduce co-infections with opportunistic infections such as HIV/AIDS. In particular, the COVID-19 only prevention strategy averted about 10,500 new co-infection cases, with similar number also averted by the HIV-only prevention control. © 2022 The Author(s)

关键词： Basic reproduction number Co-infection COVID-19 HIV Optimal control

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AI drives the assessment of lung cancer microenvironment composition

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Journal of Pathology Informatics 2024年 15卷 100400-100400页

作者： Gallo, Enzo Guardiani, Davide Betti, Martina Arteni, Brindusa Ana Maria Di Martino, Simona Baldinelli, Sara Daralioti, Theodora Merenda, Elisabetta Ascione, Andrea Visca, Paolo Pescarmona, Edoardo Lavitrano, Marialuisa Nisticò, Paola Ciliberto, Gennaro Pallocca, Matteo Department of Pathology IRCCS Regina Elena National Cancer Institute Rome Italy Biostatistics Bioinformatics and Clinical Trial Center IRCCS Regina Elena National Cancer Institute Rome Italy Department of Computer Control and Management Engineering La Sapienza University of Rome Rome Italy UOC Anatomy Pathology Biobank IRCCS Regina Elena National Cancer Institute Istituti Fisioterapici Ospitalieri IFO Rome Italy Department of Radiological Oncological and Pathological Sciences Sapienza University of Rome Policlinico Umberto I Rome Italy Department of Experimental Medicine Sapienza University of Rome Policlinico Umberto I Rome Italy School of Medicine and Surgery University of Milano-Bicocca Monza 20900 Italy Tumor Immunology and Immunotherapy Unit IRCCS Regina Elena National Cancer Institute Rome Italy Scientific Direction IRCCS Regina Elena National Cancer Institute Rome Italy Institute of Experimental Endocrinology and Oncology National Research Council Naples Italy

Purpose: The abundance and distribution of tumor-infiltrating lymphocytes (TILs) as well as that of other components of the tumor microenvironment is of particular importance for predicting response to immunotherapy in lung cancer (LC). We describe here a pilot study employing artificial intelligence (AI) in the assessment of TILs and other cell populations, intending to reduce the inter- or intra-observer variability that commonly characterizes this evaluation. Design: We developed a machine learning-based classifier to detect tumor, immune, and stromal cells on hematoxylin and eosin-stained sections, using the open-source framework QuPath. We evaluated the quantity of the aforementioned three cell populations among 37 LC whole slide images regions of interest, comparing the assessments made by five pathologists, both before and after using graphical predictions made by AI, for a total of 1110 quantitative measurements. Results: Our findings indicate noteworthy variations in score distribution among pathologists and between individual pathologists and AI. The AI-guided pathologist's evaluations resulted in reduction of significant discrepancies across pathologists: three comparisons showed a loss of significance (p > 0.05), whereas other four showed a reduction in significance (p > 0.01). Conclusions: We show that employing a machine learning approach in cell population quantification reduces inter- and intra-observer variability, improving reproducibility and facilitating its use in further validation studies. © 2024 The Authors

关键词： computer-aided tool Digital pathology Lung cancer Machine learning NSCLC Pathology image QuPath Tumor-infiltrating lymphocytes Whole slide images

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Peeking behind the ordinal curtain: Improving distortion via cardinal queries

arXiv

引用

arXiv 2019年

作者： Amanatidis, Georgios Birmpas, Georgios Filos-Ratsikas, Aris Voudouris, Alexandros A. Department of Mathematical Sciences University of Essex United Kingdom ILLC University of Amsterdam Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Computer Science University of Liverpool United Kingdom School of Computer Science and Electronic Engineering University of Essex United Kingdom

