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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Symone Soares Rui Araújo Pedro Sousa Francisco Souza Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

Industries are faced with the choice of suitable process control policies to improve costs, quality and raw material consumption. In the paper pulp industry, it is important to estimate quickly the Chemical Oxygen Demand (COD), a parameter that is highly correlated to product quality. Soft Sensors (SSs) have been established as alternative to hardware sensors and laboratory measurements for monitoring and control purposes. However, in real setups it is often difficult to get sufficient data for SS development. This work proposes Ensemble Methods (EMs) as a way to improve the SS performance for small datasets. EMs use a set of models to obtain better prediction. Their success is usually attributed to the diversity. Bootstrap and noise injection are used to produce diverse models. Several combinations of EMs are compared. The SS is successfully applied to estimate COD in a pulp process.

关键词： Noise Training Artificial neural networks Diversity reception Chemicals Paper pulp Predictive models

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Stable indirect adaptive predictive fuzzy control for industrial processes

Stable indirect adaptive predictive fuzzy control for indust...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jérôme Mendes Rui Araújo Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

The paper proposes a stable indirect adaptive fuzzy predictive control, which is based on a discrete-time Takagi-Sugeno (T-S) fuzzy model and on the Generalized predictive control (GPC) algorithm. The T-S fuzzy model is used to approximate the unknown nonlinear plant, that to provide good accuracy in identification of unknown model parameters, three online adaptive laws are proposed. It is demonstrated that the tracking error remains bounded. The stability of closed-loop control system is studied and proved via the Lyapunov stability theory. To validate the theoretical developments and to demonstrate the performance of the proposed control, the controller is applied on a nonlinear simulated laboratory-scale liquid-level process. The simulation results show that the proposed method has a good performance and disturbance rejection capacity in industrial processes.

关键词： Adaptation models Mathematical model Predictive control Predictive models Nonlinear systems Computational modeling

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Variable and time-lag selection using empirical data

Variable and time-lag selection using empirical data

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Francisco Souza Rui Araújo Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

The paper proposes a method to select the best variables and respective time-lags for industrial applications when the objective is the estimation of a target variable using the information content of empirical data. No further information is assumed about the process. The problem of jointly selecting the best variables and the respective time-lags is treated as a variable selection problem. This assumption implies an increase of input dimensionality and multicollinearity into input space. Then, a multidimensional mutual information estimator based on the l-nearest neighbor algorithm is used in a forward search procedure to select the best variables and and respective time-lags. To verify the performance of selected variables and delays, the method was successfully applied in two data sets. A least squares support vector machine was used as the main model for the soft sensor in both cases.

关键词： Input variables Delay Mutual information Correlation Computational modeling Estimation Predictive models

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Co-evolutionary genetic Multilayer Perceptron for feature selection and model design

Co-evolutionary genetic Multilayer Perceptron for feature se...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Francisco Souza Tiago Matias Rui Araójo Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

This paper proposes a method for Soft Sensors design using a Multilayer Perceptron model based on co-evolutionary genetic algorithms, called CEV-MLP. This method jointly and automatically selects the best input variables and the best configuration of the network for the prediction setting. The CEV-MLP is constituted by three levels, the first level selects the best input variables and respective delays set, the second level is composed by the parameters of hidden layers to be optimized (number of neurons in the hidden layers and transfer function), and the third level is the combination of first and second level. The method was successfully applied, and compared with two state-of-the-art methods, in three real datasets. In all the experiments, the proposed method shows the best approximation accuracy, while all the design of the prediction setting is performed automatically.

关键词： Input variables Biological cells Neurons Delay Genetic algorithms Sensors Training

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Automatic extraction of the fuzzy control system for industrial processes

Automatic extraction of the fuzzy control system for industr...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jérôme Mendes Ricardo Seco Rui Araújo Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

The paper proposes a new method to automatically extract all fuzzy parameters of a Fuzzy Logic Controller (FLC) in order to control nonlinear industrial processes. The learning of the FLC is performed from controller input/output data and by a hierarchical genetic algorithm (HGA). The algorithm is composed by a five level structure, where the first level is responsible for the selection of an adequate set of input variables. The second level considers the encoding of the membership functions. The individual rules are defined on the third level. The set of rules are obtained on the fourth level, and finally, the fifth level, selects the elements of the previous levels, as well as, the t-norm operator, inference engine and defuzzifier methods which constitute the FLC. To demonstrate and validate the effectiveness of the proposed algorithm, it is applied to control a simulated water tank level process.

关键词： Fuzzy systems Input variables Genetic algorithms Process control Encoding Delay Genetics

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Adaptive predictive control with recurrent fuzzy neural network for industrial processes

Adaptive predictive control with recurrent fuzzy neural netw...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jérôme Mendes Nuno Sousa Rui Araújo Institute of Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

The paper proposes an adaptive fuzzy predictive control method. The proposed controller is based on the Generalized predictive control (GPC) algorithm, and a recurrent fuzzy neural network (RFNN) is used to approximate the unknown nonlinear plant. To provide good accuracy in identification of unknown model parameters, an online adaptive law is proposed to adapt the consequent part of the RFNN, and its antecedent part is adapted by back-propagation method. The stability of closed-loop control system is studied and proved via the Lyapunov stability theory. A nonlinear lab oratory-scale liquid-level process is used to validate and demonstrate the performance of the proposed control. The simulation results show that the proposed method has good performance and disturbance rejection capacity in industrial processes and outperforms the PID and the classical GPC controllers.

