System identification

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In control engineering, the field of system identification uses statistical methods to build mathematical models of dynamical systems from measured data. (Wikipedia.org)






Conferences related to System identification

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2017 IEEE Power & Energy Society General Meeting

The annual IEEE Power & Energy Society General Meeting will bring together over 2000 attendees for technical sessions, student program, awards ceremony, committee meetings, and tutorials.

  • 2015 IEEE Power & Energy Society General Meeting

    The annual IEEE PES General Meeting will bring together over 2500 attendees for technical sessions, administrative sessions, super sessions, poster sessions, student programs, awards ceremonies, committee meetings, tutorials and more PLEASE NOTE: Abstracts are not accepted for the 2015 IEEE PES General Meeting, full papers only can be submitted to the submission site 24 October 2014 through 21 November 2014.  The site will be available from the PES home page www.ieee-pes.org

  • 2014 IEEE Power & Energy Society General Meeting

    The annual IEEE PES General Meeting will bring together over 2500 attendees for technical sessions, administrative sessions, super sessions, poster sessions, student programs, awards ceremonies, committee meetings, tutotials and more

  • 2013 IEEE Power & Energy Society General Meeting

    The annual IEEE Power & Energy Society General Meeting will bring together over 2000 attendees for technical sessions, student program, awards ceremony, committee meetings, and tutorials.

  • 2012 IEEE Power & Energy Society General Meeting

    The annual IEEE Power & Energy Society General Meeting will bring together over 2000 attendees for technical sessions, student program, awards ceremony, committee meetings, and tutorials.

  • 2011 IEEE Power & Energy Society General Meeting

    IEEE Power & Energy Annual Meeting --Papers --Awards --Plenary --Committee Meetings --Governing Board --Receptions --Tech tours --Tutorials --Companions Program

  • 2010 IEEE Power & Energy Society General Meeting

    IEEE Power & Energy Society Annual Meeting --Technical Sessions --Committee Meetings --Plenary Session --Gove Board Meeting --Awards Banquet --Tutorials --Student Activities --Social Events --Companions Program

  • 2009 IEEE Power & Energy Society General Meeting

    Paper and Panel sessions involving topics of interest to electric power engineers, technical committee meetings, administrative committee meetings, awards luncheon and plenary session.


2014 American Control Conference - ACC 2014

All areas of the theory and practice of automatic control, including but not limited to network control systems, model predictive control, systems analysis in biology and medicine, hybrid and switched systems, aerospace systems, power and energy systems and control of nano- and micro-systems.

  • 2013 American Control Conference (ACC)

    Control systems theory and practice. Conference themes on sustainability, societal challenges for control, smart healthcare systems. Conference topics include biological systems, vehicle dynamics and control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2012 American Control Conference - ACC 2012

    All areas of control engineering and science.

  • 2011 American Control Conference - ACC 2011

    ACC provides a forum for bringing industry and academia together to discuss the latest developments in the area of Automatic Control Systems, from new control theories, to the advances in sensors and actuator technologies, and to new applications areas for automation.

  • 2010 American Control Conference - ACC 2010

    Theory and practice of automatic control


2013 13th International Conference on Control, Automaton and Systems (ICCAS)

Control Theory and Application, Intelligent Systems, Industrial Applications of Control,Sensor and Signal Processing, Control Devices and Instruments, Robot Control, RobotVision, Human-Robot Interaction, Robotic Applications, Unmanned Vehicle Systems...


2012 16th IFAC Symposium on System Identification (SYSID 2012)

SYSID aims at promoting research and development activities in the area of system identification, experimental modeling, signal processing and adaptive control. The scope of the symposium covers all aspects of these areas, ranging from theoretical investigations to a large variety of applications.


2012 International Conference on Modelling, Identification and Control (ICMIC)

Static and dynamic systems modeling, control and optimization techniques, and nonlinear & linear system identification.

  • 2011 International Conference on Modelling, Identification and Control (ICMIC)

    The 3rd Conference provides a forum for professionals, academics, and researchers to present latest developments from interdisciplinary studies, algorithms and applications. It particularly welcomes those emerging methodologies and techniques that bridge theoretical studies and applications in all engineering and science branches. Novel quantitative economical, financial studies are considered as well.

  • 2010 International Conference on Modelling, Identification and Control (ICMIC)

    This international conference will bring together top researchers, practitioners and students from around the world to discuss the latest advances in the field of system modelling, system identification and system control.


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Periodicals related to System identification

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Instrumentation and Measurement, IEEE Transactions on

Measurements and instrumentation utilizing electrical and electronic techniques.


Power Delivery, IEEE Transactions on

Research, development, design, application, construction, the installation and operation of apparatus, equipment, structures, materials, and systems for the safe, reliable, and economic delivery and control of electric energy for general industrial, commercial, public, and domestic consumption.


