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Dynamic anti-windup design in anticipation of actuator saturation

Dynamic anti-windup design in anticipation of actuator satur...

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作者： Wu, Xiongjun Lin, Zongli Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 United States

ISBN: (纸本)9781457700804

In a traditional anti-windup design, the anti-windup mechanism is set to be activated as soon as the control signal saturates the actuator. A recent innovation of delaying the activation of the anti-windup mechanism, both static and dynamic, until the saturation reaches to a certain level of severity has led to a performance improvement of the resulting closed-loop system. More recently, it has been shown that significant further performance improvements can be obtained by activating a static anti-windup mechanism in anticipation of actuator saturation, in comparison with the delayed activation design. This paper demonstrates that anticipatory activation of a dynamic anti-windup mechanism would also lead to significant performance improvements over both the immediate and delayed activation schemes. © 2011 AACC American Automatic control Council.

关键词： Chemical activation

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Voxel based treatment prediction using diffusion anisotropy indices and spatial information in Glioblastoma Multiform tumor

Voxel based treatment prediction using diffusion anisotropy ...

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2011 18th Iranian Conference of Biomedical Engineering, ICBME 2011

作者： Sabahi, Hadi Soltanian-Zadeh, Hamid Scarpace, Lisa Mikkelsen, Tom Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI 48202 United States Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI 48202 United States

ISBN: (纸本)9781467310055

In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatment response of each tumor voxel. These DAIs are Fractional Anisotropy, Mean Diffusivity, Relative Anisotropy, and Volume Ratio, extracted from Diffusion Tensor Imaging (DTI) data before treatment. The spatial information is considered as the distance of each tumor voxel from the tumor center, extracted from pre-treatment post-contrast T1-weighted Magnetic Resonance Images (pc-T1-MRI). DAIs and spatial information of each tumor voxel are considered as feature vector. DTI and pc-T1-MRI are gathered before and after the treatment of seven GBM patients. First, DAIs of all brain voxels and the distance of each tumor voxel from the tumor center are calculated. Second, the method registers pre-treatment DAI maps and post-treatment pc-T1-MRI to pre-treatment pc-T1-MRI. Next, the tumor is segmented using thresholding technique from pc-T1-MRI. Then, Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI are compared to label the feature vectors. Three classifiers were evaluated, including Support Vector Machine, K-Nearest Neighbor, and Artificial Neural Network. Classification results show a preference for K-Nearest Neighbor based on well-established performance measures. © 2011 IEEE.

关键词： Tumors

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Novel emotion dynamic express for robot

Novel emotion dynamic express for robot

引用

International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Dong-Hwa Kim Péter Baranyi Department of Instrumentation and Control Engineering Hanbat National University Daejeon South Korea Head of Cognitive Informatics research group involved in the System and Control Laboratory Computer and Automation Research Institute (MTA-SZTAKI) Hungarian Academy of Sciences Hungary

This paper proposes the novel emotion dynamic equation for emotion implementation like human's emotion. Almost general method use artificial approach such as neutral networks to classify emotion by using speech and face image data for human's emotion recognition. But high-dimension and large size of this data cause low-speed learning in robot system. The main idea of the proposed dynamic equation method is to dynamically express emotion by multi-agent function.

关键词： Robot sensing systems Humans Dynamics Face Equations

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Dynamic Anti-windup Design in Anticipation of Actuator Saturation

Dynamic Anti-windup Design in Anticipation of Actuator Satur...

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2011 American control Conference (ACC)

作者： Xiongjun Wu Zongli Lin Department of Automation and Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiaotong University Shanghai China Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA

关键词： Actuators Windup Linear matrix inequalities Simulation Automation Symmetric matrices

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Robust ℋ∞ output feedback control of discrete-time networked systems with adaptive quantizers

Robust ℋ∞ output feedback control of discrete-time network...

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IEEE Conference on Decision and control

作者： Faiz Rasool Dan Huang Sing Kiong Nguang Department of Electrical and Computer Engineering University of Auckland Auckland New Zealand Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiaotong University Shanghai China

Quantization effects are inevitable in networked control systems (NCSs). These quantization effects can be reduced by increasing the number of quantization levels. However, increasing the number of quantization levels may lead to network congestion, (i.e., the network needs to transfer more information than its capacity). In this paper, we investigate the problem of designing a robust ℋ ∞ output feedback controller for discrete-time networked systems with an adaptive quantization density or limited information. More precisely, the quantization density is designed to be a function of the network load condition which is modeled by a Markov process. A stability criterion is developed by using Lyapunov-Krasovskii functional and sufficient conditions for the existence of a dynamic quantized output feedback controller are given in terms of Bilinear Matrix Inequalities(BMIs). An iterative algorithm is suggested to obtain quasi-convex Linear Matrix Inequalities (LMIs) from BMIs. An example is presented to illustrate the effectiveness of the proposed design.

关键词： Quantization Delay Linear matrix inequalities Markov processes Closed loop systems Stability analysis Output feedback

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Robust partially mode delay-dependent ℋ∞ output feedback control of discrete-time networked control systems

Robust partially mode delay-dependent ℋ∞ output feedback c...

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American control Conference (ACC)

作者： Seunghwan Chae Dan Huang Sing Kiong Nguang The Department of Electrical and Computer Engineering University of Auckland Auckland New Zealand Department of Automation and Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiaotong University Shanghai China

This paper examines robust partially mode de lay dependent H ∞ output feedback controller design for discrete-time systems with random communication delays. A finite state Markov chain with partially known transition probabilities is used to model random communication delays between sensors and controller. Based on Lyapunov-Krasovskii functional, a novel methodology for designing a partially mode delay-dependent output feedback controller is proposed. Using cone complementarity linearization algorithm bilinear matrix inequalities (BMIs) are solved to obtain the controller gains. We also show that the results for completely known transition probabilities and completely unknown transition probabilities can be derived as special cases of our result. The effectiveness of the proposed design methodology is demonstrated by a numer ical example. To the best of authors' knowledge, the problem of designing an output feedback controller for a partially known transition probability has not been fully investigated.

