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第三十八届中国控制会议

作者： Jianqi Chen Dan Ma Yong Xu Jie Chen Department of Electronic Engineering City University of Hong Kong College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process Industries Northeastern University The School of Automation Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of Technology

In this paper we study delay robustness of PID controllers in stabilizing systems containing uncertain, variable *** consider second-order unstable systems and seek analytical characterization and exact computation of the PID delay margin,where by PID delay margin we mean the maximal range of delay values within which the system can be robustly stabilized by a PID controller. Our contribution is threefold. First, we show that the delay margin achieved by PID control coincides with that by PD controllers. Second, we show that other than helping stabilize the delay-free part of a plant, the proportional control contributes no action to increase the delay margin. Finally, we show that the PID delay margin can be computed efficiently by solving a unimodal problem, that is, a univariate optimization problem that admits a unique maximum and hence is a convex optimization problem in one variable. This unimodal problem is one of pseudo-concave optimization and hence can be solved using standard convex optimization or gradient-based methods. As such, from a computational perspective, the PID delay margin problem is completely resolved in this paper! The results not only insure that the PID delay margin problem be readily solvable, but also provide fundamental conceptual insights into the PID control of delay systems, and analytical justifications to long-held engineering intuitions and heuristics, thus lending useful guidelines in the tuning and analytical design of PID controllers.

关键词： Delay margin robust stabilization PID controller uncertain time delay nonlinear programming pseudo-concavity

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Robust Stabilization of T-S Fuzzy Stochastic Descriptor Systems via Integral Sliding Modes

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第9期48卷 2736-2749页

作者： Li, Jinghao Zhang, Qingling Yan, Xing-Gang Spurgeon, Sarah K. Institute of Systems Science State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Instrumentation Control and Embedded Systems Research Group School of Engineering and Digital Arts University of Kent Canterbury U.K. Department of Electronic and Electrical Engineering University College London London U.K.

This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi-Sugeno (T-S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T-S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.

关键词： Integral sliding mode control inverted pendulum nonparallel distributed compensation (Non-PDC) robust stabilization Takagi-Sugeno (T-S) fuzzy stochastic descriptor systems

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A novel fault classification method based on neural network in smart grid

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International Journal of Electrical engineering 2018年第1期25卷 1-7页

作者： Zhang, Tong Sun, Lanxiang Liu, Jianchang Yu, Haibin College of Information Science and Engineering Northeastern University Shenyang China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control System CAS Shenyang China University of Chinese Academy of Sciences Beijing China

This paper presents a back propagation (BP) neural network method to identify fault types and phases in the smart grid with renewable sources. A fault classification method based on the BP neural network is used to identify patterns of voltage and current measured with phasor measurement unit (PMU). The voltage and current values are decomposed, and then they are used as the input matrix of the BP neural network, which identifies the fault type and fault phasor. All the common short-circuit faults occurred are analyzed, BP neural network method is proposed for fault classification in a power active distribution network. Simulation results show feasibility and usefulness of the BP neural network method, which provides good classification performances.

关键词： Smart power grids

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Predictive control for Continuous Stirred Tank Reactors

Predictive Control for Continuous Stirred Tank Reactors

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2019 International Conference on Informatics, control and Robotics 2019信息学、控制和机器人学国际会议(ICICR2019)

作者： Ioana NASCU Ioan NASCU Wen-li DU Sai GU Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Department of Chemical and Process Engineering University of Surrey Department of Automation Technical University of Cluj-Napoca

The paper focuses on the implementation of a model based predictive control(MBPC) method, for Continuous Stirred Tank Reactors. First, the modelling problem of a single irreversible exothermic reaction, taking place in a perfectly mixed continuously stirred tank reactor(CSTR) is presented. The dynamic model consists of differential material and energy balance equations. The control strategy is investigated and evaluated by performing simulations and analyzing the results. The disturbance rejection capacity of the control system(regulatory control performances) have been tested and compared with those obtained using a classical Proportional Integral Derivative(PID) based controller. The results show that this control strategy has good performances and can be efficiently used to control the CSTR.

关键词： Predictive control PID control Chemical reactor process model

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Pulp concentration control based on dynamic matrix control

Pulp concentration control based on dynamic matrix control

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Chinese Intelligent Systems Conference, CISC 2017

作者： Hao, Wen Dong, Jie Peng, Kaixiang Jia, Mengqi Wang, Qiang Key Laboratory for Advanced Control of Iron and Steel Process of Ministry of Education Beijing100083 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9789811064982

In the papermaking industry, the stability of the pulp concentration determines the quality of the paper. However, the change of the pulp concentration is in a state of fluctuation for a long time and the pulp concentration control system has the characteristics of large lag, non-linearity and time-varying. It is difficult to achieve the desired control effect by using the traditional PID controller in the concentration control process. Therefore, use of dynamic matrix control algorithm to design the controller can solve the problem of disturbance and modeling complexity. In this paper, dynamic matrix control algorithm and PID control simulation results show that the dynamic matrix control algorithm has better control quality. The output satisfies the constraint limit with higher probability, and the output constraints and performance index can be met. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Three term control systems

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Distributed Optimization of Nonlinear Multi-Agent Systems: A Small-Gain Approach

Distributed Optimization of Nonlinear Multi-Agent Systems: A...

