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作者： Frost, Susan A. Balas, Mark J. Wright, Alan D. Intelligent Systems Division NASA Ames Research Center M/S 269-1 Moffett Field CA 95034 United States Department of Electrical and Computer Engineering University of Wyoming 1000 E. University Avenue Laramie WY 82071 United States National Renewable Energy Laboratory M/S 3811 1617 Cole Blvd. Golden CO 80401 United States

ISBN: (纸本)9781563479694

Many challenges exist for the efficient and safe operation of wind turbines due to the difficulty in creating accurate models of their dynamic characteristics and the turbulent conditions in which they operate. A promising new area of wind turbine research is the application of adaptive control techniques, which are well suited to problems where the plant model is not well known and the plant operating conditions are unpredictable. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility scale, variable-speed horizontal axis wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed and reject step disturbances, which model the uniform wind disturbance across the wind turbine rotor. The control objective is accomplished by collectively pitching the turbine blades. To improve controller performance, we use an extension of the Direct Model Reference Adaptive control (DMRAC) approach to regulate turbine rotational speed and to accommodate step disturbances. The turbine simulation models the controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine that has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved generator speed regulation in Region 3 when compared with the baseline PI pitch controller. The adaptive controller demonstrated robustness to modeling errors and changes in system parameters.

关键词： Turbomachine blades

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Properties of the Parametric Lyapunov Equation Based Low Gain Design with Applications in Stabilization of Time-Delay Systems

Properties of the Parametric Lyapunov Equation Based Low Gai...

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2009 American control Conference (ACC 2009)

作者： Bin Zhou Zongli Lin Guangren Duan Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin 150001 PR China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 U.S.A.

ISBN: (纸本)9781424445233

This paper studies some properties of the recently developed parametric Lyapunov equation based low gain feedback design method. As applications of these new properties, alternative and simpler solutions are proposed to the (global) stabilization problem for a class of linear systems with input delay and the semi-global stabilization problem when the systems are in addition subject to actuator saturation. Besides the simplicity in their construction, the new solutions can also be easily scheduled online to achieve global result in the presence of input saturation.

关键词： Linear systems control systems Delay systems Hydraulic actuators Delay estimation Riccati equations Nonlinear equations Lyapunov method Output feedback Design methodology

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Fractional-order memristive systems

Fractional-order memristive systems

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Ivo Petráš YangQuan Chen Calvin Coopmans Institute of Control and Informatization of Production Processes BERG Faculty Technical University of Košice Kosice Slovakia Center for Self-Organizing and Intelligent Systems (CSOIS) Electrical and Computer Engineering Department Utah State University Logan UT USA

This paper deals with the concept of (integer-order) memristive systems, which are generalized to non-integer order case using fractional calculus. We consider the memory effect of the fractional inductor (fractductor), fractional capacitor and fractional memristor. We also show that the memory effect of such devices can be also used for an analogue implementation of the fractional-order operator, namely fractional-order integral and fractional-order derivatives. This kind of operator is useful for realization of the fractional-order controllers. We present theoretical description of such implementation and we proposed the practical realization and did some simulations and experimental measurements as well.

关键词： Memristors Fractional calculus Inductors Capacitors Voltage Circuit simulation Resistors Temperature Phase change memory control systems

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Multi-area integrated E/MEG and fMRI modeling

Multi-area integrated E/MEG and fMRI modeling

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Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Babajani-Feremi, Abbas Bowyer, Susan Moran, John Elisevich, Kost Podell, Kenneth Soltanian-Zadeh, Hamid Image Analysis Lab. Radiology Department Henry Ford Hospital Detroit MI 48202 United States Neuromagnetism Lab. Neurology Department Henry Ford Hospital Detroit MI 48202 United States Department of Neurology Henry Ford Hospital Detroit MI 48202 United States Division of Neuropsychology and Sports Concussion Safety Program Henry Ford Hospital Detroit MI 48202 United States Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran 14395-515 Iran

