Search Results - (( parameter estimation method algorithm ) OR ( process identification method algorithm ))
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1
Estimation in spot welding parameters using genetic algorithm
Published 2007“…The application has widespread in many areas especially in system and control engineering. Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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2
Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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3
Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. …”
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4
PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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5
A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…The results showed that the proposed method was efficient in identifying both the Hammerstein model subsystems in terms of the quadratic output estimation error and parameter deviation index. …”
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6
Simultaneous Computation of Model Order and Parameter Estimation of a Heating System Based on Gravitational Search Algorithm for Autoregressive with Exogenous Inputs
Published 2015“…Model order selection and parameter estimation are two significant aspects of determining the mathematical model for system identification. …”
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7
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…System identification is a method to build a model for a dynamic system from the experimental data. …”
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8
Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…System identification is a method to build a model for a dynamic system from the experimental data. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…The results show that Volterra model with PSO–KS is preferable for fast identification process, while ABC–KS method is preferable for accurate identification process. …”
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10
RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…The learning method will determine the performance’s capability of the networks for the system identification process which will be one of the key issues to be discussed in the thesis. …”
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11
SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS
Published 2009“…The subspace system identification method is used to estimate the linear model parameters. …”
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12
Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…The results show that Volterra model with PSO-KS is preferable for fast identification process, while ABC-KS method is preferable for accurate identification process. …”
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13
Parameter identification of an autonomous quadrotor
Published 2011“…The unknown parameter of the quadrotor will be identified using state estimation method with the implementation of Unscented Kalman Filter (UKF). …”
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Proceeding Paper -
14
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…The numerical and experimental results also showed that both Hammerstein model subsystems are defined effectively using the mMVO-based method, particularly in quadratic output estimation error and a differentiation parameter index. …”
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15
A graphical user interface application for continuous-time identification of dynamical system
Published 2002“…This paper introduces a Graphical User Interface (GUI) application in system identification and parameter estimation of dynamic systems using Generalized Poisson Moment Functionals (GPMF) method based on Instrumental Variable (IV) algorithm. …”
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16
Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim
Published 2018“…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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17
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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18
Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…The adaptive control structure is based on the linear model of the process and combined with numerical algorithm for subspace state space system identification (N4SID). …”
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19
Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The NARMAX model and its derivatives (Nonlinear Auto-Regressive with Exogenous Inputs (NARX) and Nonlinear Auto-Regressive Moving Average (NARMA)) are powerful, efficient and unified representations of a variety of nonlinear models. The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm. …”
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20
The largest studentized residual test for bad data identification in state estimation of a power system
Published 2015“…The presence of systematic errors can alter the results of state estimation. The chi-square and normalized residual tests are the common post estimation procedures usually used for detection and identification of gross errors in the estimation algorithm. …”
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