System Identification and Parameter Estimation (191131700)
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Parameter Estimation of Loranz Chaotic Dynamic System Using Bees Algorithm
An important problem in nonlinear science is the unknown parameters estimation in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Bees algorithm (BA) is a new member of me...
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Frequency response diagrams of a system include detailed and recognizable information about the structural and parameter effects of the transfer function model of the system. The information are qualitatively and quantitatively obtainable from simultaneous consideration of amplitude ratio and phase information. In this paper, some rules and relationships are presented for making use of frequenc...
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Neural networks are applied to the system identification problems using adaptive algorithms for either parameter or functional estimation of dynamic systems. In this paper the neural networks' sensitivity to input values and connections' weights, is studied. The Reduction-Sigmoid-Amplification (RSA) neurons are introduced and four different models of neural network architecture are proposed and...
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Parameter identification techniques are particularly attractive to determine the inertial parameters of robot manipulators and manipulated payloads. These parameters are particularly needed in implementation of a model-based controller for robot manipulators. In this paper, the inertial parameters of a manipulated rigid-body object have been estimated. The Newton-Euler equations will be employe...
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تاریخ انتشار 2012