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2021 China automation Congress, CAC 2021

作者： Liu, Yue Xiong, Gang Zhu, Fenghua Chen, Shichao Zhang, Liguo Liu, Xudong School of Artificial Intelligence and Automation Beijing University of Technology The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation The Cloud Computing Center Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Qingdao Academy of Intelligent Industries Chinese Academy of Sciences Beijing China Faculty of Information and Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781665426473

In the face of the rapid development of the IoT, the traditional cloud computing, while providing services for mobile intelligent devices, also brings problems such as network bandwidth occupation and communication delay. Edge computing can solve these problems to some extent. But too many offloaded tasks may result in an edge server becoming overloaded and execution delay of tasks increasing, the computing resources of idle edge devices are also not fully utilized. In order to make full use of the computing resources of idle edge devices in the local network and reduce the execution delay for computing tasks, this paper takes the average delay time for all end devices as the optimization objective and proposes an end-edge cooperative scheduling (EECS) model to schedule tasks for edge computing. The scheduling algorithm used in EECS model is improved based on MCT algorithm. We use the EdgeCloudSim to verify the EECS model and scheduling algorithm. The simulation results show that the average completion time of computing tasks in EECS model, compared with only single edge server (SEE) task computing model, can be reduced by up to three times. In addition, the system load can be balanced to a certain extent in local network. © 2021 IEEE

关键词： Edge computing

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Design and Experiment of a Magnetic Shape Memory Alloy Actuator 3

Design and Experiment of a Magnetic Shape Memory Alloy Actua...

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3rd International Academic Exchange Conference on Science and Technology Innovation, IAECST 2021

作者： Zeng, Yulu Zhu, Zhifang Wan, Jiaxin Zhao, Ran Huang, Senlin Nanchang Institute of Technology Jiangxi Province Key Laboratory of Precision Drive Control Nanchang China Faculty of Mechanical Engineering and Automation Nanchang Institute of Technology Jiangxi Province Key Laboratory of Precision Drive Control Zhejiang Sci-Tech University Nanchang China Zhongyuan University of Technology Zhongyuan-Petersburg Aviation College Zhengzhou China

ISBN: (纸本)9781665402675

This paper presented a large displacement precision actuator based on magnetic shape memory alloy (MSMA). A Ni-Mn-Ga rod was chosen as the driving source for the proposed actuator. The structure of the actuator was designed, and the its parameters are determined by calculation. The magnetic field is simulated by the finite element simulation software. After determining that the magnetic field meets the requirements, the prototype is made for experiments. The experimental results show that the maximum output displacement of the magnetic shape memory alloy actuator reaches 1.07mm when the pre-stress is 0 MPa. Which indicates that the design of the device is reasonable and is of great significance for broadening the application field of micro-displacement actuators. © 2021 IEEE.

关键词： Magnetic fields

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Demand Tracking control in Manufacturing Systems

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IFAC-PapersOnLine 2020年第2期53卷 11219-11224页

作者： Khaled A.A.A. Othman Thomas Meurer Chair of Automatic Control Faculty of Engineering Kiel University 24143 Kiel Germany

The purpose of this research is to design optimal boundary control to solve demand tracking problems for manufacturing systems represented at the factory level in terms of conservation laws coupled with ordinary differential equations. The factory level is modeled as a network with arcs describing specific production policies, e.g., velocity, processing rate, number of machines, and each vertex represents the buffer zone. Different interconnection topologies that correspond to dispersing and merging networks are considered. Numerical solutions are performed using direct and indirect methods.

关键词： Manufacturing systems Production systems Flow control Conservation laws Boundary control Optimal control Continuum models

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Dissipative PI control for a class of semilinear heat equations with actuator disturbance

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IFAC-PapersOnLine 2020年第2期53卷 7503-7508页

作者： A. Schaum P. Feketa T. Meurer Chair of Automatic Control Faculty of engineering Kiel University 24143 Kiel Germany

The problem of dissipative proportional-integral (PI) output-feedback control for a class of semilinear heat equations with actuator disturbance is addressed. Sufficient conditions for strict dissipativity in the state and thus exponential stability of the closed-loop system are derived which are stated in terms of the dissipavity properties of the nonlinearity, the controller gains and the actuator and sensor shape functions (i.e., their form and localization). Based on these conditions a dissipation maximization procedure is proposed to appropriately choose the degrees of freedom using optimization algorithms. Numerical simulation results illustrate the performance of the proposed controller.

