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3rd International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013

作者： Li, MingHao Wang, XueWu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China

Particle swarm optimization algorithm tends to fall into local optimum sometimes. To resolve this problem, an improved particle swarm optimization algorithm based on two kinds of different chaotic maps is proposed. The algorithm produces primitive chaotic particle swarm using the uniform distribution of Tent map and improves the diversity of search. When the particle swarm evolves to a local optimum, the chaotic mutation operator produced by Logistic map is adopted to form a disturbance on the swarm to drive particle swarm jump out of local optimum and approach the global optimum. Meanwhile, an adaptive inertia weight factor is introduced to adjust particles inertia weight factor adaptively, which forms a new 2-chaotic maps embedded adaptive particle swarm optimization algorithm (2-CMEAPSO) that can fully utilize the randomness and ergodicity of the chaotic motion to enhance optimization capability. Experimental results show that the improved algorithm can efficiently overcome the premature of standard particle swarm optimization algorithm. Besides, it has stronger global optimization ability and higher accuracy than the basic particle swarm optimization algorithm.

关键词： Global optimization

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A new co-evolutionary immune algorithm for flow shop with zero wait

A new co-evolutionary immune algorithm for flow shop with ze...

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5th FTRA International Conference on Computer Science and its Applications, CSA 2013

作者： Xu, Zhenhao Zhang, Shun Gu, Xingsheng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

ISBN: (纸本)9783642416736

The flow shop scheduling problems with zero wait is considered as one of the most challenging problems in the field of scheduling. This paper deals with the problem considering the makespan minimization as the objective. In order to solve the corresponding model, a new co-evolutionary immune algorithm (NCIA) is proposed based on the '80/20' rule and a designed local search strategy. Moreover, a global crossover operator is presented to preserve excellent genes fragment and increase the diversity of population during the process of evolution. to confirm the performance of the proposed algorithm, in terms of solution quality, the algorithm is applied to various test instances of benchmark problems available in the literature. The computational results show that the proposed algorithm outperforms other algorithms. © 2014 Springer-Verlag Berlin Heidelberg.

关键词： Scheduling

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Octane model based on principal component analysis and neural network by near-infrared spectroscopy and its application in online gasoline blending process 3

Octane model based on principal component analysis and neura...

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3rd International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013

作者： He, Kaixun Cheng, Hui Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China

For the gasoline pipeline blending process, recipe optimization system is greatly dependent on the near-infrared spectroscopy online analyzer, whose spectral model plays an important role in the measurement. The sepectral model's accuracy and adaptability directly affect the applicability of the entire online blending system. This paper studies how to establish model for gasoline octane number for the gasoline pipeline blending process with near-infrared spectroscopy online analyzer. It is proposed using principal component analysis (PCA) together with Artificial Neural Network (ANN) method to establish spectral-model for octane number. Multivariate linear regressions(MLR) and partial least squares (PLS) method have also been used to establish gasoline octane model for comparison purpose. The results show that the model established by PCA and ANN has strong anti-jamming capability and suitable for gasoline online blending application.

关键词： Principal component analysis

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A hybrid discrete harmony search algorithm for flow shop scheduling with limited buffers 3

A hybrid discrete harmony search algorithm for flow shop sch...

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3rd International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013

作者： Cui, Zhe Gu, Xing-Sheng Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

The flow shop scheduling problem with limited buffers is widely existing in manufacturing systems. This article proposes a hybrid discrete harmony search algorithm for the problem to minimize total flow time. The algorithm presents a novel discrete improvisation and a differential evolution scheme with the job-permutation-based representation. Moreover, the discrete harmony search is hybridized with the problem-dependent local search based on insert neighborhood to balance the global exploration and local exploitation. In addition, an orthogonal experiment design is employed to provide a receipt for turning the adjustable parameters of the algorithm. Comparisons based on the Taillard benchmarks indicate the superiority of the proposed algorithm in terms of effectiveness and efficiency.

关键词： Manufacture

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Fixed-time consensus for multi-agent systems under directed and switching interaction topology

Fixed-time consensus for multi-agent systems under directed ...

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2014 American control Conference, ACC 2014

作者： Zuo, Zongyu Yang, Wen Tie, Lin Meng, Deyuan Beijing 100191 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai 200237 China Beijing 100191 China

ISBN: (纸本)9781479932726

In this paper, we address the fixed-time consensus problem for multi-agent systems in networks with directed and switching interaction topology. With the introduction of mirror operation, two global distributed nonlinear consensus protocols are constructed for each first-order agent under strongly connected information flow. The distinctive feature of this paper is to address the explicit bounds of the finite settling time for both protocols are independent of initial condition, which makes it possible for network consensus problems of a multi-agent team with guaranteed convergence time. Further, the second protocol is valid for the networks of multi-agents with switching topology provided that the sum of time intervals, in which the information flow is strongly connected, is larger than the estimated upper-bound for settling time. Finally, simulations are provided to demonstrate the performance and effectiveness of our theoretical results. © 2014 American Automatic control Council.