Aggregating the preferences of individuals into a collective decision is the core subject of study of social choice theory. In 2006, Procaccia and Rosenschein considered a utilitarian social choice setting, where the agents have explicit numerical values for the alternatives, yet they only report their linear orderings over them. To compare different aggregation mechanisms, Procaccia and Rosenschein introduced the notion of distortion, which quantifies the inefficiency of using only ordinal information when trying to maximize the social welfare, i.e., the sum of the underlying values of the agents for the chosen outcome. Since then, this research area has flourished and bounds on the distortion have been obtained for a wide variety of fundamental scenarios. However, the vast majority of the existing literature is focused on the case where nothing is known beyond the ordinal preferences of the agents over the alternatives. In this paper, we take a more expressive approach, and consider mechanisms that are allowed to further ask a few cardinal queries in order to gain partial access to the underlying values that the agents have for the alternatives. With this extra power, we design new deterministic mechanisms that achieve significantly improved distortion bounds and, in many cases, outperform the best-known randomized ordinal mechanisms. We paint an almost complete picture of the number of queries required by deterministic mechanisms to achieve specific distortion bounds. Copyright © 2019, The Authors. All rights reserved.

关键词： Decision theory

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Research on the Preparation of Supercapacitor Perovskite and the Performance of Solar Cell Integrated Devices

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IOP Conference Series: Earth and Environmental Science 2021年第3期804卷

作者： Pei Jiang Yuhan Lu Ying Ma School of Control and Computer Engineering North China Electric Power University Baoding City Heibei Province 071003 China School of Economics and Management North China Electric Power University Baoding City Heibei Province 071003 China School of Electrical and Electronic Engineering North China Electric Power University Baoding City Heibei Province 071003 China

In today's world rely on fossil fuels is the main energy, causing a series of ecological environment problems, people have to put attention to the renewable energy, including solar energy with its access to such advantages as low cost, relatively stable, clean particularly favoured by people, and perovskite high conversion efficiency of solar cells and solar cells that category. As a new type of energy storage element, supercapacitor has the advantages of high specific energy, good cycle stability and environmental friendliness compared with traditional capacitors, while polyvinyl alcohol is easy to process, easy to form film and low price. In this paper, a perovskite solar cell-supercapacitor integrated device preparation method is proposed, and its performance is studied and analysed.

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computer vision based object grasping 6DoF robotic arm using picamera 4

Computer vision based object grasping 6DoF robotic arm using...

引用

4th International Conference on control, Automation and Robotics, ICCAR 2018

作者： Kumar, Vishal Wang, Qiang Minghua, Wang Rizwan, Syed Shaikh, S.M. Liu, Xuan Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9781538663387

This article presents a project to design a robust robotic arm which can perform multifunctional tasks. The controller of the manipulator is based on Arduino mega 2560 Microcontroller. The aim of the project is to focus all axes of manipulator to lift, carry and unload the objects at a desired location. This requires a precise drive motion control that incorporate electric motors as a drive system. Further experiments are done to implement a camera based 3D vision system integrated with a computer vision algorithm to recognize object deformation and spatial coordination to control the deviation from the original training. The 3D visualization systems are able to detect the objects as well as their distance from the End-effecter and transmit the signals to the drive system. The vision system requires a separate computing hardware capable of processing complex vision algorithms. We utilize Raspberry pi microcontroller for processing the vision data, separately making the vision system capable of recognizing the specified object as per program commands. © 2018 IEEE.

关键词： Robotic arms

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Performance Evaluation of CFB Unit Combustion System Based on Comprehensive Economics and Entropy Weight Method

Performance Evaluation of CFB Unit Combustion System Based o...

引用

International Conference on Sensing, Diagnostics, Prognostics, and control (SDPC)

作者： Ce Qin Mingming Gao Hongfu Zhang The State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9781728101996

ISBN: (纸本)9781728102009

A performance evaluation method for the combustion system in the variable load process of circulating fluidized bed (CFB) unit based on the minimum variance control is proposed. Each operating parameter are initially weighted according to the dynamic economic index of the operating parameters, and entropy weight method is used to adjust the weights of operating parameter under different operating conditions. Then, the minimum variance index based on comprehensive economic and entropy weight method is proposed to evaluate the performance of the combustion system of CFB unit, which reduces the polarization effect generated by the single weighting performance evaluation method and improves the objective scientificality of the operating parameter weighting. Finally, a case study on the combustion system of a 300MW CFB unit reveals that the minimum variance index based on the comprehensive economy and entropy weight method can better evaluate the performance of the combustion system in the dynamic process of the unit, compared with the traditional performance evaluation method. It is of great significance to the operational safety and economy of CFB boiler units.