关键词： Semilinear partial differential equations PI control dissipativity actuator disturbance

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Analytical Center of Mass Trajectory Generation for Humanoid Walking and Running with Continuous Gait Transitions

Analytical Center of Mass Trajectory Generation for Humanoid...

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IEEE-RAS International Conference on Humanoid Robots

作者： Tobias Egle Johannes Englsberger Christian Ott Faculty of Electrical Engineering and Information Technology TU Wien Tobias Egle and Christian Ott are with the Automation and Control Institute Vienna Austria Institute of Robotics and Mecha-tronics German Aerospace Center (DLR) Wessling Germany

ISBN: (纸本)9798350309805

We present an analytical trajectory generation framework for the combined computation of multiple walking and running sequences with continuous gait transitions. This framework builds on the Divergent Component of Motion (DCM)-based walking algorithm and the spline-based trajec-tory generation of the Biologically Inspired Deadbeat (BID) control for running. We describe our approach to generating closed-form center of mass (CoM) trajectories for walking and running by alternately linking the two gaits through continuity constraints. Thereby, we distinguish between vertical and horizontal planning. The vertical trajectory is computed in a forward recursion from the first to the last gait sequence. Due to the coupling of the gait sequences in the horizontal direction, we show the efficient generation of the horizontal CoM trajectory in a single matrix calculation. Subsequently, we unify the control strategies using a DCM tracking controller for the complete trajectory and integrate the proposed framework into an inverse dynamics-based whole-body controller. Finally, the presented approaches are validated in simulations with the humanoid robot Toro.

关键词： Legged locomotion Couplings Humanoid robots Biology Trajectory Planning Splines (mathematics)

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Target Capturing in an Ellipsoidal Region with a Swarm of Quadrotor UAVs

Target Capturing in an Ellipsoidal Region with a Swarm of Qu...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： M. Alp Merzi Veysel Gazi Giuseppe Fedele Luigi D’ Alfonso Antonio Bono Dept. Electrical and Electronics Eng. Faculty of Engineering Marmara University Istanbul Turkey Dept. Control and Automation Eng. Faculty of Electrical and Electronics Engineering Yildiz Technical University Istanbul Turkey Dept. of Informatics Modeling Electronics and Systems Eng. University of Calabria Rende Italy

ISBN: (数字)9781665405935

ISBN: (纸本)9781665405942

In a recent paper [1], we developed a target capturing strategy for swarms composed of double integrator agents. In this paper, we build on the results in [1] and focus on the implementation of the methodology for a swarm composed of quadrotor UAVs. We utilize both MATLAB and ROS environments under realistic conditions for that purpose. In ROS, we utilize Ultra-Violet LED blinkers based Ultra-Violet Direction And Ranging (UVDAR) system for relative localization. The sensing and localization errors serve as realistic errors for the assumptions in [1] for the uncertainties of the velocity and acceleration of the target. We verify in a realistic scenario that the agents converge to a user-defined ellipsoidal ring around the target despite the uncertainties and the more realistic agent dynamics.

关键词： Location awareness Uncertainty Ultraviolet sources Light emitting diodes Distance measurement Sensors Aircraft

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Non-crossing Quantile Regression Neural Network as a Calibration Tool for Ensemble Weather Forecasts

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Advances in Atmospheric Sciences 2024年第7期41卷 1417-1437页

作者： Mengmeng SONG Dazhi YANG Sebastian LERCH Xiang'ao XIA Gokhan Mert YAGLI Jamie M.BRIGHT Yanbo SHEN Bai LIU Xingli LIU Martin Janos MAYER School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin150001China Heidelberg Institute for Theoretical Studies Schloss-Wolfsbrunnenweg 3569118HeidelbergGermany Chair of Statistical Methods and Econometrics Karlsruhe Institute of Technology(KIT)Bluecherstr.1776185KarlsruheGermany Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China Solar Energy Research Institute of Singapore(SERIS) National University of Singapore(NUS)Singapore117574Singapore UK Power Networks LondonSE61NPUK China Meteorological Administration Beijing100081China Heilongjiang Meteorological Bureau Harbin150001China Department of Energy Engineering Faculty of Mechanical EngineeringBudapest University of Technology and EconomicsMűegyetem rkp.3H-1111BudapestHungary