关键词： Adaptation models Predictive models Predictive control Fuzzy control Mathematical model Fuzzy neural networks Equations

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Erratum to “A New Solution for Camera Calibration and Real-Time Image Distortion Correction in Medical Endoscopy–Initial Technical Evaluation” [Mar 12 634-644]

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IEEE Transactions on Biomedical engineering 2012年第7期59卷 2095-2095页

作者： Rui Melo João P. Barreto Gabriel Falcão Institute for Systems and Robotics and Department of Electrical and Computer Engineering Faculty of Science and Technology Coimbra Portugal Instituto de Telecomunicações Faculty of Science and Technology Coimbra Portugal

In the above-titled paper (ibid., vol. 59, no. 3, pp. 634-644, Mar. 2012), the affiliation of G. Falcao should have read as follows: G. Falcao is with the Instituto de Telecomunicacoes and department of electrical and computer engineering, Faculty of Science and Technology, University of Coimbra, 3030-290 Coimbra, Portugal (e-mail: gff@***).

关键词： Cameras Calibration Biomedical imaging Endoscopes Graphics processing unt Lenses

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Active CMOS-MEMS conductive probes and arrays for tunneling-based atomic-level surface imaging

Active CMOS-MEMS conductive probes and arrays for tunneling-...

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International Solid-State Sensors, Actuators and Microsystems Conference

作者： Zhang, Y. Wang, J. Santhanam, S. Fedder, G.K. Department of Electrical and Computer Engineering United States Institute for Complex Engineered Systems Pittsburgh PA United States Robotics Institute Carnegie Mellon University Pittsburgh PA United States

ISBN: (纸本)9781457701573

This paper reports on development of AFM-like active CMOS-MEMS conductive probes and arrays. The active probes are aimed for scanning tunneling microscopy (STM) imaging and field-emission (FE) assisted nanostructure formation. Two kinds of STM tip approaches compatible with CMOS-MEMS process Electron-Induced Beam Deposition (EBID) and Spindt tip method are presented, and their functionality is examined. Atomic-level resolution is achieved using tips in an ultra-high vacuum (UHV) STM. The MEMS probe working in ambient STM is also demonstrated. The active probe is equipped with a transimpedance amplifier (TIA) for tip FE current measurement around a nominal value of 1 nA. © 2011 IEEE.

关键词： CMOS integrated circuits

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Modeling and SVPWM control of quasi-Z-source inverter

Modeling and SVPWM control of quasi-Z-source inverter

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11th International Conference on electrical Power Quality and Utilisation, EPQU 2011

作者： Liu, Yushan Ge, Baoming Ferreira, Fernando J. T. E. De Almeida, Anibal T. Abu-Rub, Haitham School of Electrical Engineering Beijing Jiaotong University Beijing China Institute of Systems and Robotics University of Coimbra Coimbra Portugal Engineering Institute of Coimbra Polytechnic Institute of Coimbra Coimbra Portugal Department of Electrical and Computer Engineering Texas A and M University at Qatar Doha Qatar

ISBN: (纸本)9781467303798

In today's renewable energy power generation systems, inverters have become key devices connected between energy sources and power grids. The newly presented quasi-Z-source inverter (qZSI) has the unique advantages of boosting DC bus voltage without additional boost link, lower component ratings, as well as constant DC input current compared with the traditional Z-source inverter. To better design the control schemes of this novel topology, the small-signal model is deduced using state variables perturbance mathematical analysis. By this model, the voltage-current closed-loop control of shoot-through duty cycle is designed. The space vector PWM (SVPWM) technique is modified to satisfy the particularity of qZSI. Simulation results certify the correctness and effectiveness of the proposed model and control strategies and demonstrate the applicability of qZSI technology to overcome the disturbances from DC link or AC loads in renewable energy power generation systems. © 2011 IEEE.

关键词： Topology

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Cost-efficient built-in repair analysis for embedded memories with on-chip ECC

Cost-efficient built-in repair analysis for embedded memorie...

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International Symposium on Access Spaces

作者： Sun, Hongbin Zhao, Jizhong Wang, Fei Zheng, Nanning Zhang, Tong Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an Shaanxi 710049 China Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute Troy NY 12180 United States

ISBN: (纸本)9781457707179

This paper concerns low-cost implementation of built-in repair analysis (BIRA) for embedded memories. As embedded memories become more and more dominant in system-on-chip (SoC) design, it is very crucial to achieve sufficiently high embedded memory yield. Due to the increasing number of diversified embedded memories on chip, external memory testing and redundancy repair analysis become inadequate and the use of BIRA becomes more attractive and even indispensable. The essential challenge of BIRA design is to how to minimize its unnegligible implementation cost without sacrificing the achievable repair rate. The key feature that distinguishes this work from prior work is that, motivated by the fact that almost all the embedded memories use error correction code (ECC) for soft error tolerance, we propose to appropriately leverage such existing built-in error correction capability to enable very low-cost BIRA implementations while maintaining the same and even higher defect repair rate and the same soft error tolerance. With this underlying theme, this paper presents a specific design solution, and its effectiveness and advantages over existing solutions has been successfully demonstrated using computer simulations. © 2011 IEEE.

关键词： Repair

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