Nonlinear dynamic system identification
Review of rational (total) nonlinear dynamic system modelling, identification, and control
... into nonlinear rational model term selection and parameter ...model identification with proper extension of classical least squares ...control system design, the U-model and hence U-control provide a ...
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An Intelligent Nonlinear System Identification Method with an Application to Condition Monitoring
... types, dynamic nonlinear systems are best modeled by recurrent networks, due to the interacting nature of present and past values of the inputs and outputs via feedback ...any nonlinear ...
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Nonlinear System Identification in Frequent and Infrequent Operating Points for Nonlinear Model Predictive Control
... low nonlinear process up to 1000 for high nonlinear ...adaptive dynamic [6] or general nonlinear dynamic model has also been used [8] in some ...in identification of a ...
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Identification of continuous-time models for nonlinear dynamic systems from discrete data
... System identification involves two coupled problems: the detection of the model structure and estimation of the ...Therefore system identification searches for a solution in the Cartesian ...
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Designing Dynamic Neural Network For Non-Linear System Identification
... the system, or - according to the principle of parsimony - we have to select as simple model class as ...or nonlinear system identification and there are special ones developed for neural ...
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Sparse Bayesian Nonlinear System Identification using Variational Inference
... Abstract—Bayesian nonlinear system identification for one of the major classes of dynamic model, the nonlinear autoregressive with exogenous input (NARX) model, has not been widely ...
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Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
... in identification from input-output ...block-oriented nonlinear systems where the linear dynamic block is sandwiched in between two static nonlinear blocks, which appear in many engineering ...
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Identification and Adaptive Control of Dynamic Nonlinear Systems Using Sigmoid Diagonal Recurrent Neural Network
... From Table 1 and Figure 4, it is obvious that the val- ues of the diagonal weights in the DRNN controller is located within a wide range between 16.4877 (neuron number 4) and -45.6087 (neuron number 7) while in the SDRNN ...
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Hydrologic system complexity and nonlinear dynamic concepts for a catchment classification framework
... towards identification of models for medium-term to long-term water planning and management (including envi- ronmental flow requirements), rather than flood forecasting, which requires data at daily and even much ...
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On the orthogonalised reverse path method for nonlinear system identification
... linear dynamic compliance matrix in the presence of nonlinearities in a general Multi-Degree-of-Freedom (MDOF) system can be solved using the Conditioned Reverse Path (CRP) method introduced by Richards and ...
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Multivariable system identification for dynamic discrete time nonlinear system using genetic algorithm
... The number of possible terms in AutoRegressivs Moving Average with eXogenous input or ARMAX model is equal to the sum of allowable maximum lags while the maximum numb= of terms in NARMAX[r] ...
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Nonlinear system identification and control using dynamic multi-time scales neural networks
... analysis, identification and control with continuous time dynamic neural networks with or without considering the time ...for dynamic neural networks with different ...Many dynamic neural ...
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An Adaptive Nonlinear Filter for System Identification
... the identification of Hammerstein nonlinear systems (a static memoryless nonlinear system in series with a dynamic linear system) is that the output of the nonlinear ...
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Nonlinear dynamic of the multicellular chopper
... In recent decades, it was discovered that most of static converters were the seat of unknown nonlinear phenomena in power electronics [7, 8, 13, 19]. It is for example the case of multicellular choppers that can ...
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Linear system identification of longitudinal vehicle dynamics versus nonlinear physical modelling
... solver to be important in this work. MATLAB’s ode23 solver [14] operated well for the ‘best’ parameters—those which would provide a good fit to the data. However, this solver became computationally inefficient towards ...
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Studies on Test System Graying and Its Dynamic Feature Identification
... box” system transforms to “white” system or “gray” system have gradually been in hot ...measurement system is time-varying, dynamic, random and self-correlation, it should be considered ...
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Recurrence and Nonlinear System Dynamic Analysis of the Electrochemical Oscillations Recorded in the System Mild Steel/H3PO4
... A number of methods have been devised to compute dynamical parameters from time series [18]. Such parameters are the information dimension, entropy, Lyapunov exponents, dimension spectrum, etc. In all cases it is assumed ...
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Complex Nonlinear System Modelling and Parameters Identification by Deep Neural Networks
... inherently nonlinear in nature, many efforts have been made to improve the understanding of complicated nonlinear ...identify nonlinear systems by conventional methods such as machine ...complex ...
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Bayesian system identification of a nonlinear dynamical system using a novel variant of Simulated Annealing
... the system identification of a nonlinear dynamical system using experimentally obtained training ...modal identification [2], state-estimation [3] (through use of the particle fil- ...
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A practical approach to parameter identification for a lightly damped, weakly nonlinear system
... damped system is not common in the ...fluid-structure system is ...fluid-structure system is very lightly damped and weakly non-linear, but it is these weak damping forces which determine both the ...
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