关键词： Multi agent systems

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Co-simulation Research of Autonomous Landing control System 33

Co-simulation Research of Autonomous Landing Control System

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第三十三届中国控制会议

作者： WANG Zhaoning WU Shengxi DUN Xiangming GU Xingsheng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Research Institute of Robotics Shanghai Jiao Tong University

ISBN: (纸本)9781479947249

In this paper, a control simulation of the autonomous landing process of a Vertical Take-Off and Landing(VTVL) Reusable Launch Vehicle(RLV) is proposed and we consider the effects of the inner liquid propellant sloshing, elastic vibration, disturbance force, disturbance torque and other complex conditions in the virtual RLV model. On the basis of dynamics modeling of the RLV, we analyzed RLV's landing process. The landing control system was designed under certain conditions. Co-simulation Research was achieved by ADAMS and MATLAB/Simulink. The simulation results show that the control system performs well.

关键词： vertical take-off and landing autonomous landing reusable launch vehicle control system co-simulation research

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Adaptive Local Outlier Probability for Dynamic Process Monitoring

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Chinese Journal of Chemical Engineering 2014年第7期22卷 820-827页

作者：马玉鑫侍洪波王梦灵 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

Complex industrial processes often have multiple operating modes and present time-varying behavior. The data in one mode may follow specific Gaussian or non-Gaussian distributions. In this paper, a numerically efficient movingwindow local outlier probability algorithm is proposed, lies key feature is the capability to handle complex data distributions and incursive operating condition changes including slow dynamic variations and instant mode shifts. First, a two-step adaption approach is introduced and some designed updating rules are applied to keep the monitoring model up-to-date. Then, a semi-supervised monitoring strategy is developed with an updating switch rule to deal with mode changes. Based on local probability models, the algorithm has a superior ability in detecting faulty conditions and fast adapting to slow variations and new operating modes. Finally, the utility of the proposed method is demonstrated with a numerical example and a non-isothermal continuous stirred tank reactor.

关键词： Time-varying Complex data distribution Local outlier probability Multi-mode Fault detection

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Plant-wide process monitoring based on mutual information-multiblock principal component analysis

Plant-wide process monitoring based on mutual information-mu...

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作者： Jiang, Qingchao Yan, Xuefeng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology MeiLong Road No. 130 Shanghai200237 China

Multiblock principal component analysis (MBPCA) methods are gaining increasing attentions in monitoring plant-wide processes. Generally, MBPCA assumes that some process knowledge is incorporated for block division;however, process knowledge is not always available. A new totally data-driven MBPCA method, which employs mutual information (MI) to divide the blocks automatically, has been proposed. By constructing sub-blocks using MI, the division not only considers linear correlations between variables, but also takes into account non-linear relations thereby involving more statistical information. The PCA models in sub-blocks reflect more local behaviors of process, and the results in all blocks are combined together by support vector data description. The proposed method is implemented on a numerical process and the Tennessee Eastman process. Monitoring results demonstrate the feasibility and efficiency. © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Process monitoring

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Distributed Mo del Predictive control Based on Multi-agent Mo del for Electric Multiple Units

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自动化学报 2014年第11期40卷 2625-2631页

作者： LI Zhong-Qi School of Mechanical and Electrical Engineer Nanchang University Nanchang 330031 China School of Electrical and Electronic Engineering East China Jiaotong University Nanchang 330013 China Key Laboratory of Advanced Control and Optimization of Jiangxi Province Nanchang 330013 China

The distributed-power electric multiple units (EMUs) are widely used in high-speed railway. Due to the structural characteristic of mutual-coupled power units in EMUs, each power unit is set as an agent. Combining with the traction/brake characteristic curve and running data of EMUs, a subtractive clustering method and pattern classification algorithm are adopted to set up a multi-model set for every agent. Then, the multi-agent model is established according to the multi-agent network topology and mutual-coupled constraint relations. Finally, we adopt a smooth start switching control strategy and a multi-agent distributed coordination control algorithm to ensure the synchronous speed tracking control of each agent. Simulation results on the actual CRH380A running data show the effectiveness of the proposed approach.

关键词：分布式电源电动车组多代理预测控制多单元协调控制算法多Agent 功率单元

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Improving differential evolution with impulsive control framework

Improving differential evolution with impulsive control fram...

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Congress on Evolutionary Computation

作者： Wei Du Sunney Yung Sun Leung Chun Kit Kwong Yang Tang Institute of Textiles and Clothing The Hong Kong Polytechnic University Hong Kong Hong Kong Polytechnic University Kowloon HK Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (纸本)9781479974931

Differential evolution (DE) is a simple but powerful evolutionary algorithm, which has been widely and successfully used in many areas. In this paper, an impulsive control method is introduced to the DE framework, and the impulsive DE (IpDE) is proposed for improving the performance of DE. The impulsive control operation instantly moves the individuals which do not update for continuous pre-defined generations to a desired state based on the individuals with better fitness values in the current population. This way, IpDE controls individuals' positions in the space domain according to the stagnation status of the population. In order to validate the effectiveness of IpDE, the presented framework is applied to the original DE algorithms, as well as several state-of-the-art DE variants. Experimental results exhibit that IpDE is a simple but effective framework to improve the performance of the studied DE algorithms.

关键词： Sociology Statistics optimization Radiation detectors Aerospace electronics Hybrid power systems Evolution (biology)

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