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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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Process Monitoring of Multimode processes Using Kernel Independent Component Analysis

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IFAC Proceedings Volumes 2012年第15期45卷 697-701页

作者： Yingwei Zhang Jiayu An Chi Ma State Key Laboratory of Synthetical Automation of Process Industry Northeastern University Shenyang Liaoning 110819 PR China Key Laboratory of Advanced Control and Optimization for Chemical Processes Shanghai 200237 PR China

In the paper, a new process monitoring approach is proposed for handling the multimode problem in the industrial processes. The original space can be separated into two different parts, which are the common part and the specific part. There are both similarity and dissimilarity in the underlying correlations of different modes, which play different roles in the industrial processes. Because the industrial processes have the non-Gaussian and nonlinear characteristics, modified kernel independent component analysis is used to monitor the multimode processes in this paper. The global multimode basis vector and the multimode sub-basis vector are obtained based on the modified KICA. Then, the common part and specific part in one mode are respectively analyzed. The proposed method is applied to monitor the continuous annealing process. The proposed approach effectively captures the non-Gaussian and nonlinear relationship in different modes in the industrial processes.

关键词： Multimode process monitoring Common and specific correlations Kernel independent component analysis

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Estimation of Distribution Algorithm sampling under Gaussian and Cauchy distribution in continuous domain

Estimation of Distribution Algorithm sampling under Gaussian...

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International Conference on control and Automation (ICCA)

作者： Na Luo Feng Qian Automatic Institute Key Laboratory of Advanced Control and Optimization of Chemical Processes Ministry of Education State-Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai China

Estimation of Distribution Algorithm is a new population based evolutionary optimization method and it generates new population from probability distribution model. Like most evolutionary algorithms, it is easy to trap into local optimums. In order to avoid this shortcoming, Gaussian and Cauchy probability density function are mixed as probability distribution model. For continuous problems, a new estimation of distribution algorithm sampling under the mixed model is presented. New individuals are generated not only from Gaussian distribution but sometimes from Cauchy distribution in order to keep diversity. The selection strategy of Gaussian and Cauchy distribution are also discussed. The new algorithm is tested on five benchmark functions and results are compared with basic and estimation of distribution algorithm with Cauchy mutation.

关键词： Sampling methods Genetic mutations Electronic design automation and methodology Evolutionary computation Laboratories Probability distribution Gaussian distribution Automatic control chemical processes control engineering education

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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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Multi-time Scale Hierarchical Predictive control for Energy Management of Microgrid System with Smart Users

Multi-time Scale Hierarchical Predictive Control for Energy ...

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第26届中国控制与决策会议

作者： Jun Xu Yuanyuan Zou Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China Univ.of Science and Technology Key Laboratory of System Control and Information Processing Ministry of Education

In this paper, a multi-time scale hierarchal model predictive control strategy is proposed to optimize energy management problem of a microgrid with multiple smart users. According to the power flow among different energy modules, a hierarchical system model and a multi-time scale hierarchal energy optimization management problem are established. The centralized controller in the upper layer is to optimize the charge/discharge time and energy of storage devices, controllable supply power adjustment and dispatch of the aggregators. The optimization problem in the lower layer is to meet users' demands in real time. Meanwhile, in order to improve the disturbances caused by the randomness of renewable energy and variant loads, a multi-time scale optimization scheme is applied. At the slow scale, the upper optimization problem is solved, and the optimal energy scheduling in the long-term can be achieved. At the fast scale, the energy balance between supply and demand of smart users can be realized in the short-term. Finally, simulation results illustrate the effectiveness of proposed method.

关键词： Smart user,Microgrid,Energy management,Multi-time scale time-hierarchal,Model predictive control

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Delay-dependent synchronization criteria for delayed chaotic systems with parameter mismatches

Delay-dependent synchronization criteria for delayed chaotic...

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作者： He, Wangli Qian, Feng Han, Qing-Long Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China Centre for Intelligent and Networked Systems And School of Information and Communication Technology Central Queensland University Rockhampton 4702 Australia

ISBN: (纸本)9789881725592

This paper investigates synchronization between two delayed chaotic systems with parameter mismatches. Based on Lyapunov functional approach and generalized Halanay inequality, some delay-dependent criteria are derived to guarantee the synchronization error converges to a bounded ball, whose radius, referred to as the error level, is also estimated. Moreover, an optimization algorithm is established for error level estimate, and the feedback matrix design is also addressed. Finally, a chaotic neural network is used to illustrate the effectiveness of the proposed method. © 2011 Chinese Assoc of Automati.

关键词： Synchronization

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Simulation and optimization of acetylene converter with decreasing catalyst activity

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Huagong Xuebao/CIESC Journal 2012年第1期63卷 185-192页

作者： Tian, Liang Jiang, Da Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China Olefins Department SINOPEC Shanghai Petrochemical Company Limited Shanghai 200540 China

Since the activity and selectivity of acetylene hydrogenation catalyst change with time, the operating parameters need to be changed to maximize the profit. Therefore, we collected the industrial process data and estimated the parameters of kinetic model and deactivation model by genetic algorithm. We compared the selectivity and activity performance of two commonly used catalysts. For two reactors in series filled with different catalysts, we proposed the methods of combinatorial optimization and ratio assignment to optimal ethylene production rate. When these optimization strategies were implemented in the actual plant, ethylene production rate and the total selectivity increased significantly. © All Rights Reserved.

关键词： Combinatorial optimization

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Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

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Chinese Journal of chemical Engineering 2015年第12期23卷 1945-1950页

作者：李晨黄彪钱锋 Key Laboratory of Advanced Control and Optimization Ministry of EducationEast China University of Science and Technology Department of Chemical and Materials Engineering University of Alberta

control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities(e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

关键词： control performance monitoring Kernel density estimation Hellinger distance Nonlinear system

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Automatic ocular artifact suppression from human operator's EEG based on a combination of independent component analysis and fuzzy c-means clustering techniques

Automatic ocular artifact suppression from human operator's ...

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作者： Wang, Raofen Zhang, Jianhua Wang, Xingyu Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai 200237 China

ISBN: (纸本)9789881725592

Independent component analysis (ICA) and fuzzy c-means (FCM) clustering were adopted for automatic ocular artifact suppression from operator's electroencephalogram. Firstly, ICA was applied to the 20s data containing nine channels of EEG data and one of electrooculagram (EOG) data. Secondly, each 20s independent component (IC) was partitioned into ten 2 s epochs. And five features of each epoch were calculated, which are wavelet entropy, power in the band between 0 and 5 Hz, kurtosis, mutual information and correlation. Thirdly, the epochs were classified as either EEG or ocular artifact based on the result of FCM clustering. And then components which were recognized as ocular artifact were rejected. Clean EEG was obtained. The result shows that the method based on ICA and FCM can be applied to online automatic ocular artifact suppression from EEG. © 2011 Chinese Assoc of Automati.

关键词： Independent component analysis

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