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World Congress on Intelligent control and Automation (WCICA)

作者： Xiazhu You Wenli Du Liang Zhao Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

The steam system is an important part of chemical utility system, but there are widespread phenomenon about lack of testing information, energy consumption configuration depend on given experience and wasting energy. So this paper puts forward a method about the steam pipe network system's status identification of different energy consumption based on the steam pipe network's characteristics of complex structure, much steam equipment, lack of testing information and difficult to build accurate mathematical model. The method based on affinity propagation clustering that can solve big set of data's clustering problem quickly and effective. As it is hard to find preference parameters and damping factor, this paper uses PSO to find the most optimal parameters in order to achieve the best clustering effect. This method is applied test both in classic data set and the steam pipe network of ethylene plant's status identification, the results show the effectiveness of this method.

关键词： Energy consumption Indexes optimization Clustering algorithms Temperature measurement Pattern recognition Frequency modulation

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Data-driven Model Free Adaptive control for a Class of Interconnected Systems

Data-driven Model Free Adaptive Control for a Class of Inter...

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Asian control Conference

作者： Yuanming Zhu Feng Qian Zhongsheng Hou Shangtai Jin Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Advanced Control System Laboratory Beijing Jiaotong University

ISBN: (纸本)9781479978632

This paper recalls a novel data-driven model-free adaptive control (MFAC) method for a class of interconnected discrete-time nonlinear systems, whose model is unavailable and interactions between each subsystem are measurable. Then, under some mild conditions, stability of the closed-loop system is analyzed theoretically. Compared with original MFAC, the proposed MFAC for interconnected systems belongs to decentralized control method, and makes full use of the interacted data to achieve better performance. The effectiveness and superiority are verified by simulation result.

关键词： Data-driven control Model Free Adaptive control Interconnected System

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A new brain-computer interface paradigm based on P300 and SSVEP

A new brain-computer interface paradigm based on P300 and SS...

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Chinese control Conference (CCC)

作者： Minjue Wang Jing Jin Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 China

Brain-Computer Interface (BCI) is a novel communication system without depending on conventional brain output paths (such as peripheral nerve and muscle tissue) of the brain. The evaluation of effective EEG patterns is one of the crucial issues in the current research of BCI. Most of the traditional visual evoked paradigms only evoke one kind of EEG pattern for the subsequent feature classification. This study presents a new paradigm based on P300 and Steady-State Visual Evoked Potential (SSVEP) that involves event-related stimulation and frequency flashing stimulation. P300 and SSVEP patterns are evoked simultaneously to enhance the discriminability of features. Offline comparison is implemented among the proposed paradigm and the traditional P300 and SSVEP paradigms. The results show that the new paradigm evokes more significant P300 features while weaken SSVEP features a little without destroying the online feasibility of the BCI system. Therefore, the proposed paradigm can satisfy requirements from different subjects to enlarge the user of group.

关键词： Electroencephalography Brain-computer interfaces Educational institutions Visualization Electronic mail Steady-state Correlation

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Quantized H∞ control for stochastic nonlinear networked systems

Quantized H∞ control for stochastic nonlinear networked sys...

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Chinese control and Decision Conference, CCDC

作者： Huaicheng Yan Hongbo Shi Hao Zhang Haitao Zhao Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education Shanghai 200237 China Tongji University Shanghai Shanghai CN

In this paper, we are concerned with the quantized H ∞ control problem for a class of stochastic systems with random communication delays. The system under consideration involves signals quantization, Itô stochastic disturbance as well as random communication delays. The measured output and the control input quantization are considered simultaneously. We aim at designing an observer-based controller such that the dynamics of the filtering error is guaranteed to be exponentially stable in the mean square, and a prescribed H ∞ disturbance attenuation level is also achieved. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

关键词： Educational institutions Delays Quantization (signal) Electronic mail Stochastic systems Laboratories optimization

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Quantized and networked predictive control for input-saturated systems

Quantized and networked predictive control for input-saturat...

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Chinese control Conference (CCC)

作者： Yuanyuan Zou Bei Chen Tinggang Jia Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

This paper investigates the problem of stabilizing predictive control for constrained systems with quantization and communication delays. Based on the quantization matrix, the input-saturated control systems with logarithmic quantizers are described as constrained control systems with structured norm-bounded uncertainties. A quantized and networked predictive control algorithm is presented by using a multirate delay compensation strategy. It is shown that the proposed predictive controller not only efficiently reduces the negative effects of the quantization and communication delays but also guarantees the closed-loop stability and constraints satisfaction. The simulation example shows the effectiveness of the derived method.

关键词： Delay Predictive control control systems Quantization Stability analysis Uncertainty Prediction algorithms

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Early Warning Technology for Cracking Severity Basedon Improved Cultural Differential Algorithm

Early Warning Technology for Cracking Severity Basedon Impro...

