Nonlinear Systems Research Papers - Academia.edu (original) (raw)

This paper demonstrates the ability of Genetic Algorithms (GAs) in the identification of dynamical nonlinear systems. The dynamics of the nonlinear systems have been described by first, second and third order terms. GAs were used... more

This paper demonstrates the ability of Genetic Algorithms (GAs) in the identification of dynamical nonlinear systems. The dynamics of the nonlinear systems have been described by first, second and third order terms. GAs were used suc-cessfully to identify the coefficient of these terms. A com-parison between least-square estimation (LSE) and genetic algorithms estimation (GAE) procedures is provided. The comparison was employed based on two factors, number of observations and estimation accuracy. Genetic algorithms show better performance in both noise free and noisy cases.

This work deals with the state estimation and diagnosis of nonlinear systems with application to power systems. Dynamic modeling is performed using an index 1 property and decoupling techniques. New methods of state estimation, based on... more

This work deals with the state estimation and diagnosis of nonlinear systems with application to power systems. Dynamic modeling is performed using an index 1 property and decoupling techniques. New methods of state estimation, based on Extended Kalman Filter including a sliding window of measurements, are proposed to improve the robustness and accuracy. A new convergence study based on Lyapunov function and conditioning of the observability matrix is proposed to ensure the convergence of the observers. A combination of extended Kalman filter with moving horizon and the version with unknown input is considered to ensure the monitoring task. Performances of the proposed approaches were evaluated by numerical simulations of IEEE power system test.

This work proposes a methodology of identifying linear parameter varying (LPV) models for nonlinear systems. First, linear local models in some operating points, by applying standard identifications procedures for linear systems in time... more

This work proposes a methodology of identifying linear parameter varying (LPV) models for nonlinear systems. First, linear local models in some operating points, by applying standard identifications procedures for linear systems in time domain, are obtained. Next, a LPV model with linear fractional dependence (LFR) with respect to measured variables is fitted with the condition of containing all the linear models identified in previous step (differential inclusion). The fit is carried out using nonlinear least squares algorithms. Finally, this identification methodology will then be applied to a nonlinear turbocharged diesel engine.

Abstract—In this paper a nonlinear observer which synthe-sizes sliding mode techniques and neural state space models is proposed and is applied for robust fault diagnosis in a class of nonlinear systems. The sliding mode term is utilized... more

Abstract—In this paper a nonlinear observer which synthe-sizes sliding mode techniques and neural state space models is proposed and is applied for robust fault diagnosis in a class of nonlinear systems. The sliding mode term is utilized to eliminate the effect of system uncertainties, ...

In this research, a comparative study of two recurrent neural networks, nonlinear autoregressive with exogenous input (NARX) neural network and nonlinear autoregressive moving average (NARMA-L2), and a feedforward neural network (FFNN) is... more

In this research, a comparative study of two recurrent neural networks, nonlinear autoregressive with exogenous input (NARX) neural network and nonlinear autoregressive moving average (NARMA-L2), and a feedforward neural network (FFNN) is performed for their ability to provide adaptive control of nonlinear systems. Three dynamical nonlinear systems of different complexity are considered. The aim of this work is to make the output of the plant follow the desired reference trajectory. The problem becomes more challenging when the dynamics of the plants are assumed to be unknown, and to tackle this problem, a multilayer neural network-based approximate model is set up which will work in parallel to the plant and the control scheme. The network parameters are updated using the dynamic backpropagation (BP) algorithm.

Considers control design using an adaptive backstepping algorithm for a class of nonlinear continuous uncertain processes with disturbances which can be converted to a parametric semi-strict feedback form. Sliding mode control using a... more

Considers control design using an adaptive backstepping algorithm for a class of nonlinear continuous uncertain processes with disturbances which can be converted to a parametric semi-strict feedback form. Sliding mode control using a combined adaptive backstepping sliding mode control algorithm is also studied. The algorithm follows a systematic procedure for the design of adaptive control laws for the output of observable minimum phase nonlinear systems with matched and unmatched uncertainty. An existing sufficient condition for sliding is not needed by the new algorithm

This paper deals with the control laws recon guration of nonlinear systems, by using a Fuzzy-Model-based Predictive Control (FMPC). It should be noted that the studied systems are writ- ten in the quasi-linear parametric varying (quasi-... more

