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Annual Conference of the IEEE Industrial Electronics Society

作者： Xiangyang Xing Alian Chen Weisheng Wang Chenghui Zhang Vahid Najmi School of Control Science and Engineering Shandong University Center for Power Electronics Systems The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University

ISBN: (纸本)9781479940318

The Z-source neutral point clamped (NPC) inverters can realize buck-boost energy conversion with all satisfying advantages of the three-level inverters. A significant problem related to this topology is the fluctuation of the neutral-point potential (NP). However, the previous modulation techniques for this topology cannot achieve the considerate stable voltage. In this paper, based on the analysis of the relationship among the shoot-through duty cycle and the NP voltage, the average NP current, switching frequency capacitor value, a new feed-forward compensator by modifying the shoot-through duty cycle which can improve to balance the NP voltage balancing is proposed. Meanwhile, in consideration of a low voltage gain caused by the NP voltage balance method, a new control method based on a maximum constant boost control method is proposed, which brings the benefits in both high voltage gain and low-frequency ripple. The considerate stable NP voltage and the high voltage gain have been proven in simulation and through experimental results from a prototype converter.

关键词： Z-source neutral point clamped (NPC) inverter High voltage gain Balance the neutral-point potential (NP) voltage

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Hybrid Systems with Memory: Modelling and Stability Analysis via Generalized Solutions

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IFAC Proceedings Volumes 2014年第3期47卷 6019-6024页

作者： Jun Liu Andrew R. Teel Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD United Kingdom Center for Control Dynamical Systems and Computation and Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106 USA

Hybrid systems with memory are dynamical systems exhibiting both hybrid and delay phenomena. We present a general modelling framework for such systems using hybrid functional inclusions, whose generalized solutions are defined on hybrid time domains and evolve in the phase space of hybrid memory arcs equipped with the graphical convergence topology. We prove a general existence result based on some basic conditions on the data of hybrid systems. We further establish sufficient conditions for the stability analysis of hybrid systems with memory using Lyapunov-Razumikhin (L-R) functions. We demonstrate the stability results on a general nonlinear system with switching dynamics and state jumps.

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An evolutionary artificial potential field algorithm for stable operation of a multi-robot system on domes

An evolutionary artificial potential field algorithm for sta...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Kourosh Naderi Khalil Taheri Hadi Moradi Majid Nili Ahmadabadi School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence University of Tehran Iran

In this paper, we propose a reasonable fast centralized to navigate a multi-robot system on domes. The robots, consisting of a leader and N-1 (N ≥ 2) followers, are connected to each other by N strings and make a ring around the dome. The leader uses the artificial potential field approach to plan a stable path toward its desired goal position while the other robots support it. To avoid getting into local minima we use genetic algorithm(GA) and multi-rapidly exploring random trees (multi-RRTs) before the robots get stuck into local minima. Our method guarantees the leader can reach its goal on the dome and all robots remain stable throughout the path. Finally, we have simulated the behavior of a 4-robot system on a spherical dome to show the effectiveness of the method.

关键词： Robots Genetic algorithms Multi-robot systems Force Maintenance engineering Educational institutions Stability analysis

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Efficient control synthesis for augmented finite transition systems with an application to switching protocols

Efficient control synthesis for augmented finite transition ...

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2014 American control Conference, ACC 2014

作者： Sun, Fei Ozay, Necmiye Wolff, Eric M. Liu, Jun Murray, Richard M. Information Security Center Beijing University of Posts and Telecommunications China Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109 United States Department of Control and Dynamical Systems California Institute of Technology Pasadena CA 91125 United States Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street Sheffield S1 3JD United Kingdom

ISBN: (纸本)9781479932726

Augmented finite transition systems generalize nondeterministic transition systems with additional liveness conditions. We propose efficient algorithms for synthesizing control protocols for augmented finite transition systems to satisfy high-level specifications expressed in a fragment of linear temporal logic (LTL). We then use these algorithms within a framework for switching protocol synthesis for discrete-time dynamical systems, where augmented finite transition systems are used for abstracting the underlying dynamics. We introduce a notion of minimality for abstractions of certain fidelity and show that such minimal abstractions can be exactly computed for switched affine systems. Additionally, based on this framework, we present a procedure for computing digitally implementable switching protocols for continuous-time systems. The effectiveness of the proposed framework is illustrated through two examples of temperature control for buildings. © 2014 American Automatic control Council.

