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A multi-step Gaussian filtering approach to reduce the effect of non-Gaussian distribution in aerial localization of an RF source in NLOS condition

A multi-step Gaussian filtering approach to reduce the effec...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Seyyed M. Mehdi Dehghan Hadi Moradi Advanced Robotics and Intelligent Systems laboratory Control and Intelligent Processing Center School of Electrical and Computer Engineering University of Tehran Tehran Iran

The hybrid localization using Angle of Arrival (AOA) and Received Strength Signal Indicator (RSSI) of an RF source, such as a cell phone in a search and rescue mission, with unknown power and None Line Of Sight (NLOS) condition have been proven to be advantageous compared to using each method separately. The hybrid approach has been proposed to benefit from both RSSI and AOA measurements. In this paper, the initial hybrid method, which was implemented using particle filters due to the multi-modal/non-Gaussian nature of localization in NLOS condition, has been replaced by a multi-step Gaussian filtering approach which provides nearly similar accuracy with better performance. The proposed method has been implemented using extended Kalman filter and Unscented Kalman filter. The simulation results show that the multi-step Gaussian filtering is comparable to particle filter in all cases with better performance. For further evaluation, the effects of uncertainty in the propagation parameters have been studied to show the robustness of each filter to these uncertainties.

关键词： Shadow mapping Atmospheric measurements Particle measurements Scattering Measurement uncertainty Particle filters Equations

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Safe joint mechanism using passive compliance method for collision safety

Safe joint mechanism using passive compliance method for col...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Omid Zebardast Hadi Moradi Farshid Najafi Department of mechatronics engineering University of Tehran Iran Control and Intelligent Processing Center School of Electrical & Computer Engineering University of Tehran Tehran Iran Department of Mechanical Engineering University of Tehran Tehran Iran

In this paper, the design and implementation of a novel passive safe joint is reported. This safe joint is designed for applications, such as an air hockey playing robot playing against a human, in which the force applied by the linkage should be kept below a certain threshold. The proposed mechanism benefits from the compliance of two ramps controlled by the nonlinear behavior of a spring. The passivity of the design, the small footprint, the low cost of production, and the ability to rotate 360 degrees are the main advantages of this design. The mechanism has been designed, evaluated, implemented and tested showing its effectiveness. Finally it has been incorporated in an air hockey robot showing its capability in action.

关键词： Robots Educational institutions Indexes Force

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Automatic dental CT image segmentation using mean shift algorithm

Automatic dental CT image segmentation using mean shift algo...

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Iranian Machine Vision and Image Processing (MVIP)

作者： Parinaz Mortaheb Mehdi Rezaeian Hamid Soltanian-Zadeh Electrical and Computer Engineering Department Yazd University Yazd Iran Control and Intelligent Processing Center of Excellence (CIPCE) University of Tehran Tehran Iran

Identifying the structure and arrangement of the teeth is one of the dentists' requirements for performing various procedures such as diagnosing abnormalities, dental implant and orthodontic planning. In this regard, robust segmentation of dental computerized Tomography (CT) images is required. However, dental CT images present some major challenges for the segmentation that make it difficult process. In this research, we propose a multi-step approach for automatic segmentation of the teeth in dental CT images. The main steps of this method are presented as follows: 1-Primary segmentation to classify bony tissues from nonbony tissues. 2-Separating the general region of the teeth structure from the other bony structures and arc curve fitting in the region. 3-Individual tooth region detection. 4-Final segmentation using mean shift algorithm by defining a new feature space. The proposed algorithm has been applied to several Cone Beam Computed Tomography (CBCT) data sets and quality assessment metrics are used to evaluate the performance of the algorithm. The evaluation indicates that the accuracy of proposed method is more than 97 percent. Moreover, we compared the proposed method with thresholding, watershed, level set and active contour methods and our method shows an improvement in compare with other techniques.

关键词： Teeth Image segmentation Computed tomography Dentistry Vectors Level set Three-dimensional displays

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Consensus of High-order Multi-agent Systems with Input and Communication Delays-Output Feedback Case

Consensus of High-order Multi-agent Systems with Input and C...

