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Chinese control Conference (CCC)

作者： Yuanlong Li Zongli Lin Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai P. R. China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA

In this paper we revisit the problem of global asymptotic stabilization of the double integrator system subject to output saturation. We first observe that the double integrator system cannot be asymptotically stabilized by linear static output feedback. We then establish that there exist linear dynamic output feedback laws that globally asymptotically stabilize the double integrator system subject to output saturation. The determination of the linear output feedback laws is presented in the form of an algorithm. Simulation results illustrate that the linear dynamic output feedback laws have the ability to achieve global asymptotic stabilization of the double integrator system subject to output saturation.

关键词： Output feedback Linear systems Heuristic algorithms Closed loop systems Actuators Trajectory

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Preventive Soot Blowing Strategy Based on State of Health Prediction for Coal-fired Power Plant Boiler

Preventive Soot Blowing Strategy Based on State of Health Pr...

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Chinese control Conference (CCC)

作者： Yuanhao Shi Jie Wen Xiaoqiong Pang Jianfang Jia Fangshu Cui Jianchao Zeng Jingcheng Wang North University of China School of Electrical and Control Engineering Taiyuan China North University of China School of Computer Science and Technology Taiyuan China Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

This paper seeks the optimization of soot-blowing operations for heat transfer surfaces in coal- fired power plant boiler. A preventive soot blowing strategy based on state of health prediction for heat transfer surface was proposed. The average state of health of heat transfer surface was forecasted as the threshold to draft preventive soot blowing strategy. According to the theory of renewal process, an optimization model with the system prediction interval and the threshold of preventive soot blowing operation as the optimization variables and minimize average energy losses as the target function was established. By using Particle Swarm Optimization (PSO), the optimal preventive cycle and soot-blowing threshold were obtained, and the long-run average cost rate was the lowest. The model is validated with experiment data of a 300MW coal-fired power plant boiler and the parameters of prediction model are obtained. The results can verify the feasibility of proposed strategy. It can be used as the guide for the optimization of soot blowing in coal-fired power plant to improve the energy conservation level.

关键词： Thermal engineering Radio frequency Coal Combustion Heat engines Heat transfer

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Toward stronger robustness of network controllability: A snapback network model

arXiv

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arXiv 2018年

作者： Lou, Yang Wang, Lin Chen, Guanrong Department of Electronic Engineering City University of Hong Kong Hong Kong SAR Hong Kong Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

A new complex network model, called q-snapback network, is introduced. Basic topological characteristics of the network, such as degree distribution, average path length, clustering coefficient and Pearson correlation coefficient, are evaluated. The typical 4-motifs of the network are simulated. The robustness of both state and structural controllabilities of the network against targeted and random node- and edge-removal attacks, with comparisons to the multiplex congruence network and the generic scalefree network, are presented. It is shown that the q-snapback network has the strongest robustness of controllabilities due to its advantageous inherent structure with many chain- and loop-motifs. Copyright © 2018, The Authors. All rights reserved.

关键词： controllability

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Increase in accuracy forecast for electrical energy consumption of the WEM subjects using fuzzy neural networks

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IOP Conference Series: Materials Science and engineering 2020年第1期791卷

作者： Ya P Fedorov V L Burkovsky A L Rutskov Corporate finance department and corporate management of the Financial University under the Government of the Russian Federation Leningradsky prospect 49 Moscow 125993 Russia Department of electric drive automation and control in an engineering system Voronezh State Technical University Moscow prospect 179 Voronezh 394066 Russia Forecasting department of electricity balance power and loss analysis branch office OJSC «IDGC Centre» - «Voronezhenergo» Arzamaskaya 2 Voronezh 394033 Russia

This paper covers in depth functioning essence of the balancing electricity market in the Russian Federation in accordance with the current economic stimuli. Significant role of the prediction process for energy resources consumption has been noted, which has a direct influence on a pricing policy within the marked trade area. Analysis of different factors, that impact execution accuracy of the one day in advance model, was conducted. Problem of the weakly defined and unknown parameters, that influence the performance of the balancing electricity market, is suggested to resolve by means of fuzzy neural controller. The paper presents its structure and settings, and possibility to scale it to use not only as an analyzer but as an executive element in the subsystems of electric power systems. High accuracy performance of the fuzzy neural controller was shown - around (0,5-3) %, that is much higher than methods already in use (for instance, based on a coefficient of decline/growth of power consumption).

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Retrieval-based localization based on domain-invariant feature learning under changing environments

arXiv

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arXiv 2019年

作者： Hu, Hanjiang Wang, Hesheng Liu, Zhe Yang, Chenguang Chen, Weidong Xie, Le Autonomous Robot Lab Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China T Stone Robotics Institute Chinese University of Hong Kong Hong Kong Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom School of Material Science and Engineering Shanghai Jiao Tong University Shanghai200240 China

Visual localization is a crucial problem in mobile robotics and autonomous driving. One solution is to retrieve images with known pose from a database for the localization of query images. However, in environments with drastically varying conditions (e.g. illumination changes, seasons, occlusion, dynamic objects), retrieval-based localization is severely hampered and becomes a challenging problem. In this paper, a novel domain-invariant feature learning method (DIFL) is proposed based on ComboGAN, a multi-domain image translation network architecture. By introducing a feature consistency loss (FCL) between the encoded features of the original image and translated image in another domain, we are able to train the encoders to generate domain-invariant features in a self-supervised manner. To retrieve a target image from the database, the query image is first encoded using the encoder belonging to the query domain to obtain a domain-invariant feature vector. We then preform retrieval by selecting the database image with the most similar domain-invariant feature vector. We validate the proposed approach on the CMU-Seasons dataset, where we outperform state-of-the-art learning-based descriptors in retrieval-based localization for high and medium precision scenarios. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Preventive Soot Blowing Strategy based on State of Health Prediction for Coal-fired Power Plant Boiler

Preventive Soot Blowing Strategy based on State of Health Pr...

