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Cultivation of three microalgae strains under mixotrophic conditions for biodiesel production

chemical Engineering Transactions 2016年 50卷 409-414页

作者： Rios, Luisa F. Da Silva Soares, Carla Tasić, Marija B. Maciel, Maria R. Wolf Filho, Rubens Maciel University of Campinas Chemical Engineering Faculty Laboratory of Optimization Design and Advanced Process Control-Bioen Division Av. Albert Einstein 500 Campinas SP Brazil Faculty of Technology University of Niš Bulevar oslobodjenja 124 Leskovac16000 Serbia

ISBN: (纸本)9788895608419

Microalgal biomass have a potential to be used as feedstock for biodiesel production because of high photosynthetic rates, high biomass production, faster growth in comparison to traditional feedstocks and to not be competitive with food production. In this paper, the growth and lipid content of three microalgae strains, namely Chorella vulgaris, Desmodesmus sp. and Desmodesmus brasiliensis, were studied during 9 days of mixotrophic cultivation. The laboratory scale experiments were carried out in BG-11 media enriched with 10 g/L glucose at initial medium pH of 7.5, temperature of 26 ± 4 °C and light flux of 62 μE m-2 s-1. The highest biomass concentration of 3.82 mg/mL was found in the Desmodesmus brasiliensis, followed with 3.64 mg/mL of Desmodesmus sp. and 3.32 mg/mL of Chorella vulgaris strain. However, the Desmodesmus brasiliensis had the lowest lipid content of 6%, followed with 13.2% of Chorella vulgaris, whereas the Desmodesmus sp. strain produced the highest lipids (19.45%). Copyright © 2016, AIDIC Servizi S.r.l.,.

关键词： Feedstocks

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Removal of EEG artifacts for BCI applications using fully Bayesian tensor completion

Removal of EEG artifacts for BCI applications using fully Ba...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Yu Zhang Qibin Zhao Guoxu Zhou Jing Jin Xingyu Wang Andrzej Cichocki Key Laboratory for Advanced Control and Optimization for Chemical Processes East China University of Science and Technology China Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Japan Skolkowo Institute of Science and Technology Moscow Russia

High accuracy of electroencephalogram (EEG) classification can hardly be achieved if the signals are contaminated by severe artefacts. One helpless way to avoid such artefacts is usually to directly discard the severely disturbed EEG segments. This study considers a more elegant way that tries to recover the disturbed segments from other undisturbed segments. The possible artefacts in EEG are treated as missing values. A Bayesian tensor factorization (BTF) based method is proposed to implement EEG completion for artefact removal. By specifying a sparsity-inducing hierarchical prior, the underlying low-rank tensor is discovered from incomplete EEG tensor with automatically inferred model parameters. The EEG missing values are effectively predicted with robustness to overfitting. Effectiveness of the BTF algorithm is demonstrated on EEG data recorded from seven subjects in a brain-computer interface paradigm based on event-related potentials.

关键词： Electroencephalography Tensile stress Bayes methods Brain modeling Feature extraction Brain-computer interfaces Electric potential

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Fuzzy H∞ Filtering for Nonlinear Networked Systems with Multiple Stochastic Time-Varying Delays, Packet Dropouts and Sensor Saturation 34

Fuzzy H∞ Filtering for Nonlinear Networked Systems with Mul...

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第三十四届中国控制会议

作者： XU Xiaoli YAN Huaicheng ZHANG Hao SHI Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education School of information Science and Engineering East China University of Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education

ISBN: (纸本)9781467374439

This paper investigates the problem of H∞ filter design for a class of nonlinear networked system based on T-S fuzzy model. Multiple stochastic time-varying delays and some incomplete information are considered simultaneously. Incomplete information includes randomly occurring sensor saturation and packet dropouts. Stochastic time-varying delays are depicted as a sequence of stochastic and independent variables, which take values on 0 and 1. Two sets of Bernoulli distributed white noises are introduced to describe randomly occurring sensor saturation and packet dropouts. System conservatism is reduced due to introduce an approach of piecewise quadratic Lyapunov function. By solving a set of linear matrix inequalities(LMIs), the filter parameters are obtained. Finally, a simulation example is provided to illustrate the effectiveness of the proposed filter design approach.

关键词： H ∞ filtering,multiple time-varying delays,randomly occurring sensor saturation,packet dropouts,piecewise quadratic Lyapunov function

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Impulsive quasi-synchronization of delayed dynamic networks with asymmetric connections

Impulsive quasi-synchronization of delayed dynamic networks ...

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Annual Conference of Industrial Electronics Society

作者： Wangli He Chen Peng Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China School of Mechatronic Engineering and Automation Shanghai University P.R. China

Quasi-synchronization of heterogenous dynamic networks is studied by using impulsive control in this paper. The asymmetric network connections are considered. First, the weighted average state is introduced as the virtual leader. By defining the synchronization error between the virtual leader and the network node, impulsive quasi-synchronization is analyzed and a criterion is derived to ensure quasi-synchronization in the delayed heterogenous network. Then delayed networks with symmetric connections and delay-free networks are studied, respectively, with simpler conditions obtained. Numerical simulations demonstrate the effectiveness of the derived results.

关键词： Synchronization Heterogeneous networks Eigenvalues and eigenfunctions Trajectory Network topology optimization chemical processes

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Event-triggered distributed predictive control for constrained large-scale linear systems

Event-triggered distributed predictive control for constrain...

