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Smooth controller design for non-linear systems using multiple fixed models

IET control Theory & Applications 2017年第9期11卷 1467-1473页

作者： Jie Chen Wei Chen Jian Sun The Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing Institute of Technology Beijing People's Republic of China Science and Technology on Electronic Information Control Laboratory Chengdu People's Republic of China

Multiple model adaptive control (MMAC) with second-level adaptation is a recently proposed methodology for dealing with systems where the parametric uncertainty is large. Compared with the multiple model switching scheme, the new scheme can lead to significant improvements in performance. Some research has been conducted using the new scheme, but all of the results concern linear systems with an adaptive identification model set. In this study, MMAC with second-level adaptation scheme is extended to non-linear systems in strict feedback form, and the fixed identification model set is under consideration. This is motivated by the fact that a smooth controller can lead to smooth performance and the fixed identification model set gains potential advantages over the adaptive identification model set, especially for the case that the parameters of the system change over the time. Design details are presented and the stability of MMAC with second-level adaptation using a fixed identification model set for non-linear systems is given, which has not been discussed before. Finally, two simulations are performed to show that this scheme performs much better than conventional schemes, including adaptive control and multiple-model switching schemes, in terms of convergence speed and transient performance.

关键词： nonlinear control systems control system synthesis adaptive control uncertain systems linear systems identification convergence transient performance convergence speed fixed identification model set second-level adaptation scheme adaptive identification model set linear systems multiple model switching scheme parametric uncertainty MMAC multiple model adaptive control multiple fixed models nonlinear systems smooth controller design

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Experimental Model Identification of Liquid-Circular Angular Accelerometer using Subspace Method 35

Experimental Model Identification of Liquid-Circular Angular...

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第35届中国控制会议

作者： WANG Meiling LI Xiang CHENG Siyuan FU Mengyin XIAO Meifeng Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Nanjing University of Science and Technology

ISBN: (纸本)9781509009107

In this paper, the model of a novel liquid-circular angular accelerometer is studied. Due to the absence of theoretical model of liquid-circular angular accelerometer, a subspace identification method(SIM) based on Akaike Information Criterion(AIC) is chosen for model identification of angular accelerometer. The proposed identification method is tested on a liquid-circular angular accelerometer prototype. The experimental results indicate that SIM could obtain a more accurate model than least square method, with a degree of fitting above 90%. In addition, SIM possesses good repeatability and stability. The experimental model identified by SIM in this paper can be applied in engineering practice.

关键词： system Identification Angular Accelerometer Subspace Method

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Self adaptation of chimera states

arXiv

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arXiv 2018年

作者： Yao, Nan Huang, Zi-Gang Ren, Hai-Peng Grebogi, Celso Lai, Ying-Cheng Department of Applied Physics Xi’an University of Technology Xi’an710048 China School of Life Science and Technology Xi’an Jiao Tong University Xi’an710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Institute for Complex Systems and Mathematical Biology King’s College University of Aberdeen AberdeenAB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of "intelligence" in achieving robustness through self adaptation. The behavior can be exploited for controlled generation of chimera states with their coherent component placed in any desired spatial region of the system. Copyright © 2018, The Authors. All rights reserved.

关键词： Dynamical systems

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Preliminary research on modeling and simulation technology of artificial intelligence system

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IOP Conference Series: Materials science and Engineering 2018年第4期452卷

作者： Kaiyue Li Lei Liu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing 100074 China. Beijing Electro-Mechanical Engineering Institute Beijing 100074 China.

The complex system of large-scale intelligent, concurrent and polymorphic organizational structure is a hot topic in the field of simulation. Qualitative and quantitative research on such systems requires integration of related technologies in the fields of computer simulation, system theory, and artificial intelligence. Mufti-agent simulation uses system theory and Mufti-agent system modelling method to build a system high-level model, and uses the system computing model established for the simulation software and hardware support technology based on the agent model to realize the simulation. Because it can effectively deal with the interlinear, interactivity and emergence of complex systems, it is considered to be the most dynamic and breakthrough methodology for complex system simulation. Based on this paper, the concept, theoretical method, technology and application of intelligent system engineering are mainly discussed. The application of artificial intelligence in modelling and simulation is analysed with examples.

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Robust sampled-data control for Itô stochastic Markovian jump systems with state delay

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International Journal of Robust and Nonlinear control 2018年第15期28卷

作者： Guoliang Chen Jian Sun Jianwei Xia School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China School of Mathematics Science Liaocheng University Liaocheng China

In this paper, the problem of robust sampled-data control for Itô stochastic Markovian jump systems (Itô SMJSs) with state delay is investigated. Using parameters-dependent Lyapunov functionals and some stochastic equations, we give stochastic sufficient stability criteria for polytopic uncertain Itô SMJSs. As a corollary, stochastic sufficient stability criteria are given for nominal Itô SMJSs. For this two cases of Itô SMJSs, based on the obtained stochastic stability criteria, their time-independent sampled-data controllers are designed, respectively. Then, for designing a time-dependent sampled-data controller for Itô SMJSs, a parameters-dependent time-scheduled Lyapunov functional is developed. New stochastic sufficient stability criteria are obtained for polytopic uncertain Itô SMJSs and nominal Itô SMJSs. Furthermore, their time-dependent sampled-data controllers are designed, respectively. Lastly, a numerical example is provided to illustrate the effectiveness of the proposed method.

