Model Identification and Robust Nonlinear Model Predictive Control of a Twin Rotor MIMO System [PDF]
, 2009 PhDThis thesis presents an investigation into a number of model predictive control (MPC) paradigms for a nonlinear aerodynamics test rig, a twin rotor multi-input multi-output system (TRMS).
Rahideh, Akbar
core +4 more sources
The identification method of the coal mill motor power model with the use of machine learning techniques [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 1921 The article presents an identification method of the model of the ball-and-race coal mill motor power signal with the use of machine learning techniques. The stages of preparing training data for model parameters identification purposes are described, as
Zofia Magdalena Łabęda-Grudziak +1 more
doaj +1 more source
Automatika, 2022 This paper studies the modelling of a class of nonlinear plants with known structures but unknown parameters and proposes a general nonlinear U-model expression. The particle swarm optimization algorithm is used to identify the time-varying parameters of
Fengxia Xu +3 more
doaj +1 more source
Identification of nonlinear interconnected systems [PDF]
, 2009 This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.In this work we address the problem of identifying a discrete-time nonlinear system composed of a linear dynamical system connected to a static nonlinear ...
Pepona, Eleni
core +7 more sources
A novel strategy for force identification of nonlinear structures
Journal of Low Frequency Noise, Vibration and Active Control, 2022 Dynamic force is the key indicator for monitoring the condition of a mechanical product. These mechanical structures always encompass some nonlinear factors. Most previous studies focused on obtaining the dynamic force of linear structures. Consequently,
Jie Liu +3 more
doaj +1 more source
Identification of Hysteresis Functions Using a Multiple Model Approach [PDF]
, 2001 This paper considers the identification of static hysteresis functions which describe phenomena in mechanical systems, piezoelectric actuators and materials.
Mihaylova, L +3 more
core +4 more sources
A tunable radial basis function model for nonlinear system identification using particle swarm optimisation [PDF]
, 2009 A tunable radial basis function (RBF) network model is proposed for nonlinear system identification using particle swarm optimisation (PSO). At each stage of orthogonal forward regression (OFR) model construction, PSO optimises one RBF unit's centre ...
Harris, C. J. +12 more
core +1 more source
Identification of Nonlinear Systems Using Radial Basis Function Neural Network [PDF]
, 2014 This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are ...
Pislaru, Crinela, Shebani, Amer
core +4 more sources
Analysis and Identification of Nonlinear Acoustic Damping in Miniature Loudspeakers
Applied Sciences, 2021 Nonlinear acoustic damping is a key nonlinearity in miniature loudspeakers when the air velocity is at a high amplitude. Measurement of nonlinear acoustic damping is beneficial for predicting and analyzing the performance of miniature loudspeakers ...
Jie Huang +3 more
doaj +1 more source
Fractional power NARX model identification using a harmony search algorithm [PDF]
, 2012 A novel type of discrete-time fractional-powernonlinear autoregressive with exogenous input (FPNARX) modelis introduced for system identification, modeling and prediction.Parameter estimation of such a model is a nonlinear optimizationproblem.
Zhao, Yifan +7 more
core +1 more source