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Chinese control Conference (CCC)

作者： Xu Su Yuanyuan Zou Yugang Niu Tinggang Jia Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai Shanghai CN Automation Division Shanghai Electric Group Co. Ltd China

This paper investigates the problem of event-triggered dual-mode distributed predictive control (DPC) for constrained large-scale linear systems subject to bounded disturbances. Based on input-to-state stability (ISS) theory, the event-triggering condition involving information of the subsystem itself is derived. A dual-mode predictive control scheme is designed to reduce information exchanges with neighboring subsystems. The upper bound of disturbances for ensuring the recursive feasibility and closed-loop stability are developed. Finally, a simulation example is given to show that the presented method is able to save computation resources and communication resources while guaranteeing the desired control performance.

关键词： Silicon Predictive control optimization Large-scale systems Stability analysis Trajectory Linear systems

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Online Batch process Monitoring Based on Just-in-Time Learning and Independent Component Analysis

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Journal of Donghua University(English Edition) 2016年第6期33卷 944-948页

作者： WANG Li SHI Hong-bo School of Electrical and Electronic Engineering Shanghai Institute of Technology Shanghai 200230 China Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China

A new method was developed for batch process monitoring in this paper. In the devdopad method, just-in-time learning （ JITL ） and independent component analysis （ICA） were integrated to build JITL-ICA monitoring scheme. JITL was employed to tackle with the characteristics of batch process such as inherent time- varying dynamics, multiple operating phases, and especially the case of uneven length stage. According to new coming test data, the most correlated segmentation was obtained from batch-wise unfolded training data by JITL. Then, ICA served as the principal components extraction approach. Therefore, the *** distributed data can also be addressed under this modeling framework. The effectiveness and superiority of JITL-ICA based monitoring method was demonstrated by fed-batch penicillin fermentation.

关键词： batch process monitoring just-in-time learning(JITL) independent component analysis(ICA)

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Cooperative control of heterogeneous multi-agent systems via distributed adaptive output regulation under switching topology

Cooperative control of heterogeneous multi-agent systems via...

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Annual Conference of Industrial Electronics Society

作者： Ruohan Yang Hao Zhang Huaicheng Yan Fuwen Yang Department of Control Science and Engineering Tongji University Shanghai China Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China School of Engineering Griffith University Australia

A novel distributed adaptive output feedback control strategy is developed to solve the cooperative output regulation problem of heterogeneous general linear multi-agent systems(MASs) under switching topology. The proposed control strategy avoids using the minimal non-zero eigenvalue of Laplacian matrix when calculating gain matrix, and the communication topology is assumed to contain a directed spanning tree only frequently. It is shown that individual agents could track external signal asymptotically and achieve disturbance rejection. Ultimately, a simulation is presented to exemplify the effectualness of the main result.

关键词： Topology Switches Laplace equations Output feedback Eigenvalues and eigenfunctions Adaptive control

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A fast MPC algorithm for reducing computation burden of MIMO

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Chinese Journal of chemical Engineering 2015年第12期23卷 2087-2091页

作者：祁荣宾梅华陈超钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology

The computation burden in the model-based predictive control algorithm is heavy when solving QR optimization with a limited sampling step, especially for a complicated system with large dimension. A fast algorithm is proposed in this paper to solve this problem, in which real-time values are modulated to bit streams to simplify the multiplication. In addition, manipulated variables in the prediction horizon are deduced to the current control horizon approximately by a recursive relation to decrease the dimension of QR optimization. The simulation results demonstrate the feasibility of this fast algorithm for MIMO systems.

关键词： Fast MPC algorithm Computation burden One-bit operation Dimension reduction

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Consensus of discrete-time multi-agent systems via low-gain impulsive control

Consensus of discrete-time multi-agent systems via low-gain ...

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International Conference on control, Automation, Robotics and Vision

作者： Yang Tang Zhen Li Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai 200237 PR China School of Information Science and Technology Donghua University Shanghai 201620 PR China

ISBN: (纸本)9781509035502

In this brief, a novel impulsive control has been proposed for consensus problems of discrete-time multi-agent systems. Utilizing the Lyapunov technique, a parametric discrete-time Riccati equation has been obtained in order to design impulsive controller. The derived criteria show that such impulsive control relies on the proper value of designed parameters and the upper bound of impulsive intervals. Finally, the applicability of proposed strategy is given through a numerical example.

关键词： Impulsiveness discrete-time Multi-agent systems Riccati equations numerical example

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Multi-stage process Analysis and Modelling based Online Monitoring for Chip Packaging process

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IFAC-PapersOnLine 2015年第28期48卷 993-998页

作者： Qin, Yan Zhao, Chunhui Gao, Furong State Key Laboratory of Industrial Control Technology Department of Control Science and Engineering Zhejiang University Hangzhou310027 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Shanghai20023 China Department of Chemical and Biomolecular Engineering The Hong Kong University of Science and Technology Cleary Water Bay Kowloon Hong Kong

As one of the crucial semiconductor manufacturing steps, chip packaging process plays an important role to provide a phys ical protection, electric interconnection environment for naked wafer. In the present work, the chip packaging process is analyzed in detail for process understanding and monitoring. First, detailed description of the chip packaging process is given to help better understand the process. Then, the underlying process characteristics are explored and multi-stage nature of chip packaging process is revealed by t racking changes of process variable correlat ions. The whole process is divided into several modeling phases using a step-wise sequential phase partition algorithm, agreeing well with the real process. Stage-based online monitoring and fault diagnosis is performed to analyze some common abnormal behaviors in this process. The stage-based analysis results not only provide reliable online monitoring and fault diagnosis performance but also provide enhanced process understanding. © 2015

关键词： Chip scale packages Batch data processing Failure analysis Fault detection Packaging Partial discharges process monitoring Semiconductor device manufacture Batch process Chip packaging Diagnosis performance Electric interconnection Multi stage process characteristics process understanding Semiconductor manufacturing

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