关键词： Delay Markov processes Output feedback Linear matrix inequalities Robustness Silicon

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Training ANFIS system with DE algorithm

Training ANFIS system with DE algorithm

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Allahyar Z. Zangeneh Mohammad Mansouri Mohammad Teshnehlab Ali K. Sedigh Computer Engineering Department Science and Research Branch Islamic Azad university of Tehran Iran Intelligent System laboratory (ISLAB) Control Department K. N. Toosi University of Technology Tehran Iran Advanced Process Automation & Control laboratory (APAC) Control Department K. N. Toosi University of Technology Tehran Iran

In this study, a new type of training the adaptive network-based fuzzy inference system (ANFIS) is presented by applying different types of the Differential Evolution branches. The TSK-type consequent part is a linear model of exogenous inputs. The consequent part parameters are learned by a gradient descent algorithm. The antecedent fuzzy sets are learned by basic differential evolution (DE/rand/1/bin) and then with some modifications in it. This method is applied to identification of the nonlinear dynamic system, prediction of the chaotic signal under both noise-free and noisy conditions and simulation of the two-dimensional function. Instead of DE/rand/1/bin, this paper suggests the complex type (DE/current-to-best/1+1/bin & DE/rand/1/bin) on predicting of Mackey-glass time series and identification of a nonlinear dynamic system revealing the efficiency of proposed structure. Finally, the method is compared with pure ANFIS to show the efficiency of this method.

关键词： Vectors Adaptive systems Input variables Training Mathematical model Equations Firing

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On Energy-Efficient Trap Coverage in Wireless Sensor Networks

On Energy-Efficient Trap Coverage in Wireless Sensor Network...

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Real-Time systems Symposium (RTSS)

作者： Junkun Li Jiming Chen Shibo He Tian He Yu Gu Youxian Sun State Key Laboratory of Industrial Control Technology Zhejiang University China Computer Science and Engineering University of Minnesota USA Pillar of Information System Technology and Design Singapore University of Technology and Design Singapore

In wireless sensor networks (WSNs), trap coverage has recently been proposed to tradeoff between the availability of sensor nodes and sensing performance. It offers an efficient framework to tackle the challenge of limited resources in large scale sensor networks. Currently, existing works only studied the theoretical foundation of how to decide the deployment density of sensors to ensure the desired degree of trap coverage. However, the practical issues such as how to efficiently schedule sensor node to guarantee trap coverage under an arbitrary deployment is still left untouched. In this paper, we formally formulate the Minimum Weight Trap Cover Problem and prove it is an NP-hard problem. To solve the problem, we introduce a bounded approximation algorithm, called Trap Cover Optimization (TCO) to schedule the activation of sensors while satisfying specified trap coverage requirement. The performance of Minimum Weight Trap Coverage we find is proved to be at most O(ρ) times of the optimal solution, where ρ is the density of sensor nodes in the region. To evaluate our design, we perform extensive simulations to demonstrate the effectiveness of our proposed algorithm and show that our algorithm achieves at least 14% better energy efficiency than the state-of-the-art solution.

关键词： Sensors Wireless sensor networks Approximation algorithms Algorithm design and analysis Approximation methods Euclidean distance Optimization

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Assessing lung volumetric variation to detect and stage COPD

Assessing lung volumetric variation to detect and stage COPD

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2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011

作者： Hosseini, M. Parsa Soltanian-Zadeh, Hamid Akhlaghpoor, Shahram Department of Electrical Engineering Islamic Azad University Science and Research Branch of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Radiology Tehran University of Medical Sciences Sina Hospital Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) is a devastating disease. In this paper, we propose a novel method for scoring of air trapping in the lungs for detection and evaluation of COPD. The proposed method finds volumetric changes of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared. For this comparison, the lungs parenchyma in the inspiration and expiration images are found and changes in the surface and volume of the lungs between inspiration and expiration are used to define quantitative measures (features). Using these features, the subjects are classified into two groups of normal class and COPD patients using a Bayesian classifier. In addition, t-tests are applied to evaluate discrimination powers of the features for this classification. The main advantage of the proposed method is its ability to estimate air trapping in the lungs from CT images without human intervention. The proposed method may assists radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. It may also assist them with the scoring of the disease (severity of air trapping in the lungs). © 2011 IEEE.

关键词： computerized tomography

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A novel method for identification of COPD in inspiratory and expiratory states of CT images

A novel method for identification of COPD in inspiratory and...

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2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) refers to a group of lung diseases that block airflow and cause a huge degree of human suffering. While there is no cure for COPD and the lung damage that results in this disease cannot be reversed, it is very important to diagnose it as early as possible. Additional to diagnosis, using a mathematical model to estimate severity of disease would be helpful for evaluation of treatment effects. This paper presents a new method for identifying COPD from three-dimensional (3-D) pulmonary X-ray CT images. The method has five main steps. First, corresponding positions of lungs in inspiration and expiration are found based on anatomical structures. Then, lung regions are segmented from the CT images by active contours. Next, the left and right lungs are separated using a sequence of morphological operations. Then, parenchyma variations in each lung are found as a relationship between inspiratory and expiratory states. Finally, a classifier is used to decide about the disease and its severity. A t-test is done to evaluate the results. Twelve patients with variable severity of COPD and twelve normal adults were included in this study. The proposed method may assist radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. © 2011 IEEE.

关键词： Pulmonary diseases

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