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第37届中国控制会议

作者： Yuanhao Shi Jie Wen Xiaoqiong Pang Jianfang Jia Fangshu Cui Jianchao Zeng Jingcheng Wang North University of China School of Electrical and Control Engineering North University of China School of Computer Science and Technology North University of ChinaSchool of Computer Science and Technology Shanghai Jiao Tong University Department of Automationand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

This paper seeks the optimization of soot-blowing operations for heat transfer surfaces in coal-fired power plant boiler.A preventive soot blowing strategy based on state of health prediction for heat transfer surface was *** average state of health of heat transfer surface was forecasted as the threshold to draft preventive soot blowing *** to the theory of renewal process,an optimization model with the system prediction interval and the threshold of preventive soot blowing operation as the optimization variables and minimize average energy losses as the target function was *** using Particle Swarm Optimization（PSO）,the optimal preventive cycle and soot-blowing threshold were obtained,and the long-run average cost rate was the *** model is validated with experiment data of a 300 MW coal-fired power plant boiler and the parameters of prediction model are *** results can verify the feasibility of proposed *** can be used as the guide for the optimization of soot blowing in coal-fired power plant to improve the energy conservation level.

关键词： Coal-fired Boiler Heat Transfer Surface Soot-blowing State of Health（SOH） Prediction

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Task-space cooperative tracking control of multi-robot systems with unknown parameters and time delays

Task-space cooperative tracking control of multi-robot syste...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Xinwu Liang Hesheng Wang Yun-Hui Liu Weidong Chen Le Xie The School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing Shanghai China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China National Digital Manufacturing Technology Center Shanghai Jiao Tong University Shanghai China

In this paper, the task-space cooperative tracking control problem of multi-robot systems on strongly connected digraphs is studied. To solve such synchronization problem, a novel adaptive control approach is proposed by introducing task-space synchronization errors between neighboring robotic systems into the task-space reference velocity/acceleration. To cope with unknown kinematic and dynamic parameters, adaptive laws are developed without explicitly incorporating synchronization terms. Lyapunov stability theory is used to rigorously prove asymptotical convergence of the task-space synchronization and tracking errors by fully considering the time delays. Finally, simulation results are given to illustrate the performance of the proposed task-space cooperative tracking control approach.

关键词： Task analysis Robot kinematics Kinematics Multi-robot systems Synchronization Aerospace electronics

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Stability and Neimark-Sacker bifurcation analysis for single gene discrete system with delay

Stability and Neimark-Sacker bifurcation analysis for single...

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Chinese control Conference

作者： Feng Liu Qicheng Mei Fenglan Sun Xinmei Wang Hua O. Wang Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Automation China University of Geosciences Wuhan China Research Center of System Theory and Application Chongqing University of Posts and Telecommunications Chongqing China Department of Mechanical Engineering Boston University Boston MA USA

The network structure and functional properties of gene regulatory system and their relationships arc an important research field in systems biology. In this paper, a new improved model is proposed based on the study of gene expression process. The model takes into account the effect of protein concentration on the gene expression, so as to obtain a new bifurcation point and improve the performance of the system. The validity of the model is verified by theoretical analysis and data simulation.

关键词： Mathematical model Proteins Stability analysis Bifurcation Biological system modeling Delays RNA

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Stability and Stabilization Analysis of Fractional-Order Linear systems Subject to Actuator Saturation and Disturbance

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IFAC-PapersOnLine 2017年第1期50卷 9718-9723页

作者： LI C. CHEN K. LU J. TANG R. School of Mechanical and Electrical Engineering Hainan University Haikou 570228 China Department of Automation Shanghai JiaoTong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

This paper focuses on the fractional order linear systems subject to actuator saturation and external disturbance, and proposes method to estimate the domain of attraction. The quadratic Lyapunov functions are adopted to obtain the invariance of considered systems. The convex combination form of quadratic Lyapunov function is utilized to obtain a large domain of attraction. A continuous feedback law is derived to achieve disturbance rejection for closed-loop systems. Numerical example is provided to illustrate the effectiveness of the developed method. © 2017

关键词： Disturbance Domain of Attraction Fractioanl-Order systems LMI Saturation Stability

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Optimal identification of non-Markovian environments for spin chains

arXiv

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arXiv 2018年

作者： Xue, Shibei Zhang, Jun Petersen, Ian R. Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Joint Institute of UM-SJTU Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Research School of Engineering Australian National University CanberraACT2600 Australia

Correlations of an environment are crucial for the dynamics of non-Markovian quantum systems, which may not be known in advance. In this paper, we propose a gradient algorithm for identifying the correlations in terms of time varying damping rate functions in a time-convolution-less master equation for spin chains. By measuring time trace observables of the system, the identification procedure can be formulated as an optimization problem. The gradient algorithm is designed based on a calculation of the derivative of an objective function with respect to the damping rate functions, whose effectiveness is shown in a comparison to a differential approach for a two-qubit spin chain. Copyright © 2018, The Authors. All rights reserved.

关键词： Spin dynamics

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