关键词： Itô stochastic Markovian jump systems parameters-dependent time-scheduled Lyapunov functional robust sampled-data control stability

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Model predictive control for UGV trajectory tracking based on dynamic model

Model predictive control for UGV trajectory tracking based o...

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2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016

作者： Meiling, Wang Zhen, Wang Yi, Yang Mengyin, Fu Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781509041022

In this paper, a simplified dynamic vehicle model is established to accurately describe the dynamics of Unmanned Ground Vehicle (UGV) in trajectory tracking, while meeting the real-Time computing requirement. And a modified model predictive control (MPC) algorithm with soft constraint for UGV trajectory tracking is proposed to improve the tracking stability and rapidity. The optimal control problem at each sampling time is converted into a quadratic program (QP), which has mature solutions. To verify the trajectory tracking capabilities, the proposed MPC controller is compared with a PD controller under different longitudinal velocities. The simulation results demonstrate that the MPC controller can effectively reduce the tracking error and ensure the vehicle's traveling smoothness. © 2016 IEEE.

关键词： Model predictive control

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An online state and parameter estimation of dynamic state space model of high speed train

International Journal of Control and Automation

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International Journal of control and Automation 2016年第9期9卷 51-62页

作者： Xie, Guo Zhang, Dan Hei, Xinhong Qian, Fucai Takahashi, Sei Nakamura, Hideo Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an Shaanxi710048 China College of Science and Technology Nihon University 7-24-1 Narashinodai Funabashi Chiba274-8501 Japan

In this paper, the state space model of high speed train is established to describe its nonlinear dynamic characteristics, whose parameters are disturbed by noise with an arbitrary distribution, and an online state and parameter identification method is proposed based on a parameters set by employing Bayesian theory and Particle Filter (PF). Firstly, the priori probabilities of all of the possible parameters are set to be equal, and the predicted states with different parameters are estimated using PF. Then the posterior probabilities of the parameters are updated by analyzing the characteristic of the measurement noise using Bayesian theory. Finally, the system sate and parameter are estimated by weighted summing all of the parameters and predicted states. The simulation results indicate that the proposed method can estimate the states and parameters of high speed train online and adaptively. © 2016 SERSC.

关键词： State space methods

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Non-contact transportation and rotation of micro objects by vibrating glass needle circularly under water

Non-contact transportation and rotation of micro objects by ...

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2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Liu, Xiaoming Kojima, Masaru Shi, Qing Wang, Huaping Sun, Tao Mae, Yasushi Huang, Qiang Arai, Tatsuo Fukuda, Toshio Intelligent Robotics Institute School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China Department of Systems Innovation Osaka University 1-3 Machikaneyama Toyonaka Osaka560-8531 Japan Faculty of Science and Engineering Meijo University 1-501 Shiogamaguchi Tenpaku-ku Nagoya468-8502 Japan

ISBN: (纸本)9781509046331

In micromanipulation, lots of methods have been developed to manipulate objects in microscale. However, few of them can be applied in both the transportation and the rotation of the micro objects. In this paper, we present a novel method to realize the non-contact transportation and rotation of the micro objects based on the vibration-induced swirl flow. A piezo actuator is set between the glass needle and a metal rod. The sine wave with controlled frequency and amplitude is input into the piezo actuator to drive the glass needle to move circularly, which is caused by resonance of the actuator and the metal rod. We place the glass needle under water and keep a limited distance to the bottom. The circular vibration of the glass needle can generate a swirl flow and low pressure around it. The low pressure can trap and transport the micro objects vertically to the glass needle, and the swirl flow can rotate the objects continuously. Finally, we realize the trap and rotation of micro object with only one piezo actuator. Experiments of transportation and rotation of microbeads are carried out, and the results demonstrate it is a simple, low-cost, effective micromanipulation method. © 2017 IEEE.

关键词： Needles

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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Observer-based fault detection for affine nonlinear systems with disturbances and uncertainties 35

Observer-based fault detection for affine nonlinear systems ...

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第35届中国控制会议

作者： HAN Huayun YANG Ying LI Linlin Chen Yu State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University School of Automation and Electrical Engineering University of Science and Technology Beijing the Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen Beijing Institute of Astronautics System Engineering

ISBN: (纸本)9781509009107

This paper is concerned with the integrated design schemes of L observer-based fault detection（FD） systems for affine nonlinear processes with disturbances and uncertainties,*** this end,a so called L observer-based FD scheme is studied ***,the integrated design approaches for nonlinear systems with disturbances and uncertainties are addressed,*** the end,examples are given to illustrate the effectiveness of the proposed approaches.

关键词： Robust Fault Detection Observer Design Affine Nonlinear systems

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