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第35届中国控制会议

作者： Zhou Yingjiang Shen Jingjin Jiang Guoping Sun Changyin College of Automation Nanjing University of Posts and Telecommunications Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University School of Automation Southeast University

ISBN: (纸本)9781509009107

This paper studies the protocol of synchronization in complex dynamical networks via pinning control by using a new error variable *** control is used to stable the error system,which can force the complex dynamical networks to reach *** is found that if the disturbances satisfy some conditions,synchronization can be achieved by pinning the least number of *** are finally performed to illustrate the effectiveness of the theoretical results.

关键词： Synchronization complex dynamical networks pinning control PI control

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Weighted Group-Consensus of Multi-Agent systems with Bipartite Topologies 28

Weighted Group-Consensus of Multi-Agent Systems with Biparti...

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第28届中国控制与决策会议

作者： He Ying-gao Wang Xiang-yu Wuxi Institute of Arts & Technology School of Automation Southeast UniversityNanjing 210096China& Key Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of Education

ISBN: (纸本)9781467397155

This paper studies weighted group-consensus of multi-agent systems with bipartite topologies through adjusting the proportion of the current states and the delay states in the control algorithms.A sufficient condition for the convergence to a weighted group-consensus is proposed by adopting the generalized Nyquist stability criterion and the Gerschgorin disk theorem This condition is able to enlarge the upper bound on the maximum time-delay of weighted *** of the proposed result is demonstrated through numerical simulations.

关键词： Multi-agent systems group-consensus Nyquist criterion Gerschgorin disk theorem

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Finite-time output consensus of second-order multi-agent systems with mismatched disturbances via active anti-disturbance control

Finite-time output consensus of second-order multi-agent sys...

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Asian control Conference

作者： Guipu Li Xiangyu Wang Shihua Li Wei Xing Zheng Xisong Chen School of Automation Southeast University Nanjing PR China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education PR China School of Computing Engineering and Mathematics Western Sydney University Sydney NSW Australia

ISBN: (纸本)9781509015740;9781509015733

This paper studies the finite-time output consensus problem of second-order multi-agent systems with both mismatched disturbances and unknown state elements. This problem is solved by an active anti-disturbance control (AADC) method, which integrates the disturbance estimation/compensation and the baseline consensus protocols based on feedback control together. To estimate the matched/mismatched disturbances and the agents unknown state elements, a finite-time generalized state observer is constructed for each agent. Based on the distributed adding a power integrator feedback control method, and the estimates of the matched/mismatched disturbances and the systems unknown states, AADC consensus protocols are developed for both leaderless and leader-follower cases. The proposed protocols achieve finite-time consensus of the agents outputs in both cases. Simulation results demonstrate the effectiveness of the proposed consensus algorithms.

关键词： Multi-agent systems Output consensus Mismatched disturbances Distributed adding a power integrator method Finite-time generalized state observer

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Deep learning for robust outdoor vehicle visual tracking

Deep learning for robust outdoor vehicle visual tracking

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Ji-ng Xin Xing Du Jian Zhang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an P.R.China Faculty of Engineering and Information Technology University of Technology (UTS) Sydney Australia

ISBN: (纸本)9781509060689

Robust visual tracking for outdoor vehicle is still a challenging problem due to large appearance variations caused by illumination variation, occlusion and scale variation, etc. In this paper, a deep-learning-based approach for robust outdoor vehicle tracking is proposed. Firstly, a stacked denoising auto-encoder is pre-trained to learn the feature representation way of images. Then, a k-sparse constraint is added to the stacked denoising auto-encoder and the encoder of k-sparse stacked denoising auto-encoder (kSSDAE) is connected with a classification layer to construct a classification neural network. After fine-tuning, the classification neural network is applied to online tracking under particle filter framework. Extensive tracking experiments are conducted on a challenging single object online tracking evaluation platform benchmark to verify the effectiveness of our tracker. Experiments show that our tracker outperforms most state-of-the-art trackers.

关键词： Robustness Object tracking Machine learning Feature extraction Biological neural networks Visualization

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Sensor fault diagnosis based on on-line random forests 35

Sensor fault diagnosis based on on-line random forests

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35th Chinese control Conference, CCC 2016

作者： Yang, Li Zhang, Jia Deng, Fang Chen, Jie School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control of Complex System Beijing100081 China

ISBN: (纸本)9789881563910

In order to reduce the memory requirement, and obtain real-time status of equipment, the paper proposed to use the the on-line random forests (ORFs) algorithm to identify sensor fault. The sample set is derived from Tennessee Eastman (TE) process. The models are updated by a group of sensor data, which are collected in each interval. As models are real-time and dynamic, the equipment could be tested at any time. Moreover, the samples obtained at previous intervals are not need to store. The results of experiments show that the accuracies of ORFs and Random Forests (RFs) are similar in sensor fault diagnosis process. And in some fast changing process, ORFs distinguishes fault types with higher accuracy, better adaptable and faster than RFs. © 2016 TCCT.

关键词： On-line Random Forests Sensor fault Tennessee Eastman process

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Current control of IPMSM servo system in field-weakening region via DOB-based model predictive control

Current control of IPMSM servo system in field-weakening reg...

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Annual Conference of Industrial Electronics Society

作者： Chao Wu Shihua Li Qi Li Wei Xing Zheng School of Automation Southeast University Nanjing P. R. China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Computing Engineering and Mathematics Western Sydney University Sydney NSW Australia

Current control of IPMSM servo system is investigated in this paper. Under the field-weakening control framework, nonlinear couplings of the voltage equations are very strong. The current control performance may not be well until such nonlinear couplings are well dealed. In this case, a DOB-based model predictive control is proposed to improve the current control performance under field-weakening control framework. The proposed control method consists of a forecasted model based on disturbance observer, feedback correction for model mismatch rejection, and receding optimization for an optimized control input. Numerical simulations demonstrate that proposed method achieves nonlinear coupling attenuation ability and well promising field-weakening control performance.

关键词： Couplings Mathematical model Torque Voltage control Stators Current control

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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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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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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 adaptive passivity-based controller of a buck-boost converter with a constant power load

arXiv

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arXiv 2017年

作者： He, Wei Ortega, Romeo Machado, Juan E. Li, Shihua Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China Laboratoire des Signaux et Systemes Supelec Plateau du Moulon Gif-sur-Yvette91192 France

This paper addresses the problem of regulating the output voltage of a DC-DC buck-boost converter feeding a constant power load, which is a problem of current practical interest. Designing a stabilising controller is theoretically challenging because its average model is a bilinear second order system that, due to the presence of the constant power load, is non-minimum phase with respect to both states. Moreover, to design a high-performance controller, the knowledge of the extracted load power, which is difficult to measure in industrial applications, is required. In this paper, an adaptive interconnection and damping assignment passivity-based control-that incorporates the immersion and invariance parameter estimator for the load power-is proposed to solve the problem. Some detailed simulations are provided to validate the transient behaviour of the proposed controller and compare it with the performance of a classical PD scheme. Copyright © 2017, The Authors. All rights reserved.

关键词： DC-DC converters

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