关键词： Combustion Time series analysis Data models Performance evaluation Entropy Indexes Boilers

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Fault-tolerant Individual Pitch control using Adaptive Sliding Mode Observer

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IFAC-PapersOnLine 2018年第24期51卷 1127-1132页

作者： Liu, Yanhua Patton, Ron J. Lan, Jianglin School of Engineering and Computer Science University of Hull Cottingham Road HullHUG 7RX United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Portobello Street SheffieldS1 3JD United Kingdom

Due to the increasing size of wind turbines, the unbalanced loads caused by the uneven spatial distribution of wind speed and turbulence are becoming larger and larger. As has been proved, individual pitch control (IPC) can mitigate the blade asymmetric loads greatly in region 3. On the other hand, the pitch actuator faults can affect the pitching performance with slow dynamics, resulting in generator power instability and even deteriorating the unbalanced loads of blades. However, the effects of unbalanced blade loads deterioration caused by pitch actuator faults have not been taken into account by the traditional IPC design. In the present paper, a fault-tolerant control (FTC) strategy using adaptive sliding mode estimation is combined with a traditional IPC system based on two different control methods (Proportional-Integral and H∞ loop-shaping). It maintains the nominal pitch performance and removes the negative effects of pitch actuator faults on generator power and unbalanced blade loads perfectly. The effectiveness of the proposed strategy is verified on the 5MW NREL wind turbine system. © 2018

关键词： Adaptive control systems Actuators Deterioration Fault tolerance Sliding mode control Two term control systems Wind Wind turbines Actuator fault Adaptive sliding mode Adaptive sliding mode observer Fault tolerant control Individual pitch control Load reduction Proportional integral Sliding mode observers

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Randomised benchmarking for characterizing and forecasting correlated processes

arXiv

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arXiv 2023年

作者： Zhang, Xinfang Wu, Zhihao White, Gregory A.L. Xiang, Zhongcheng Hu, Shun Peng, Zhihui Liu, Yong Zheng, Dongning Fu, Xiang Huang, Anqi Poletti, Dario Modi, Kavan Wu, Junjie Deng, Mingtang Guo, Chu Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Physics and Astronomy Monash University VIC3800 Australia Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute of Physics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster and Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Quantum for NSW Sydney2000 Australia

The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning algorithms, we develop a method to learn the details of temporally correlated noise. In particular, we can learn the time-independent evolution operator of system plus bath and this leads to (i) the ability to characterize the degree of non-Markovianity of the dynamics and (ii) the ability to predict the dynamics of the system even beyond the times we have used to train our model. We exemplify this by implementing our method on a superconducting quantum processor. Our experimental results show a drastic change between the Markovian and non-Markovian regimes for the learning accuracies. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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Robust on-line ADP-based solution of a class of hierarchical nonlinear differential game

arXiv

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arXiv 2019年

作者： Satouri, Mohammad Reza Kebriaei, Hamed Razminia, Abolhassan Yazdanpanah, Mohammad Javad School of Electrical and Computer Engineering College of Engineering University of Tehran P.O. Box 4395-515 Tehran Iran Research Lab. Department of Electrical Engineering School of Engineering Persian Gulf University P.O. Box 75169 Boushehr Iran School of Electrical and Computer Engineering College of Engineering University of Tehran P.O. Box 4395-515 Tehran Iran Control & Intelligent Processing Center of Excellence

In this paper a hierarchical one-leader-multi-followers game for a class of continuous-time nonlinear systems with disturbance is investigated by a novel policy iteration reinforcement learning technique in which, the game model consists both of the zero-sum and nonzero-sum games, simultaneously. An adaptive dynamic programming (ADP) method is developed to achieve optimal control strategy under worst case of disturbance. This algorithm reduces the number of neural networks which are used for estimation for about thirty percent. Proposed algorithm uses neural networks to estimate value functions, control policies and disturbances. Convergence analysis of the estimations is investigated using Lyapunov theory and exploiting properties of the Nemytskii operator. Finally the simulation results will show effectiveness of developed ADP *** Codes 91A65, 49N70, 68T05, Copyright © 2019, The Authors. All rights reserved.

关键词： Nonlinear systems

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