ISBN: (纸本)9780819475138

Functional magnetic resonance imaging (fMRI) has complementary spatiotemporal resolution compared to Electroencephalography (EEG) as well as Magnetoencephalography (MEG). Thus, their integrated analysis should improve the overall resolution. To integrate analysis of E/MEG and fMRI, we extend our previously proposed integrated E/MEG and fMRI neural mass model to a multi-area model by defining two types of connections: the Short-Range Connections (SRCs) between minicolumns within the areas and Long-Range Connections (LRCs) between inter-areas minicolumns. The nonlinear input/output relationship in the proposed model is derived from the state space representation of the multi-area model. The E/MEG signals are originated from the overall synaptic activities of the pyramidal cells of all minicolumns and can be calculated using the lead field matrix (i.e., forward electromagnetic model). The fMRI signal is extracted from the proposed integrated model by calculating the overall neural activities in the areas and using it as the input of the extended balloon model (EBM). Using the simulation results, the capabilities of the proposed model to generate E/MEG and fMRI signals is shown. In addition, changes in the dynamics of the model to variations of its parameters were evaluated and lead us to the appropriate ranges for the parameters. In conclusion, this work proposes an effective method to integrate E/MEG and fMRI for the more effective use of these techniques in functional neuroimaging. © 2009 SPIE.

关键词： Electroencephalography

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NEURO-FUZZY BASED FAULT DIAGNOSIS OF A STEAM GENERATOR

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IFAC Proceedings Volumes 2009年第8期42卷 1180-1185页

作者： Roozbeh Razavi-Far Hadi Davilu Vasile Palade Caro Lucas Department of Nuclear Engineering Amirkabir University of Technology P.O. Box 15875-4413 Tehran Iran (Tel:+98-***) Computing Laboratory Oxford University Wolfson Building Parks Road Oxford OX1 3QD UK Center of Excellence on Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran P.O. Box 14395-1515 Tehran Iran

This paper focuses on the development and application of a Neuro-Fuzzy (NF) networks-based scheme for Fault Detection and Isolation (FDI) in a U-tube Steam Generator (UTSG). First, a NF network is trained with data collected from a full scale UTSG simulator, and residuals are generated for fault detection. To identify the UTSG, a Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained using the Locally Linear Model Tree (LOLIMOT) algorithm which is an incremental tree structure algorithm. Then, an evolutionary algorithm is used to train a Mamdani type NF network to classify the residuals. The residuals are analyzed by using this NF classifier for fault isolation purposes.

关键词： Fault Diagnosis Neuro-Fuzzy Networks Locally Linear Neuro Fuzzy Model Locally Linear Model Tree Steam Generator

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engineering research and education in power system voltage stability enhancement

Engineering research and education in power system voltage s...

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IEEE General Meeting Power& Energy Society

作者： James A. Momoh C. Trevor Gaunt Sunny Onohaebi Center of Energy Systems and Control (CESaC) Howard University College of Medicine Washington D.C. DC USA University of Cape Town South Africa Head of the Department of Electrical Electronics and Computer Engineering (EECE) University of Benin Benin Nigeria

Research in areas of voltage stability monitoring, assessment and control of power systems is an ongoing international activity at Howard University. The research engineering development involves real-time system parameters to compute a Voltage Stability Index (VSI) and margin, and provide advanced control schemes to mitigate the Voltage/Var problems. The strategy is based on the use of advanced measurement technologies to lay the foundations for applications of advanced optimization methods such as hybrid Fuzzy Logic Adaptive Dynamic Programming based controllers for VSI control and coordination. Thus far, the related international activities of our research and education work involve Howard University, University of Benin (Uniben) in Nigeria, and University of Cape Town (UCT) in South Africa (SA). Our research has developed understanding of real-time VSI using but not limited to practical power utility test data system models from both African countries.

关键词： Power system stability Power engineering and energy Power engineering education Systems engineering education Power system control Voltage control control systems Real time systems control engineering education Monitoring

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MABEL, A New Robotic Bipedal Walker and Runner

MABEL, A New Robotic Bipedal Walker and Runner

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2009 American control Conference (ACC 2009)

作者： J.W. Grizzle Jonathan Hurst Benjamin Morris Hae-Won Park Koushil Sreenath Control Systems Laboratory Electrical Engineering and Computer Science Department University of Michigan Ann Arbor MI 48109-2122 USA Mechanical Engineering 204 Rogers Hall Oregon State University Corvallis OR 97331 USA Eaton Innovation Center 26201 Northwestern Highway Southfield MI 48076 USA Mechanical Engineering Department University of Michigan Ann Arbor MI 48109-2125 USA

ISBN: (纸本)9781424445233

This paper introduces MABEL, a new platform for the study of bipedal locomotion in robots. One of the purposes of building the mechanism is to explore a novel powertrain design that incorporates compliance, with the objective of improving the power efficiency of the robot, both in steady state operation and in responding to disturbances. A second purpose is to inspire the development of new feedback control algorithms for running on level surfaces and walking on rough terrain. A third motivation for building the robot is science and technology outreach;indeed, it is already included in tours when K-through-12 students visit the College of engineering at the University of Michigan. MABEL is currently walking at 1.1 m/s on a level surface, and a related monopod at Carnegie Mellon is hopping well, establishing that the testbed has the potential to realize its many objectives.