Power Systems, IEEE Transactions on

Requirements, planning, analysis, reliability, operation, and economics of electrical generating, transmission, and distribution systems for industrial, commercial, public, and domestic consumption.


Signal Processing, IEEE Transactions on

The technology of transmission, recording, reproduction, processing, and measurement of speech; other audio-frequency waves and other signals by digital, electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of thesetechnologies.



Most published Xplore authors for System identification

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Xplore Articles related to System identification

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Techniques to improve the regressor matrix condition for real-time parameter identification

A. D. Ngo; D. B. Doman American Control Conference, 2001. Proceedings of the 2001, 2001

In this paper, on-line parameter identification algorithms that consider the collinearity of the system measurements are presented. Using null-space injection and regularized linear regression with stochastic constraints, the proposed methods improve the estimates of the system parameters


A nonlinear least-squares approach for identification of the induction motor parameters

Kaiyu Wang; J. Chiasson; M. Bodson; L. M. Tolbert IEEE Transactions on Automatic Control, 2005

A nonlinear least-squares method is presented for the identification of the induction motor parameters. A major difficulty with the induction motor is that the rotor state variables are not available measurements so that the system identification model cannot be made linear in the parameters without overparametrizing the model. Previous work in the literature has avoided this issue by making simplifying ...


Modified AIC and FPE criteria for autoregressive (AR) model order selection by using LSFB estimation method

Sh. Khorshidi; M. Karimi Advances in Computational Tools for Engineering Applications, 2009. ACTEA '09. International Conference on, 2009

The Least-Squares-Forward-Backward (LSFB) method for estimating the parameters of the autoregressive (AR) model is considered and new theoretical approximations for expectations of the prediction error and the residual variance are derived. These results are used for modifying the AR order selection criteria FPE and AIC. The performance of these modified criteria is compared with other AR order selection criteria using ...


Asymptotic system identification method based on particle swarm optimization

Hideo Muroi; Shuichi Adachi ICCAS-SICE, 2009, 2009

In general, structure of a system to be identified is unknown for users a priori. This makes the model complex and high order structure. In this paper, we introduce the asymptotic method (ASYM) to deal with the problem. ASYM calculates a high-order model using the well-known least squares method, then reduces the identified model to a simple one. For this ...


Separable least squares identification of a parallel cascade model of human ankle stiffness [stretch reflex EMG]

D. T. Westwick; R. E. Kearney Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE, 2001

The identification of a dynamic, nonlinear model of human ankle stiffness is considered in a minimum mean squared error framework. The model consists of two parallel pathways, one representing the intrinsic dynamics, the other representing the reflex contribution to the stiffness. The model is shown to be linear in all of its parameters, except for those used to describe a ...


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Educational Resources on System identification

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eLearning

Techniques to improve the regressor matrix condition for real-time parameter identification

A. D. Ngo; D. B. Doman American Control Conference, 2001. Proceedings of the 2001, 2001

In this paper, on-line parameter identification algorithms that consider the collinearity of the system measurements are presented. Using null-space injection and regularized linear regression with stochastic constraints, the proposed methods improve the estimates of the system parameters


A nonlinear least-squares approach for identification of the induction motor parameters

Kaiyu Wang; J. Chiasson; M. Bodson; L. M. Tolbert IEEE Transactions on Automatic Control, 2005

A nonlinear least-squares method is presented for the identification of the induction motor parameters. A major difficulty with the induction motor is that the rotor state variables are not available measurements so that the system identification model cannot be made linear in the parameters without overparametrizing the model. Previous work in the literature has avoided this issue by making simplifying ...


Modified AIC and FPE criteria for autoregressive (AR) model order selection by using LSFB estimation method

Sh. Khorshidi; M. Karimi Advances in Computational Tools for Engineering Applications, 2009. ACTEA '09. International Conference on, 2009

The Least-Squares-Forward-Backward (LSFB) method for estimating the parameters of the autoregressive (AR) model is considered and new theoretical approximations for expectations of the prediction error and the residual variance are derived. These results are used for modifying the AR order selection criteria FPE and AIC. The performance of these modified criteria is compared with other AR order selection criteria using ...


Asymptotic system identification method based on particle swarm optimization

Hideo Muroi; Shuichi Adachi ICCAS-SICE, 2009, 2009

In general, structure of a system to be identified is unknown for users a priori. This makes the model complex and high order structure. In this paper, we introduce the asymptotic method (ASYM) to deal with the problem. ASYM calculates a high-order model using the well-known least squares method, then reduces the identified model to a simple one. For this ...


Separable least squares identification of a parallel cascade model of human ankle stiffness [stretch reflex EMG]

D. T. Westwick; R. E. Kearney Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE, 2001

The identification of a dynamic, nonlinear model of human ankle stiffness is considered in a minimum mean squared error framework. The model consists of two parallel pathways, one representing the intrinsic dynamics, the other representing the reflex contribution to the stiffness. The model is shown to be linear in all of its parameters, except for those used to describe a ...


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