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IEEE Annual Conference on Decision and control

作者： Tengfei Liu Zhengyan Qin Yiguang Hong Zhong-Ping Jiang State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Laboratory of Systems and Control Chinese Academy of Sciences Beijing China Tandon School of Engineering New York University Brooklyn NY USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

This paper studies the distributed optimal output agreement problem for multi-agent systems described by uncertain nonlinear models. By using partial information of an objective function, the design aims to steer the outputs of the agents to an agreement on the optimal solution to the objective function. To solve this problem, this paper introduces distributed coordinators to calculate the ideal outputs, and designs reference-tracking controllers for the agents to follow the ideal outputs. To deal with the nonlinear uncertain dynamics, the closed-loop multi-agent system is considered as a dynamical network, and Sontag's input-to-state stability (ISS) properties are employed to characterize the interconnections. It is shown that output agreement in multi-agent nonlinear systems is achievable by means of distributed optimal coordinators via a small-gain approach. Numerical simulations are employed to show the effectiveness of the design.

关键词： Multi-agent systems Linear programming Optimization Robustness Nonlinear dynamical systems Stability analysis Convergence

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Delay Robustness of Second-Order Uncertain Nonlinear Delay Systems under PID control*

Delay Robustness of Second-Order Uncertain Nonlinear Delay S...

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control Technology and Applications (CCTA),

作者： Zexi Lu Dan Ma Juan Wang College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang P. R. China College of Information and Control Engineering Shenyang Jianzhu University Shenyang P. R. China

This paper studies the delay robustness problem for tracking control of second-order systems subject to unknown input delay and uncertain nonlinearity under PID control. The basic issue is to find the largest allowable input delay under PID control can achieve robust tracking in spite of the uncertain nonlinearity. First, the uncertain nonlinear delay system under PID control can be transferred into a delay system with time-varying uncertainty. Second, we develop the largest allowable time delay under fixed PID controller parameters by solving the generalized eigenvalue problem (GEVP). Third, a genetic algorithm (GA) is proposed to achieve the largest allowable delay and the corresponding PID parameters, which consists with the solutions under GEVP. The first-order uncertain nonlinear delay systems under PI control is investigated as well. Finally, two examples are given to show the effectiveness of the proposed method.

关键词： Delays Robustness PI control PD control Delay effects Delay systems Symmetric matrices

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Notice of Retraction: Adaptive Decentralized Tracking control for Nonlinear Large-Scale Systems

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International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 2021年第5期29卷 789-789页

作者： Karthik Chandran Weidong Zhang Rajalakshmi Murugesan S. Prasanna A. Baseera Sanjeevi Pandiyan Department of Automation Shanghai Jiao Tong University Shanghai China Department of Mechatronics Jyothi Engineering College Thrissur India Department of EEE Ultra College of Engineering and Technology India School of Information Technology and Engineering VIT Vellore India School of Computing Science and Engineering VIT Bhopal University India Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi 214122 China

This article has been retracted at the request of the first and corresponding author, Dr. Karthik Chandran. The author has alerted the Editor-in-Chief of IJUFKS the reasons for the retraction: The proposed system was modelled with the incorrect data set. The system response has become incorrect because of this incorrect data set. Two percent of the information (mathematical assumptions) was taken from one paper without proper citation of the source.

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Numerical detection of Gaussian entanglement and its application to the identification of bound entangled Gaussian states

arXiv

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arXiv 2020年

作者： Ma, Shan Xue, Shibei Guo, Yu Shu, Chuan-Cun School of Automation Central South University Changsha410083 China Peng Cheng Laboratory Shenzhen518000 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Hunan Provincial Key Laboratory of Flexible Electronic Materials Genome Engineering School of Physics and Electronic Science Changsha University of Science and Technology Changsha410114 China Hunan Key Laboratory of Super-Microstructure and Ultrafast Process School of Physics and Electronics Central South University Changsha410083 China

We present a numerical method for solving the separability problem of Gaussian quantum states in continuous-variable quantum systems. We show that the separability problem can be cast as an equivalent problem of determining the feasibility of a set of linear matrix inequalities. Thus, it can be efficiently solved using existent numerical solvers. We apply this method to the identification of bound entangled Gaussian states. We show that the proposed method can be used to identify bound entangled Gaussian states that could be simple enough to be producible in quantum optics. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum optics

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Challenges and solutions in automotive powertrain systems

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Journal of control and Decision 2018年第1期5卷 61-93页

作者： Tielong Shen Mingxin Kang Jinwu Gao Jiangyan Zhang Yuhu Wu Department of Engineering and Applied Sciences Sophia UniversityTokyoJapan State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyangP.R.China State Key Laboratory of Automobile Simulation and Control Jilin UniversityChangchunP.R.China College of Mechanical and Electronic Engineering Dalian Minzu UniversityDalianP.R.China School of Control Science and Engineering Dalian University of TechnologyDalianP.R.China

Automotive powertrain mainly consisting of combustion engine,motor and battery(*** for hybrid powertrain)is a very complicated integration system,and the research on the automotive powertrain control techniques remains hot-spot in past *** paper proposes some challenging issues and control solutions of automotive powertrain system from the perspective of the dynamic system *** typical characteristics of automotive powertrain system are analysed for control development,and the several control applications using model-based and model-free control design are demonstrated with sufficient experimental *** addition,some open issues for future powertrain control development are summarised.

关键词： Model-based control model-free control combustion engine automotive powertrain control technology

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