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第三十二届中国控制会议

作者： Bin Zhou Zongli Lin Center for Control Theory and Guidance Technology Harbin Institute of Technology Charles L. Brown Department of Electrical and Computer Engineering University of Virginia

ISBN: (纸本)9781479900305

We study in this paper the consensus problem for multi-agent systems with agents characterized by high-order linear systems with time delays in both the communication network and inputs. Provided that the open-loop dynamics of the agents is not exponentially unstable, but may be polynomially unstable, and the communication topology contains a directed spanning tree, a truncated predictor feedback approach is established to solve the consensus problem. It is shown that, if the delays are constant and exactly known, the consensus problems can be solved by observer based output feedback protocols for arbitrarily large yet bounded delays. If it is further assumed that the open-loop dynamics of the agents only contains zero eigenvalues, the delays are allowed to be time-varying and unknown.

关键词： Consensus high-order multi-agent systems time delays truncated predictor feedback Output feedback

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Model Free Predictive control for a Nonlinear Biological System with Intelligent Optimization Approach

Model Free Predictive Control for a Nonlinear Biological Sys...

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第25届中国控制与决策会议

作者： Mojtaba Zaare Mehrjerdi Ghassem Amoabediny Behzad Moshiri Arman Ashktorab Babak Nadjar Araabi Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Faculty of Engineering University of Tehran Research Center for New Technologies in Life Science Engineering University of Tehran Department of Life Science Engineering Faculty of New Technologies University of Tehran Department of Chemical Engineering Faculty of Engineering University of Tehran

ISBN: (纸本)9781467355339

Today the importance of life science and its related processes are undeniable. Modeling and control of these kind of processes are too complicate because of existence of delay in growth and also nonlinear behavior of micro-organisms. Model predictive control is one of the most popular advanced controlling strategies in this industry, however its dependence on accurate model for predicting future input and output values is limitating. If there is a way that could predict the future values of the process properly, it is possible to overcome to the existing challenges. In this paper we design a model free predictive controller by using a trained recurrent neural network as a predictor for prediction stage at MPC and using GA for solving the associated optimization problem that result the optimal control signal sequence.

关键词： NNMPC GA Biological System Aerated Flask

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Model Predictive control with Sequential Linearization Approach for a Nonlinear Time Varying Biological System

Model Predictive Control with Sequential Linearization Appro...

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第25届中国控制与决策会议

作者： Mojtaba Zaare Mehrjerdi Behzad Moshiri Ghassem Amoabediny Arman Ashktorab Babak Nadjar Araabi Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Faculty of Engineering University of Tehran Research Center for New Technologies in Life Science Engineering University of Tehran Department of Life Science Engineering Faculty of New Technologies University of Tehran Department of Chemical Engineering Faculty of Engineering University of Tehran

ISBN: (纸本)9781467355339

As life science progress and its consequences provide human life necessities, controlling these kinds of processes has recently become very important. Unfortunately because of including delay and nonlinear behavior of micro-organisms these processes have nonlinear time varying model and so controlling them is too complicated. These nonlinear dynamics are too slow and so it is possible to linearize the model step by step and apply control signal to the local linearized models. In this paper we design a model predictive controller for each linearized model at time unit and as a result a nonlinear time varying system has been controlled properly. As these localized models are open loop unstable, we have to use close loop paradigm also due to its numerically robustness. Finally result has validated with experimental values and reliability of this approach has been exposed.

关键词： MPC, Sequential Linearization, Biological System control, Aerated Flask

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Automatic sleep stage classification GUI with a portable EEG device

Automatic sleep stage classification GUI with a portable EEG...

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15th International Conference on Human-computer Interaction, HCI International 2013

作者： Huang, Chih-Sheng Lin, Chun-Ling Ko, Li-Wei Wang, Yu-Kai Liang, Jyun-Wei Lin, Chin-Teng Brain Research Center University System of Taiwan Hsinchu Taiwan Institute of Electrical Control Engineering National Chiao-Tung University Hsinchu Taiwan Department of Biological Science and Technology National Chiao-Tung University Hsinchu Taiwan Department of Computer Science National Chiao-Tung University Hsinchu Taiwan

