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International Conference on Information and Automation (ICIA)

作者： Kang Zhang Xingsheng Gu Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai

The Group Search Optimizer(GSO) is a novel optimization algorithm, which is inspired by searching behavior of animals. In this paper, we proposed an improved GSO algorithm named Fast Global Group Search Optimizer(FGGSO) to increase searching speed and balance the exploitation and exploration of the algorithm, which is based on our previous works. At first time, considering the complexity and time-consuming design of the producer's angle searching strategy, a novel local search mechanism, named campaign strategy, is developed, which is inspired by competition and cooperation between candidates in an electoral process. After that, a reconstruction operation is applied in searching process to guarantee the avoidance of the local minimum. The algorithm is evaluated on a set of 11 numerical optimization problems and compared favorably with other version of GSOs. Experimental results indicate the remarkable improvement on the performance of these problems.

关键词： optimization Standards Animals Acceleration Biological system modeling Convergence Search problems

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Dynamic optimization of chemical engineering problems using affinity propagation based estimation of distribution algorithm

Dynamic optimization of chemical engineering problems using ...

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World Congress on Intelligent control and Automation (WCICA)

作者： Na Luo Wei Feng Xiaoqiang Wang Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

Dynamic optimization has attracted much attention for its wide applications in engineering problems. However, it is still a challenge for high nonlinear, multi-dimensional and multimodal problems. Estimation of Distribution Algorithm was proposed in which probabilistic models extracted relevant features of the complex search space and then generated new individuals during optimization. In order to decrease the dependences among control variables in dynamic optimization, affinity propagation was applied to cluster the individuals in evolutionary iterations. In each cluster, the probabilistic density function of Gaussian mixture model refined the promising spaces with high quality solutions and avoided the random combination of different control variables. To evaluate the performance of the new approach, three dynamic optimization problems of chemical process are used as cases comparing with three state-of-the-art global optimization methods. The results showed that the new approach could achieve the best solution in most cases with less computational effort and higher efficiency.

关键词： Statistics Probabilistic logic optimization Sociology Algorithm design and analysis Robustness Genetic algorithms

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Distributed estimation over analog fading channels using constant-gain estimators 19

Distributed estimation over analog fading channels using con...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Xiao, Nan Xie, Lihua Niu, Yugang Hong, Yiguang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China EXQUISITUS Centre for E-City School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783902823625

This paper considers the distributed estimation of an unstable target via constant-gain estimators under local communications and channel fading. The communication graph is assumed to be fixed and undirected, and the channel fading is assumed to be identical. Necessary and sufficient conditions on communication network over which the state of the unstable target can be estimated in the mean square sense are given for both continuous-time and discrete-time cases, which reveal the fundamental limitation on distributed estimation induced by local communications, channel fading, and target dynamics. In addition, our results for the case without channel fading and the case with separate communications are consistent with the results in the literature. © IFAC.

关键词： Fading channels

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Investigation of mental fatigue induced by a continuous mental arithmetic task based on EEG coherence analysis

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 461卷 33-38页

作者： Chen, Lanlan Zhao, Y. Zhang, Jian Zou, Junzhong Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology 130 Meilong Road Shanghai200237 China

ISBN: (纸本)9783662452820

In the present study, twelve volunteers were participated in a 2 h continuous mental arithmetic task without any break, which was designed to induce mental fatigue. The negative influence was investigated through EEG coherence, which was used as a measure of synchronization of different underlying brain regions. It was observed that the sustained mental task led to increased EEG coherence, which did not result in more efficient performance. The change of EEG coherence was widespread not limited to specific brain regions or frequency bands. The variation of EEG coherence combined with behavior performance validated the impact of mental fatigue caused by a continuous mental task. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Brain

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Statistical process monitoring based on improved principal component analysis and its application to chemical processes

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2013年第7期14卷 520-534页

作者： Chu-dong TONG Xue-feng YAN Yu-xin MA Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

In this paper, a novel criterion is proposed to determine the retained principal components (PCs) that capture the dominant variability of online monitored data. The variations of PCs were calculated according to their mean and covariance changes between the modeling sample and the online monitored data. The retained PCs containing dominant variations were selected and defined as correlative PCs (CPCs). The new Hotelling's T2 statistic based on CPCs was then employed to monitor the process. Case studies on the simulated continuous stirred tank reactor and the well-known Tennessee Eastman process demonstrated the feasibility and effectiveness of the CPCs-based fault detection methods.

关键词： Fault detection Principal component analysis (PCA) Correlative principal components (CPCs) Tennessee Eastman process

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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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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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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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A new improved Alopex-based evolutionary algorithm and its application to parameter estimation

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Journal of Central South University 2013年第1期20卷 123-133页

作者：桑志祥李绍军董跃华 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education (East China University of Science and Technology)

In this work, focusing on the demerit of AEA (Alopex-based evolutionary algorithm) algorithm, an improved AEA algorithm (AEA-C) which was fused AEA with clonal selection algorithm was proposed. Considering the irrationality of the method that generated candidate solutions at each iteration of AEA, clonal selection algorithm could be applied to improve the method. The performance of the proposed new algorithm was studied by using 22 benchmark functions and was compared with original AEA given the same conditions. The experimental results show that the AEA-C clearly outperforms the original AEA for almost all the 22 benchmark functions with 10, 30, 50 dimensions in success rates, solution quality and stability. Furthermore, AEA-C was applied to estimate 6 kinetics parameters of the fermentation dynamics models. The standard deviation of the objective function calculated by the AEA-C is 41.46 and is far less than that of other literatures' results, and the fitting curves obtained by AEA-C are more in line with the actual fermentation process curves.

关键词： Alopex evolutionary algorithm Alopex-based evolutionary algorithm clone selection parameter estimation

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