Despite the maturity of ensemble numerical weather prediction(NWP),the resulting forecasts are still,more often than not,*** such,forecast calibration tools have become *** those tools,quantile regression(QR)is highly competitive in terms of both flexibility and predictive ***,a long-standing problem of QR is quantile crossing,which greatly limits the interpretability of QR-calibrated *** this point,this study proposes a non-crossing quantile regression neural network(NCQRNN),for calibrating ensemble NWP forecasts into a set of reliable quantile forecasts without *** overarching design principle of NCQRNN is to add on top of the conventional QRNN structure another hidden layer,which imposes a non-decreasing mapping between the combined output from nodes of the last hidden layer to the nodes of the output layer,through a triangular weight matrix with positive *** empirical part of the work considers a solar irradiance case study,in which four years of ensemble irradiance forecasts at seven locations,issued by the European Centre for Medium-Range Weather Forecasts,are calibrated via NCQRNN,as well as via an eclectic mix of benchmarking models,ranging from the naïve climatology to the state-of-the-art deep-learning and other non-crossing *** and stringent forecast verification suggests that the forecasts post-processed via NCQRNN attain the maximum sharpness subject to calibration,amongst all ***,the proposed conception to resolve quantile crossing is remarkably simple yet general,and thus has broad applicability as it can be integrated with many shallow-and deep-learning-based neural networks.

关键词： ensemble weather forecasting forecast calibration non-crossing quantile regression neural network CORP reliability diagram post-processing

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Fast calibration of agent-based model using mean-field approach 1

Fast calibration of agent-based model using mean-field appro...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Lu, Wanze Xiong, Gang Liu, Xudong Liu, Sheng Ye, Peijun Zhang, Liguo Beijing University of Technology Faculty of Information and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665433372

Calibration of simulation system is an important step to establish a reliable simulation system. In this paper, based on the existing mean field calibration theory, a new fast calibration method for complex urban traffic system based on mean field method is discussed by establishing the relationship between the macroscopic observation quantity and the proxy microscopic parameters. This method makes use of the machine learning method, and reduces the dimension of the state vector in the discrete time period, so that the dimension of the macroscopic state transition matrix is lower, and then reduces the computational complexity of the system calibration. Finally, the calibration results of the simulation system were verified by SUMO traffic simulation software. © 2021 IEEE.

关键词： Calibration

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An interpretability analysis of travel decision learning in cyber-physical-social-systems 1

An interpretability analysis of travel decision learning in ...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Guo, Miao Ye, Peijun Liu, Xudong Liu, Sheng Xiong, Gang Zhang, Liguo Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China Faculty of Information and Technology Beijing University of Technology Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

In the few decades, the rise of Internet and social media has fundamentally changed the management, control, and operation modes of modern engineering and social systems like defense, energy, critical health care and ... 详细信息

ISBN: (纸本)9781665433372

关键词： Deep learning Social networking (online) Scalability Perturbation methods Neurons Transportation Transforms

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On the dual implementation of collision-avoidance constraints in path-following MPC for underactuated surface vessels

arXiv

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arXiv 2021年

作者： Helling, Simon Roduner, Christian Meurer, Thomas Chair of Automatic Control Faculty of Engineering Kiel University Kiel24143 Germany AVL Software and Functions GmbH Regensburg93059 Germany

A path-following collision-avoidance model predictive control (MPC) method is proposed which approximates obstacle shapes as convex polygons. Collision-avoidance is ensured by means of the signed distance function which is calculated efficiently as part of the MPC problem by making use of a dual formulation. The overall MPC problem can be solved by standard nonlinear programming (NLP) solvers. The dual signed distance formulation yields, besides the (dual) collision-avoidance constraints, norm, and consistency constraints. A novel approach is presented that combines the arising norm equality with the dual collision-avoidance inequality constraints to yield an alternative formulation reduced in complexity. Moving obstacles are considered using separate convex sets of linearly predicted obstacle positions in the dual problem. The theoretical findings and simplifications are compared with the often-used ellipsoidal obstacle formulation and are analyzed with regard to efficiency by the example of a simulated path-following autonomous surface vessel during a realistic maneuver and AIS obstacle data from the Kiel bay area. Copyright © 2021, The Authors. All rights reserved.

关键词： Model predictive control

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