ISBN: (纸本)9783642394720

In this study, a developed automatic sleep stage classification system with a portable EEG recording device, (Mindo-4s) is implemented by JAVA-based sleep graphical user interface (GUI) in android platform. First, the parameters of the developed sleep stage classification system, including extracting effective sleep features and a hierarchical classification structure consisting of preliminary wake detection rule, adaptive adjustment scheme, and support vector machine, were trained by our existing sleep database, which collected using polysomnogram (PSG), in MATLAB program. Finally, this classification system would be reedited by JAVA language, and the corresponding JAVA-based sleep GUI software was working in android platform and Mindo-4s. The connection between JAVA-based sleep GUI software and the portable Mindo-4s was through Bluetooth communication. The performance of this JAVA-based sleep GUI can reach 72.43% average accuracy comparing to the result from manual scoring. This JAVA-based sleep GUI can on-line display, record and analyze the forehead EEG signals simultaneously. After sleep, the user can received a complete sleep report, including sleep efficiency, sleep stage distribution, from JAVA-based sleep GUI. Thus, this system can provide a preliminary result in sleep quality estimation, and help the sleep doctor to decide someone needs to have a complete PSG testing in hospital. Using this system is more convenient for long-term and home-based daily caring than traditional PSG measurement. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Graphical user interfaces

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Corrigendum: A limit formula for the quantum fidelity (2013 J. Phys. A: Math. Theor. 46 025304)

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Journal of Physics A: Mathematical and Theoretical 2014年第32期47卷

作者： Gaetana Spedalieri Christian Weedbrook Stefano Pirandola Department of Computer Science University of York York YO10 5GH UK Center for Quantum Information and Quantum Control Department of Electrical and Computer Engineering and Department of Physics University of Toronto Toronto M5S 3G4 Canada

The full text of this article is available in the PDF provided.

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Solutions to finite horizon cost problems using actor-critic reinforcement learning

Solutions to finite horizon cost problems using actor-critic...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ivo Grondman Hao Xu Sarangapani Jagannathan Robert Babuška Delft Center for Systems and Control Delft University of Technology Delft The Netherlands Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla USA

Actor-critic reinforcement learning algorithms have shown to be a successful tool in learning the optimal control for a range of (repetitive) tasks on systems with (partially) unknown dynamics, which may or may not be nonlinear. Most of the reinforcement learning literature published up to this point only deals with modeling the task at hand as a Markov decision process with an infinite horizon cost function. In practice, however, it is sometimes desired to have a solution for the case where the cost function is defined over a finite horizon, which means that the optimal control problem will be time-varying and thus harder to solve. This paper adapts two previously introduced actor-critic algorithms from the infinite horizon setting to the finite horizon setting and applies them to learning a task on a nonlinear system, without needing any assumptions or knowledge about the system dynamics, using radial basis function networks. Simulations on a typical nonlinear motion control problem are carried out, showing that actor-critic algorithms are capable of solving the difficult problem of time-varying optimal control. Moreover, the benefit of using a model learning technique is shown.

关键词： Mathematical model Equations Optimal control Learning (artificial intelligence) Approximation algorithms Heuristic algorithms Markov processes

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A driver face monitoring system for fatigue and distraction detection

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International Journal of Vehicular Technology 2013年第1期2013卷

作者： Sigari, Mohamad-Hoseyn Fathy, Mahmood Soryani, Mohsen Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran 14399 Iran Computer Engineering Department Iran University of Science and Technology Tehran 16846 Iran

Driver face monitoring system is a real-time system that can detect driver fatigue and distraction using machine vision approaches. In this paper, a new approach is introduced for driver hypovigilance (fatigue and distraction) detection based on the symptoms related to face and eye regions. In this method, face template matching and horizontal projection of top-half segment of face image are used to extract hypovigilance symptoms from face and eye, respectively. Head rotation is a symptom to detect distraction that is extracted from face region. The extracted symptoms from eye region are (1) percentage of eye closure, (2) eyelid distance changes with respect to the normal eyelid distance, and (3) eye closure rate. The first and second symptoms related to eye region are used for fatigue detection;the last one is used for distraction detection. In the proposed system, a fuzzy expert system combines the symptoms to estimate level of driver hypo-vigilance. There are three main contributions in the introduced method: (1) simple and efficient head rotation detection based on face template matching, (2) adaptive symptom extraction from eye region without explicit eye detection, and (3) normalizing and personalizing the extracted symptoms using a short training phase. These three contributions lead to develop an adaptive driver eye/face monitoring. Experiments show that the proposed system is relatively efficient for estimating the driver fatigue and distraction. © 2013 Mohamad-Hoseyn Sigari et al.

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