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arXiv 2020年

作者： Theodosis, Dionysios Berkane, Soulaimane Dimarogonas, Dimos V. Dynamic Systems and Simulation Laboratory School of Production Engineering and Management Technical University of Crete Greece Département d’informatique et d’ingénierie Université du Québec en Outaouis GatineauQC Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper deals with the problem of state estimation for a class of linear time-invariant systems with quadratic output measurements. An immersion-type approach is presented that transforms the system into a state-affine system by adding a finite number of states to the original system. Under suitable persistence of excitation conditions on the input and its higher derivatives, global state estimation is exhibited by means of a Kalman-type observer. A numerical example is provided to illustrate the applicability of the proposed observer design for the problem of position and velocity estimation for a vehicle navigating in the n−dimensional Euclidean space using a single position range measurement. Copyright © 2020, The Authors. All rights reserved.

关键词： State estimation

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Guidance on the use of complex systems models for economic evaluations of public health interventions

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HEALTH ECONOMICS 2023年第7期32卷 1603-1625页

作者： Breeze, Penny R. Squires, Hazel Ennis, Kate Meier, Petra Hayes, Kate Lomax, Nik Shiell, Alan Kee, Frank de Vocht, Frank O'Flaherty, Martin Gilbert, Nigel Purshouse, Robin Robinson, Stewart Dodd, Peter J. Strong, Mark Paisley, Suzy Smith, Richard Briggs, Andrew Shahab, Lion Occhipinti, Jo-An Lawson, Kenny Bayley, Thomas Smith, Robert Boyd, Jennifer Kadirkamanathan, Visakan Cookson, Richard Hernandez-Alava, Monica Jackson, Christopher H. Karapici, Amanda Sassi, Franco Scarborough, Peter Siebert, Uwe Silverman, Eric Vale, Luke Walsh, Cathal Brennan, Alan School of Health and Related Research University of Sheffield Sheffield UK British Medical Journal Technology Appraisal Group London UK MRC/CSO Social and Public Health Sciences Unit University of Glasgow Scotland UK School of Geography University of Leeds Leeds UK Department of Public Health LaTrobe University Melbourne Australia Centre for Public Health Queen's University Belfast Belfast UK Population Health Sciences Bristol Medical School University of Bristol Bristol UK NIHR Applied Research Collaboration West (ARC West) Bristol UK Department of Public Health Policy and Systems University of Liverpool Liverpool UK CRESS University of Surrey Guildford UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Business School University of Newcastle Newcastle UK Lumanity-HEOR South Yorkshire Sheffield UK College of Medicine and Health University of Exeter Exeter UK London School of Hygiene & Tropical Medicine London UK Department of Behavioural Science and Health UCL London UK Brain and Mind Centre University of Sydney New South Wales Camperdown Australia United Kingdom Health Security Agency Birmingham UK MRC/CSO Social and Public Health Sciences Unit University of Glasgow Glasgow UK Centre for Health Economics University of York Heslington UK MRC Biostatistics Unit University of Cambridge Cambridge UK NIHR SPHR London School of Hygiene and Tropical Medicine London UK Centre for Health Economics & Policy Innovation Imperial College Business School London UK Nuffield Department of Population Health University of Oxford Oxfordshire Oxford UK Department of Public Health Health Services Research and Health Technology Assessment UMIT TIROL - University for Health Sciences and Technology Hall in Tirol Tyrol Austria Division of Health Technology Assessment and Bioinformatics ONCOTYROL - Center for Personalized Cancer Medicine Innsbruck Austria Center for Health Decision Science Departments of Epidemio

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed;principles for designing a complex systems model;and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

关键词： complex systems economic modeling public health

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

arXiv

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arXiv 2020年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Department of Electrical Engineering University of North Texas DentonTX76203 United States The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is considered. This problem is an important component of many machine learning techniques with data parallelism, such as deep learning and federated learning. We propose a distributed primal–dual stochastic gradient descent (SGD) algorithm, suitable for arbitrarily connected communication networks and any smooth (possibly nonconvex) cost functions. We show that the proposed algorithm achieves the linear speedup convergence rate O(1/√nT) for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak–Lojasiewicz (P–L) condition, where T is the total number of iterations. We also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global optimum. We demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Cost functions

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A Demand Response Framework to Overcome Network Overloading in Power Distribution Networks ⁎

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IFAC-PapersOnLine 2020年第2期53卷 13339-13344页

作者： Muhammad Jibran Hasan Arshad Nasir Faran Qureshi Usman Ali Colin Jones School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad 44000 Pakistan Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal 23955 Saudi Arabia Automatic Control Lab in Ecole Polytechnique Fédérale de Lausanne Lausanne CH-1015 Switzerland

This paper considers the problem of network overloading in the power distribution networks of Pakistan, often resulting from the inability of the transmission system to transfer power from source to end-user during peak loads. This results in frequent power-outages and consumers at such times have to rely on alternative energy sources, e.g. Uninterrupted Power Supply (UPS) systems with batteries to meet their basic demand. In this paper, we propose a demand response framework to eliminate the problem of network overloading. The flexibility provided by the batteries at different houses connected to the same grid node is exploited by scheduling the flow of power from mains and batteries and altering the charging-discharging patterns of the batteries, thereby avoiding network overloading and any tripping of the grid node. This is achieved by casting the problem in an optimal control setting based on a prediction of power demand at a grid node and then solving it using a model predictive control strategy. We present a case study to demonstrate the application and efficacy of our proposed framework.

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Prescribed Performance control Guided Policy Improvement for Satisfying Signal Temporal Logic Tasks

Prescribed Performance Control Guided Policy Improvement for...