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The 8th World Congress on Intelligent control and Automation(第八届智能控制与自动化世界大会 WCICA 2010)

作者： Yunxia Pu Mandan Liu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

Effective monitoring and early warning for cracking severity are directly related to the ethylene production stability and the overall economic benefits. Elman neural network is used to establish the early warning model of cracking severity, and an improved Cultural Differential Evolution algorithm(ICDE) is proposed to training the model. This hybrid algorithm integrates Cultural algorithm(CA) and Differential Evolution algorithm(DE) together, and increases some measure indicators of evolution direction, to make the algorithm more adaptive. Simulation results show that this method gains accurate warning signals to the cracking working conditions timely and effectively, obtained satisfactory results.

关键词： Cultural differences Artificial neural networks Furnaces Training Next generation networking Predictive models Production

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Stable Distributed Model Predictive control strategy based on agent coordination

Stable Distributed Model Predictive Control strategy based o...

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Chinese control Conference (CCC)

作者： Mengling Wang Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai Shanghai CN

Many systems composed by several interacting subsystems are usually controlled by a distributed control framework. Distributed Model Predictive control (DMPC) strategy, in which each subsystem is controlled by a local MPC controller, has advantages of accommodating constraints, less computational cost and high flexibility. In order to improve the global performance and guarantee the system stability, a stabilized DMPC strategy is proposed in this paper, in which subsystems interact through inputs. At first, local initial feasible solutions are achieved based on a Minkowski functional to guarantee the local closed-loop system stabilization. And then the global optimal solutions are obtained through coordination strategy for the sake of reducing iteration time and accelerating the convergence speed efficiently. Finally, the accuracy and efficiency of the proposed scheme is put to test through simulation.

关键词： Cost function Equations Mathematical model Predictive control Stability analysis Trajectory

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MPA EEG Model-based Vigilance Level Estimation by Artificial Neural Network

MPA EEG Model-based Vigilance Level Estimation by Artificial...

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2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

作者： Bei Wang Jiesen Wang Xingyu Wang Masatoshi Nakamura Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationSc Research Institute of Systems Control Institute for Advanced Research and Education Saga University

In this paper, the vigilance levels during day time short nap sleep were estimated on the basis of Markov Process Amplitude (MPA) EEG model. The ultimate purpose was to adopt the MPA model to discriminate three levels of vigilance through a simple neural network. A set of parameters were firstly calculated based on MPA EEG model. Secondly, correlation analysis was adopted to extract effective parameters to ensure a small amount of inputs of the artificial neural network. The outputs of artificial neural network were the classified three levels: wakeful, drowsy and sleep. The obtained estimation result showed that the accuracy of wakeful was about 90.0％, drowsy 80.0％, and sleep 93.3％.

关键词： MPA EEG model correlation analysis artificial neural network power spectrum

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Quantized Consensus of Linear Multi-Agent Systems Under An Event-triggered Strategy ⁎

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IFAC-PapersOnLine 2020年第2期53卷 1813-1818页

作者： Tinghui Luo Wangli He Wenying Xu The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China School of Mathematics Southeast University Nanjing 21189 China

This paper addresses a quantized consensus problem of general linear multi-agent systems in a symmetric network under an event-triggered scheme. Firstly, a distributed event-triggered strategy is developed with a dynamic threshold to reduce the unnecessary control update. Then, based on absolute quantized state measurements, a distributed controller is proposed and then a consensus criterion is derived, which ensures bounded consensus of linear multi-agent systems. The Zeno behavior is also successfully excluded. Finally, a numerical simulation is presented to validate theoretical results.

关键词： Multi-agent systems quantized consensus event-triggered strategy

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Optimal control Nodes Selection for Consensus in Multi-agent Systems

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IFAC Proceedings Volumes 2014年第3期47卷 11697-11702页

作者： Wen Yang Xiaofan Wang Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 Department of Automation Shanghai Jiaotong University Shanghai 200240

In a resource limited multi-agent system, it is of practical importance to select a fraction of nodes (agents) to provide control inputs such that consensus can be achieved with optimized performance in terms of network cost and/or convergence speed. In this paper, we investigate the problem of how to select control nodes so as to minimize the network cost, where the control nodes are selected at the beginning and will be fixed all the time. This problem can be transformed to a combinatorial optimization problem, and further relaxed to a convex optimization problem with reweighted l 1 norm. We propose a suboptimal algorithm to solve the convex optimization problem. Finally, we offer several numerical examples to illustrate the efficiency of the proposed strategies, and investigate the relationship how the degrees of control nodes will influence network cost and convergence speed.

关键词： Node selection Convex optimization Multi-agent systems

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