9,651 resources 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.
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 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...
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.
Static and dynamic systems modeling, control and optimization techniques, and nonlinear & linear system identification.
Measurements and instrumentation utilizing electrical and electronic techniques.
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.
Requirements, planning, analysis, reliability, operation, and economics of electrical generating, transmission, and distribution systems for industrial, commercial, public, and domestic consumption.
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.
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
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 ...
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 ...
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 ...
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 ...
Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on, 1995
Discrete-time nonlinear systems represented in the state-space form are considered. Input (drive signal) and output (response signal) are assumed to be measurable. The problem of approximating the external behavior of such a system-in the form of an Input-Output (I-O) model-is addressed. It is already known that a system with fading-memory can be uniformly I-O approximated by a nonlinear MA filter ...
Decision and Control, 1985 24th IEEE Conference on, 1985
After reviewing the already known "static" characteristics of weighted least squares (WLS) estimators such as the effective and equivalent numbers of observations, their tracking properties are investigated. Several new "dynamic" characteristics of WLSE's are proposed, like the associate impulse response, associate frequency characteristics, estimation bandwidth and estimation delay. It is shown that the associate frequency characteristics may serve as a ...
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on, 2001
In an impulsive noise environment, most learning algorithms encounter difficulty in distinguishing the nature of a large error signal, whether caused by the impulse noise or model error. Consequently, they suffer from large misadjustment or otherwise slow convergence. A new nonlinear RLS (VFF- NRLS) adaptive algorithm with variable forgetting factor for FIR filters is introduced. In this algorithm, the autocorrelations ...
Instrumentation and Measurement, IEEE Transactions on, 1998
This paper introduces a new set of multifrequency ternary sequence (MTS) signals. They are MTS octave signals, which are designed by frequency shift keyed (FSK) modulation so that two separate parts of a frequency response are examined by one test signal. One of these signals is a new five-octave FSK MTS signal which is described by a total of 64 ...
India Conference, 2008. INDICON 2008. Annual IEEE, 2008
Pairing is the first step of decentralized controller design procedure in multi-input multi-output (MIMO) processes. In spite of considerable efforts dedicated to this problem, most of the known pairing techniques are offline algorithms and fail to decide when dealing with high dimensional and/or time varying processes and adaptive control applications. In this article, normalized effective relative gain array (NERGA) is ...
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