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arXiv 2020年

作者： Trobia, José Gabrick, Enrique C. Seifert, Evandro G. Borges, Fernando S. Protachevicz, Paulo R. Szezech, José D. Iarosz, Kelly C. Santos, Moises S. Caldas, Iberê L. Tian, Kun Ren, Hai-Peng Grebogi, Celso Batista, Antonio M. Graduate Program in Science - Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Department of Mathematics and Statistics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Department of Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Faculty of Telêmaco Borba FATEB Telêmaco BorbaPR84266-010 Brazil Graduate Program in Chemical Engineering Federal Technological University of Paraná Ponta Grossa Paraná84016-210 Brazil Shaanxi Key Lab of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Xi’an Technological University Xi’an710021 China Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenAB24 3UE United Kingdom

Cancer is a term used to refer to a large set of diseases. The cancerous cells grow and divide and, as a result, they form tumours that grow in size. The immune system recognise the cancerous cells and attack them, though, it can be weakened by the cancer. One type of cancer treatment is chemotherapy, which uses drugs to kill cancer cells. Clinical, experimental, and theoretical research has been developed to understand the dynamics of cancerous cells with chemotherapy treatment, as well as the interaction between tumour growth and immune system. We study a mathematical model that describes the cancer growth, immune system response, and chemotherapeutic agents. The immune system is composed of resting cells that are converted to hunting cells to combat the cancer. In this work, we consider drug sensitive and resistant cancer cells. We show that the tumour growth can be controlled not only by means of different chemotherapy protocols, but also by the immune system that attacks both sensitive and resistant cancer cells. Furthermore, for all considered protocols, we demonstrate that the time delay from resting to hunting cells plays a crucial role in the combat against cancer cells. Copyright © 2020, The Authors. All rights reserved.

关键词： Chemotherapy

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Distance-based separability criterion of ROI in classification of farmland hyper-spectral images

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International Journal of Agricultural and Biological Engineering 2017年第5期10卷 177-185页

作者： Tang Jinglei Miao Ronghui Zhang Zhiyong Xin Jing Wang Dong College of Information Engineering Northwest A&F UniversityYangling 712100ShaanxiChina Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048China College of Information Science and Engineering Shanxi Agricultural UniversityTaigu 030801ShanxiChina

The hyper-spectral image contains spectral and spatial information,which increases the ability and precision of objects *** the classification value of hyper-spectral imaging technology within various applications,users often find it difficult to effectively apply in practice because of the effect of light,temperature and wind in outdoor *** research presented a new classification model for outdoor farmland objects based on near-infrared(NIR)hyper-spectral *** involves two steps including region of interest(ROI)acquisition and establishment of classifiers.A distance-based method for quantitative analysis was proposed to optimize the reference pixels in ROI acquisition *** maximum likelihood(ML)and support vector machine(SVM)were used for farmland objects *** performance of the proposed method showed that the total classification accuracy based on the reference pixels was over 97.5%,of which the SVM-M model could reach 99.5%.The research provided an effective method for outdoor farmland image classification.

关键词： distance-based separability criterion near-infrared hyper-spectral image ROI farmland image classification

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Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network

arXiv

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arXiv 2019年

作者： Santos, Moises S. Protachevicz, Paulo R. Iarosz, Kelly C. Caldas, Iberê L. Viana, Ricardo L. Borges, Fernando S. Ren, Hai-Peng Szezech, José D. Batista, Antonio M. Grebogi, Celso Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xi'an710048 China Xian Technological University Xi'an710021 China Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen AberdeenAB24 3UE United Kingdom

Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is composed of coupled adaptive exponential integrate-and-fire neurons that are connected by means of chemical synapses. In our neuronal network, the chimera states exhibit spatial structures both with spikes and bursts activities. Furthermore, those desynchronised domains not only have either spike or burst activity, but we show that the structures switch between spikes and bursts as the time evolves. Moreover, we verify the existence of multicluster chimera states. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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Comparative study of VSP binning methods for estimating fuel consumptions of LDVs on urban roads

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AIP Conference Proceedings 2019年第1期2066卷

作者： Qi Zhao Qi Chen Guohua Song Lei Yu 1Beijing Key Laboratory of Urban Intelligent Traffic Control Technology North China University of Technology Beijing 100144 China 2MOE Key Laboratory for Urban Transportation Complex System Theory and Technology Beijing Jiaotong University Beijing 100044 China 3College of Science and Technology Texas Southern University Houston Texas 77004 United States

The micro-scale fuel consumption model is a tool commonly used to evaluate the effect of traffic flow conditions on vehicle fuel consumptions, which is an essential step in developing traffic management strategies for saving fuels. In developing any micro-scale fuel consumption model, the Vehicle Specific Power (VSP) binning method has been widely adopted in recent years as a fundamental approach. Existing studies have shown that the high distribution frequency when VSP=0 contributes to high fuel consumptions, so a question quickly emerged about whether VSP=0 should be designed as an independent VSP bin in the VSP binning method. This paper strives to compare different VSP binning methods for Light-Duty Vehicles (LDVs) on urban roads in Beijing in terms of their effects on the estimation of fuel consumptions. After collecting and processing field vehicle activity data and fuel consumption data, three VSP binning methods are proposed for the study. Then, total fuel consumptions and fuel consumption factors are calculated by using the proposed VSP binning methods as well as the second-by-second and average travel speed data. Finally, the estimation accuracy of total fuel consumptions and fuel consumption factors based on the three different VSP binning methods are compared for LDVs on urban roads. The study proves that an independent VSP bin at VSP=0 is indeed necessary, which can improve the estimation accuracy on both total fuel consumptions and fuel consumption factors.

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

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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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