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2011 IEEE International Conference on Robotics and Automation, ICRA 2011

作者： Fentanes, Jaime Pulido Zalama, Eduardo Gómez-García-Bermejo, Jaime CARTIF Foundation Spain Universidad de Valladolid Spain CARTIF Centro Tecnológico Dep. Of Robotics and Computer Vision Boecillo Valladolid Spain Dep. Of Systems Engineering and Automatic Control Industrial Engineering School Spain

ISBN: (纸本)9781612843865

In this paper, an algorithm for the reconstruction of an outdoor environment using a mobile robot is presented. The focus of this algorithm is making the mapping process efficient by capturing the greatest amount of information on every scan, ensuring at the same time that the overall quality of the resulting 3D model of the environment complies with the specified standards. With respect to existing approaches, the proposed approach is an innovation since there are very few information based methods for outdoor reconstruction that use resulting model quality and trajectory cost estimation as criteria for view planning. © 2011 IEEE.

关键词： Mobile robots

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An Object Frame Knowledge Representation Approach for Fault Diagnosis Expert System

An Object Frame Knowledge Representation Approach for Fault ...

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2011 International Conference on Future computer Sciences and Application（ICFCSA 2011）

作者： Bailin Liu Mingye Duan Gang Zhao School of Computer Science and Engineering Xi'an Technological University North Automatic Control Technique Institute

Knowledge quality and usability is core to a fault diagnosis *** knowledge technique has been used to represent knowledge in many information and expert *** simplify the complexity of knowledge representation in fault diagnosis expert system,a novel object-frame knowledge representation approach based on hierarchical model was *** this approach,domain specific knowledge is expressed by combinations of *** Object-frame is composed by relevant state-object,test-object and rule-object or *** rules are used to connect relevant objects' *** features of object-frame and inference algorithm are ***-frame based knowledge items are stored in SQL database,inference engine performs the inference operation of knowledge using forward chaining strategy,implements reasoning,finds the cause of faults and gives repair suggestion driven by test *** interpretation completes the task of explanation,which improved the clarity of *** advantage of this method is that we do not need knowledge representation language *** results show that the method proposed is effective,which improved the fault diagnosis and maintenance for a meteorological vehicle system.

关键词： Fault Diagnosis Expert System Hierarchical Model Object-Frame Knowledge Representation Inference Engine

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Seeded faults and their locations design using bayes formula and program logic in software testing

Seeded faults and their locations design using bayes formula...

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6th International Conference on Evaluation of Novel Approaches to Software engineering, ENASE 2011

作者： Lina, Wang Jie, Tian Bo, Li Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing Aerospace Automatic Control Institute Beijing China Beijing Command College CPAPF Beijing China

ISBN: (纸本)9789898425577

Focusing on three questions "what faults to seed", "how to seed faults more effectively" and "how to select the seeded fault locations", the methods of fault seeding are studied. Aiming at procedural language source code, a fault classification scheme is presented. Referring to Howden's fault classification scheme, and based on the occurrence causes and manifestations of software faults, a hierarchy of fault classes is designed. The faults are categorized as assignment faults, control flow faults or runtime environment faults. Then they are further classified by degrees, respectively. 96 categories are included in all. According to this classification, a statistical method based on Bayes formula is designed to determine the manifestations of seeded faults. A logical method based on the logical relation between control flow and data flow of program is presented to set seeded locations. And the concrete seeding process is introduced. Finally, the methods are verified by a case.

关键词： Software testing

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The implementation of radar signal simulator

The implementation of radar signal simulator

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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Fuyang Zhang Jun Wang Yuxian Zhang Pei Wang School of Electronic and Information Engineering Beihang University Beijing China Automatic Control and Computer Simulation Liaoning China Troops

ISBN: (纸本)9781612847016

This article describes a variety of FPGA-based radar signal generator. This system is connected to the host, binding data from the software interface, through the PCI bus transfer stored in the system. Within the FPGA to achieve DDS signal generator, and finally through the digital-analog converter output. Finally, the system resource utilization and the actual results are given.

关键词： Field programmable gate arrays SDRAM Frequency control Radar Clocks Signal generators

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An Object Frame Knowledge Representation Approach for Fault Diagnosis Expert System

An Object Frame Knowledge Representation Approach for Fault ...

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International Conference on Future computer Sciences and Application (ICFCSA)

作者： Bailin Liu Mingye Duan Gang Zhao School of Computer Science and Engineering Xi'an Technological University Xi'an China North Automatic Control Technique Institute Taiyuan China

Knowledge quality and usability is core to a fault diagnosis system. Frame knowledge technique has been used to represent knowledge in many information and expert systems. To simplify the complexity of knowledge representation in fault diagnosis expert system, a novel object-frame knowledge representation approach based on hierarchical model was proposed. In this approach, domain specific knowledge is expressed by combinations of object-frames. An Object-frame is composed by relevant state-object, test-object and rule-object or repair-object. Production rules are used to connect relevant objects' states. General features of object-frame and inference algorithm are introduced. Object-frame based knowledge items are stored in SQL database, inference engine performs the inference operation of knowledge using forward chaining strategy, implements reasoning, finds the cause of faults and gives repair suggestion driven by test data. Inference interpretation completes the task of explanation, which improved the clarity of reasoning. The advantage of this method is that we do not need knowledge representation language support. Experimental results show that the method proposed is effective, which improved the fault diagnosis and maintenance for a meteorological vehicle system.