关键词： Continuous time systems

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Support Vector Machine with Nonlinear-Kernel Optimization for Lateralization of Epileptogenic Hippocampus in MR Images

Support Vector Machine with Nonlinear-Kernel Optimization fo...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Mohammad-Parsa Hosseini Mohammad R. Nazem-Zadeh Fariborz Mahmoudi Hao Ying Hamid Soltanian-Zadeh Medical Image Analysis Lab. Radiology Department Henry Ford Health System Department of Electrical and Computer Engineering Wayne State University Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran

ISBN: (纸本)9781424479276

Surgical treatment is suggested for seizure control in medically intractable epilepsy patients. Detailed pre-surgical evaluation and lateralization using Magnetic Resonance Images (MRI) is expected to result in a successful surgical outcome. In this study, an optimized pattern recognition approach is proposed for lateralization of mesial Temporal Lobe Epilepsy (mTLE) patients using asymmetry of imaging indices of hippocampus. T1-weighted and Fluid-Attenuated Inversion Recovery (FLAIR) images of 76 symptomatic mTLE patients are considered. First, hippocampus is segmented using automatic and manual segmentation methods;then, volumetric and intensity features are extracted from the MR images. A nonlinear Support Vector Machine (SVM) with optimized Gaussian Radial Basis Function (GRBF) kernel is used to classify the imaging features. Using leave-one-out cross validation, this method results in a correct lateralization rate of 82%, a probability of detection for the left side of 0.90 (with false alarm probability of 0.04) and a probability of detection for the right side of 0.69 (with zero false alarm probability). The lateralization results are compared to linear SVM, multi-layer perceptron Artificial Neural Network (ANN), and volumetry and FLAIR asymmetry analysis. This lateralization method is suggested for pre-surgical evaluation using MRI before surgical treatment in mTLE patients. It achieves a more correct lateralization rate and fewer false positives.

关键词： Magnetic Resonance Imaging (MRI) Hippocampus Epilepsy Lateralization Support Vector Machine (SVM)

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Observer design for a class of nonlinear systems with long delay in output measurements: an LMI approach

Observer design for a class of nonlinear systems with long d...

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European control Conference (ECC)

作者： Alaleh Vafaei Mohammad J. Yazdanpanah The School of Electrical and Computer Engineering University of Tehran Tehran Iran The Control & Intelligent Processing Center of Excellence University of Tehran Tehran Iran

ISBN: (纸本)9781479947287

This paper proposes a new state observer for a class of nonlinear systems with non negligible time delays in the output and Lipschitz nonlinearity. The proposed observer is composed of a chain of observers each of which estimates the states in different time instants, while the last observer estimates the state in the present time. This observer,unlike the previously introduced chain-like observers, introduces similar structure for all of the observation algorithms, is applicable for both of the stable and unstable nonlinear systems and has no limit for the value of time delay. Conditions for stability of the observer are translated into linear matrix inequalities (LMIs) to obtain the observer gains. Simulation results demonstrate effectiveness of this observer for both of the stable and unstable systems.

关键词： Observers Nonlinear systems Linear matrix inequalities Delays Delay effects Stability analysis

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Transverse Flux Permanent Magnet Motor with Double-C Stator Hoops and Flux-Concentrated Rotor for In-Wheel Drive Electric Vehicle

Transverse Flux Permanent Magnet Motor with Double-C Stator ...