关键词： Alfven surface Robot stability operations runners walking dynamic efficiency Walkers colleges Rough terrain Buildings construction robot

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Particle filtering of point processes observation with application on the modeling of visual cortex neural spiking activity

Particle filtering of point processes observation with appli...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： Yousef Salimpour Hamid Soltanian-Zadeh Computational Neuroscience in School of Cognitive Sciences Institute of Studies in Fundamental Sciences Tehran Iran Department of Radiology Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence(CIPCE) Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Recording of neural response to specific stimulus in a repeated trial is very common in neuroscience protocol. The perstimulus time histogram (PSTH) is a standard tool for analysis of neural response. However it could not capture the non-deterministic properties of the neuron especially in higher level cortical area such as inferior temporal cortex. The stochastic state point process filter theory is used for the estimation of the conditional intensity of the point process observation as a time varying firing rate and the particle filter is used to numerically estimate this density in time. The particle filters were applied to the results of the point process observation for compensating the Gaussian assumption. The results of applying point process modeling on a real data from inferior temporal cortex of macaque monkey indicates that, based on the assessment of goodness-of-fit, the neural spiking activity and biophysical property of neuron could be captured more accurately in compare to conventional methods.

关键词： Filtering Brain modeling Neurons Stochastic processes State estimation Particle filters Histograms Mathematical model Neural engineering Neuroscience

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Droop based control of parallel-connected single-phase inverters in D-Q rotating frame

Droop based control of parallel-connected single-phase inver...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Saeed Golestan Mahmood Joorabian Hasan Rastegar Arman Roshan Josep M. Guerrero Faculty of Electrical Engineering Amirkabir University of Technology슠 Tehran Iran Shahid Chamran University Ahvaz Iran Center of Power Electronics Systems Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Automatic Control Systems Computer Engineering Universitat Poliltècnica de Catalunya Barcelona Spain

ISBN: (纸本)9781424435067

In this paper, control of parallel single-phase inverters in direct-quadrature(DQ) rotating frame based on droop method is proposed. For each inverter, a secondary orthogonal imaginary circuit is created to provide the second phase required for the transformation; thus a DQ model of the inverter is obtained. The DQ transformation provides a time-invariant model of the inverter which makes the control design similar to that of dc-dc converters. The recognition of this analogy is important in that all of advanced dc-dc converters control techniques that have been previously developed can be applied to the control parallel inverters. The controller then is designed in DQ frame. Theoretically, infinite loop gain can be achieved in DQ rotating frame resulting in the elimination of the steady state error at the fundamental frequency of the inverter. The output impedance of the inverters is also considered, to ensure the decoupling between active and reactive power control using droop method. Simulation results are provided to prove the concept.

关键词： Inverters Communication system control Circuits DC-DC power converters Uninterruptible power systems Power system reliability control systems control design Frequency Reactive power control

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Protection ellipsoids for stability analysis of feedforward neural-net controllers

Protection ellipsoids for stability analysis of feedforward ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Abraham K. Ishihara Shahar Ben-Menahem Nhan Nguyen Department of Electrical and Computer Engineering Carnegie Mellon University Silicon Valley NASA Research Park Moffett Field CA USA Department of Physics University of Stanford Stanford CA USA Avago Technologies Inc. San Jose CA USA Intelligent Systems Division NASA Ames Research Center Moffett Field CA USA

In this paper, we consider a feedforward neural network for the control of a class of multi-input, multi-output nonlinear systems. While feedforward neural networks offer a simple and appealing approach to enhance the trajectory tracking performance of the closed loop system, stability analysis is often more difficult than the conventional implementation of a neural network embedded within the feedback path. We present a stability theorem which guarantees that the closed loop system is uniformly bounded. We derive conditions on the feedback gain matrices that guarantee this bound. Additionally, we outline a generalization to the non-symmetric case.

关键词： Protection Ellipsoids Stability analysis Neural networks Feedforward neural networks Closed loop systems Neurofeedback Nonlinear control systems control systems Nonlinear systems

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