This paper deals with the control laws
recon guration of nonlinear systems, by using a
Fuzzy-Model-based Predictive Control (FMPC). It
should be noted that the studied systems are writ-
ten in the quasi-linear parametric varying (quasi-
LPV) form. This FMPC strategy is developed to
preserve closed-loop stability in the nominal and
actuator faulty case. Fault accommodation by per-
turbations rejection is presented. This step is done
by interpolation-based control to cover the entire
area of operation. To allow the process to maintain
current performances closed to desired performances,
a dynamic optimizer is used. Our contribution comes
from the combination of several aspects: fuzzy model,
quadratic programming and faults decoupling princi-
ple. The linearization around a family of equilibrium
points is also studied. The operating points are appro-
priately con gured by a set of variables called premise.

This is a one page reference sheet for several common numerical methods. It lists and/or describes several methods for root finding, linear & non-linear systems of equations, quadrature, and solving differential equations. It also... more

This is a one page reference sheet for several common numerical methods. It lists and/or describes several methods for root finding, linear & non-linear systems of equations, quadrature, and solving differential equations. It also includes certain Mat-lab built in functions. As it is only one page, some numerical methods are only mentioned in order to provide a starting point for further research. A special thanks goes to my professor for the Mat-lab Programming & Numerical Methods class in Howard County Community College, Professor Mark Edelen, who was an excellent teacher for this class. He also looked over an earlier version of this paper and proofread it.

: The goal of this project was to put the intuitive idea of gain-scheduling on a rigorous foundation for a class of nonlinear, distributed-parameter systems. This involved a study of the existence and characterization of the ideal,... more

: The goal of this project was to put the intuitive idea of gain-scheduling on a rigorous foundation for a class of nonlinear, distributed-parameter systems. This involved a study of the existence and characterization of the ideal, infinite-dimensional, feedback control. Since in most applications the feedback function cannot be computed in closed form it was necessary to study the convergence of approximate feedback functions, based on increasingly higher order finite-dimensional approximations of the system, to the ideal function. Finally, the results were applied to Burgers' Equation, which can be viewed as a low-order approximation to a wide variety of physical phenomena, including viscous compressible flow.

The ongoing and primary goal of the research is the pursuit of understanding of nonlinear processes in natural phenomena arising in optics and fluids. A considerable share of our attention is devoted to nonlinear optics, a relatively... more

The ongoing and primary goal of the research is the pursuit of understanding of nonlinear processes in natural phenomena arising in optics and fluids. A considerable share of our attention is devoted to nonlinear optics, a relatively young subject, extremely rich in scientific and technological potential. While the studies focus on scientific questions connected with laser diode arrays, beam instabilities and the behavior of light beams at interfaces between nonlinear dielectrics, the technological ramifications and future opportunities are in many cases obvious. Optics also serves as a useful paradigm for gaining an increased understanding in other fields. For example, turbulence in optics, the study of the complex space-time filaments, patterns and defects which appear in feedback cavities and counterpropagating beams may be more analytically tractable than in other branches of continuous mechanics. There is little doubt that nonlinear optics is a subject in which interest is increasing.

A total of 49 extended abstracts are included in this volume of papers presented at the 15th International Workshop on Water Waves and Floating Bodies, held 17 February - 1 March, 2000, Caesarea, Israel. Also see... more

A total of 49 extended abstracts are included in this volume of papers presented at the 15th International Workshop on Water Waves and Floating Bodies, held 17 February - 1 March, 2000, Caesarea, Israel. Also see http://www.eng.tau.ac.il/-miloh/iwwwfb. The objective of the Workshop is to provide a forum for informal discussions of fundamental research, of mutual interest to both engineers and scientists, in the broad area of wave interactions with fixed, floating or submerged bodies.

We derive a novel explicit wave-domain model for “diode clipper” circuits with an arbitrary number of diodes in each orientation, applicable, e.g., to wave digital filter emulation of guitar distortion pedals. Improving upon and... more

We derive a novel explicit wave-domain model for “diode clipper” circuits with an arbitrary number of diodes in each orientation, applicable, e.g., to wave digital filter emulation of guitar distortion pedals. Improving upon and generalizing the model of Paiva et al. (2012), which approximates reverse-biased diodes as open circuits, we derive a model with an approximated correction term using two Lambert W functions. We study the energetic properties of each model and clarify aspects of the original derivation. We demonstrate the model’s validity by comparing a modded Tube Screamer clipping stage emulation to SPICE simulation.