关键词： Fault diagnosis Knowledge representation Expert systems Maintenance engineering Cognition Engines

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Backstepping control of uncertain strict-feedback system based on time-scale separation

Backstepping control of uncertain strict-feedback system bas...

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International Conference on control, Instrumentation, and Automation

作者： Navid Noroozi Alireza Khayatian Tianshi Chen School of Electrical and Computer Engineering Shiraz University Shiraz Iran Automatic Control Division Electrical Engineering Department Linköping University Linkoping Sweden

In this paper, a state-feedback strategies based on time-scale separation technique for a class of strict-feedback systems in the presence of unstructured uncertainties is proposed which recovers the state trajectories of a nominal control design (without uncertainties) in the presence of unmatched uncertain nonlinearities. The performance of the feedback control scheme is evaluated by simulating state-feedback control for an uncertain strict-feedback system.

关键词： Instruments Automation

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Sensorless Speed control With MRAS for Induction Motor Drive

Sensorless Speed Control With MRAS for Induction Motor Drive

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International Conference on Electrical Machines

作者： Y. Agrebi Zorgani Y. Koubaa M. Boussak Laboratory of Sciences and Techniques of Automatic control & computer engineering (Lab-STA) National School of Engineering of Sfax University of Sfax-Postal Box 1173 3038 Sfax Tunisia the Laboratoire des Sciences de l'Information et des Systèmes (LSIS) UMR CNRS 7296 - Ecole Centrale Marseille (ECM) - 38 rue Joliot Curie Technop?le de Chateau Gombert 13451 Marseille Cedex 20 France

ISBN: (纸本)9781467301435

Usually In the speed sensorless of the induction motor, the machine parameters (especially rotor resistance Rr) have a strong influence on the speed estimation. This paper presents simultaneous estimation of speed and rotor resistance in sensorless ISFOC induction Motor drive based on a Model Reference System (MRAS). The MRAS has been formed to estimate the rotor speed and the rotor resistance which are tuned to obtain high-performance ISFOC induction motor drive. The error between the reference and adjustable models, developed in stationary stator reference frame, is used to drive a suitable adaptation mechanism that generates the estimate wr and Rr from measured terminal voltages and currents. The proposed algorithm has been tested by numerical simulation, showing the capability of driving active load and stability is preserved. Experimental results for the simultaneous estimation are presented in order to validate the effectiveness of the proposed scheme. The control algorithm has been implemented using a digital signal processor based on dSPACE DS1104.

关键词： Induction motor drive indirect stator field oriented control (ISFOC) model reference adaptive system (MRAS) rotor speed estimation rotor resistance estimation

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Dynamic cloning based Immune Network algorithm for multi-modal optimization

Dynamic cloning based Immune Network algorithm for multi-mod...

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International Conference on Natural Computation (ICNC)

作者： Xu-hua Shi Yu-guang Zhu Research Institute of Electric Automatic Control NingBo University China School of Computer & Information Engineering Changzhou Institute of Technology JiangSu China

In this paper, a novel multi-modal optimization algorithm, namely Dcopt-aiNet is proposed, which is based on biological immune network mechanism for global numerical optimization. Different from de Castro's opt-aiNet algorithm, Dcopt-aiNet models cloning operation using dynamic cloning operation which is adopted from biological immune network mechanism. Based on the multi-modal benchmarks, experiments were carried out to compare the performance of Dcopt-aiNet with that of opt-aiNet. Experiment results show that when compared with the opt-aiNet method, the new algorithm is capable of improving search performance significantly in successful rate and convergence speed.

关键词： Cloning Immune system Optimization Heuristic algorithms Convergence Benchmark testing

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Input design for nonlinear stochastic dynamic systems - A particle filter approach

Input design for nonlinear stochastic dynamic systems - A pa...

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作者： Gopaluni, R. Bhushan Schön, Thomas B. Wills, Adrian G. Department of Chemical and Biological Engineering University of British Columbia Vancouver V6T 1Z3 Canada Division of Automatic Control Linköping University SE-581 83 Linköping Sweden School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW 2308 Australia

ISBN: (纸本)9783902661937

We propose an algorithm for optimal input design in nonlinear stochastic dynamic systems. The approach relies on minimizing a function of the covariance of the parameter estimates of the system with respect to the input. The covariance matrix is approximated using a joint likelihood function of hidden states and measurements, and a combination of state filters and smoothers. The input is parametrized using an autoregressive model. The proposed approach is illustrated through a simulation example. © 2011 IFAC.

关键词： Covariance matrix

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Blind Identification of Wiener Models *

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IFAC Proceedings Volumes 2011年第1期44卷 5597-5602页

作者： Adrian Wills Thomas B. Schön Lennart Ljung Brett Ninness School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW 2308 Australia Division of Automatic Control Linköping University SE-581 83 Linköping Sweden

Abstract This paper develops and illustrates methods for the identification of Wiener model structures. These techniques are capable of accommodating the “blind” situation where the input excitation to the linear block is not observed. Furthermore, the algorithm developed here can accommodate a nonlinearity which need not be invertible, and may also be multivariable. Central to these developments is the employment of the Expectation Maximisation (EM) method for computing maximum likelihood estimates, and the use of a new approach to particle smoothing to efficiently compute stochastic expectations in the presence of nonlinearities.

关键词： Wiener Model Nonlinear Systems Maximum Likelihood System Identification Parameter Estimation

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