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IEEE Energy Conversion Congress and Exposition

作者： Zhou Jia Heyun Lin Hui Yang Chris Mi Department of Electrical and Computer Engineering University of Michigan Dearborn Dearborn MI 48128 USA Engineering Research Center for Motion Control of MOE Southeast University Nanjing 210096 China

ISBN: (纸本)9781479957774

This paper proposes a novel transverse flux permanent magnet motor (TFPMM) with double-C stator hoops. The proposed TFPMM carries significantly increased power density due to higher coefficient of utilization of the volume compared with the traditional double-side counterparts. The topology, principle and parametric calculation of the TFPMM are described elaborately. The magnetic field and characteristics analysis are conducted by three-dimensional finite element method (3D FEM) including flux density, EMF and winding inductance, and cogging torque are obtained to verify the feasibility of proposed TFPMM design. The mechanism of cogging torque of the proposed double-C stator hoops TFPMM is also analyzed. The results of transient simulation of power density well align with the theoretical analysis, which confirm that the power density is significantly increased due to its higher volumetric utilization ratio.

关键词： double-C stator finite element method flux-concentrated transverse flux permanent magnet motor (TFPMM)

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RFID-Augmentation for Improving Long-term Pose Accuracy of an Indoor Navigating Robot

RFID-Augmentation for Improving Long-term Pose Accuracy of a...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Daniel Opoku Abdollah Homaifar Edward Tunstel Autonomous Control and Information Technology (ACIT) Center Department of Electrical and Computer Engineering North Carolina Agricultural and Technical State University ACIT Center Department of Electrical and Computer Engineering North Carolina A&T State University Johns Hopkins University Applied Physics Laboratory

ISBN: (纸本)9781479938414

This paper presents a Radio Frequency based system for handling long-term drift of pose estimates for a robot performing odometer-based navigation in an indoor environment. The indoor environment is augmented with RFID tags and their associated door-markers to form a partially structured environment. To enhance the performance of the odometry, we adopted a Least Squares calibration approach to mitigate the effect of the systematic errors. The residual errors, mainly non-systematic, are handled by intermittent resetting of the robot's pose based on the global positioning references designed with the RFID tags and their associated door-markers. The results reveal that the long-term confidence in the estimated position improves about six times with this approach.

关键词： Mathematical model Equations Estimation Calibration Mobile robots Wheels

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The neuviz data visualization tool for visualizing internet-measurements data

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Mondo Digitale 2014年第49期13卷

作者： Futia, Giuseppe Zimuel, Enrico Basso, Simone De Martin, Juan Carlos Nexa Center Italy R and D department of Zend Technologies University of Amsterdam Brown University United States Nexa Center Department of Control and Computer Engineering Italy Nexa Center Institute of Electrical and Electronic Engineers Italy

In this paper we present NeuViz, a data processing and visualization architecture for network measurement experiments. NeuViz has been tailored to work on the data produced by Neubot (Net Neutrality Bot), an Internet bot that performs periodic, active network performance tests. We show that NeuViz is an effective tool to navigate Neubot data to identify cases (to be investigated with more specific network tests) in which a protocol seems discriminated. Also, we suggest how the information provided by the NeuViz Web API can help to automatically detect cases in which a protocol seems discriminated, to raise warnings or trigger more specific tests.

关键词： Network performance

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A clustering based multiobjective evolutionary algorithm

A clustering based multiobjective evolutionary algorithm

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Congress on Evolutionary Computation

作者： Hu Zhang Shenmin Song Aimin Zhou Xiao-Zhi Gao Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China Department of Computer Science and Technology East China Normal University Shanghai China Department of Electrical Engineering and Automation School of Electrical Engineering Aalto Finland

In this paper, we propose a clustering based multiobjective evolutionary algorithm (CLUMOEA) to deal with the multiobjective optimization problems with irregular Pareto front shapes. CLUMOEA uses a k-means clustering method to discover the population structure by partitioning the solutions into several clusters, and it only allows the solutions in the same cluster to do the reproduction. To reduce the computational cost and balance the exploration and exploitation, the clustering process and evolutionary process are integrated together and they are performed simultaneously. In addition to the clustering, CLUMOEA also uses a distance tournament selection to choose the more similar mating solutions to accelerate the convergence. Besides, a cosine nondominated selection method considering the location and distance information of the solutions are further presented to construct the final population with good diversity. The experimental results show that, compared with some state-of-the-art algorithms, CLUMOEA has significant advantages on dealing with the given test problems with irregular Pareto front shapes.

关键词： Sociology Statistics Shape Convergence Vectors Evolutionary computation Optimization

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