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American control Conference

作者： Peter Varnai Dimos V. Dimarogonas Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology 114 28 Stockholm Sweden

ISBN: (纸本)9781538679012;9781538679265

Signal temporal logic (STL) provides a user-friendly interface for defining complex tasks for robotic systems. Recent efforts aim at designing control laws or using reinforcement learning methods to find policies which guarantee satisfaction of these tasks. While the former suffer from the trade-off between task specification and computational complexity, the latter encounter difficulties in exploration as the tasks become more complex and challenging to satisfy. This paper proposes to combine the benefits of the two approaches and use an efficient prescribed performance control (PPC) base law to guide exploration within the reinforcement learning algorithm. The potential of the method is demonstrated in a simulated environment through two sample navigational tasks.

关键词： Religious Missions Temporal logic Exploration Simulated Environment Policies Satisfaction Learning Learning methods control law signals

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Prescribed performance control guided policy improvement for satisfying signal temporal logic tasks

arXiv

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arXiv 2019年

作者： Varnai, Peter Dimarogonas, Dimos V. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm114 28 Sweden

Signal temporal logic (STL) provides a userfriendly interface for defining complex tasks for robotic systems. Recent efforts aim at designing control laws or using reinforcement learning methods to find policies which guarantee satisfaction of these tasks. While the former suffer from the trade-off between task specification and computational complexity, the latter encounter difficulties in exploration as the tasks become more complex and challenging to satisfy. This paper proposes to combine the benefits of the two approaches and use an efficient prescribed performance control (PPC) base law to guide exploration within the reinforcement learning algorithm. The potential of the method is demonstrated in a simulated environment through two sample navigational tasks. Copyright © 2019, The Authors. All rights reserved.

关键词： Temporal logic

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Gradient-Based STL control with Application to Nonholonomic systems

arXiv

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arXiv 2019年

作者： Varnai, Peter Dimarogonas, Dimos V. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm114 28 Sweden

In this paper, we study the control of dynamical systems under temporal logic task specifications using gradient-based methods relying on quantitative measures that express the extent to which the tasks are satisfied. A class of controllers capable of providing satisfaction guarantees for simple systems and specifications is introduced and then extended for the case of unicycle-like dynamics. The possibility of combining such controllers in order to tackle more complex task specifications while retaining their computational efficiency is examined, and the practicalities related to an effective combination are demonstrated through a simulation study. The introduced framework for controller design lays ground for future work in the direction of effectively combining such elementary controllers for the purpose of aiding exploration in learning algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： controllers

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controlling a Networked SIS Model via a Single Input over Undirected Graphs ⁎

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IFAC-PapersOnLine 2020年第2期53卷 10981-10986页

作者： Dan Wang Ji Liu Philip E. Paré Wei Chen Li Qiu Carolyn L. Beck Tamer Başar Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong China Department of Electrical and Computer Engineering Stony Brook University NY 11794 USA Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Mechanics and Engineering Science & Beijing Innovation Center for Engineering Science and Advanced Technology Peking University Beijing China Coordinated Science Laboratory University of Illinois at Urbana-Champaign IL 61801 USA

This paper formulates and studies the problem of controlling a networked SIS model using a single input in which the network structure is described by a connected undirected graph. A necessary and sufficient condition on the values of curing and infection rates for the healthy state to be exponentially stable is obtained via the analysis of signed Laplacians when the control input is the curing budget of a single agent. In the case when the healthy state is stabilizable, an explicit expression for the minimum curing budget is provided. The utility of the algorithm is demonstrated using a simulation over a network of cities in the northeastern United States.

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Verification of AA-Diagnosability in Probabilistic Finite Automata is PSPACE-Hard

Verification of AA-Diagnosability in Probabilistic Finite Au...

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IEEE Annual Conference on decision and control

作者： Christoforos Keroglou Christoforos N. Hadjicostis Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

In this paper we consider the complexity of verifying the property of AA-diagnosability in probabilistic finite automata and establish that AA-diagnosability is, in general, a PSPACE-hard problem. In deterministic and nondeterministic finite automata, the property of diagnosability captures our ability to determine, based on our observation of the activity in a given finite automaton, the occurrence of any fault event, at least if we wait for at most a finite number of events (following the occurrence of the unobservable fault event). In stochastic settings where the underlying system is a probabilistic finite automaton under partial observation, there is not a prevalent notion of diagnosability and many variations have been proposed, including A-diagnosability and AA-diagnosability. Earlier work has shown that the verification of A-diagnosability (also referred to as strong stochastic diagnosability) for a given probabilistic finite automaton is a PSPACE-hard problem. In this paper, we establish that the verification of AA-diagnosability (also referred to as stochastic diagnosability) is a PSPACE-hard problem.

关键词： Automata Hidden Markov models Probabilistic logic Markov processes Complexity theory Fault diagnosis

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Hierarchic Stabilization of Flying Convex-Path-Following Formations Part II: Underactuated Agents

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IFAC-PapersOnLine 2019年第12期52卷 352-357页

作者： Mohamed I. El-Hawwary Department of Electrical Power Engineering Faculty of Engineering Cairo University Giza 12613 Egypt Division of Decision and Control Systems School of Electrical Engineering & Computer Science KTH Royal Institute of Technology SE-100 44 Stockholm Sweden

In this paper the flying convex-path-following formations problem (FCxPFF) is solved for two cases of underactuated rigid bodies. In the first case the the rigid bodies have a single degree of underactuation with two thrusts and three torques. In the second, they have two degrees of underactuation with a single thrust. The solution builds on the one developed for fully-actuated agents in Part I of the paper. In addition, the way the solution is tailored for underactuation relies on further utilization of hierarchic set stabilization, and reduction. Additional remarks on the benefits of the approach, and simulation results of the proposed solutions are presented.

关键词： Formation control distributed stabilization underactuated systems hierarchical control reduction

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