Stationary Response of States-Constrained Nonlinear Systems Under Stochastic Parametric and External Excitations

1991 ◽  
Vol 113 (4) ◽  
pp. 575-581 ◽  
Author(s):  
R. J. Chang
Keyword(s):  
Fourier Series ◽  
Robot Manipulator ◽  
External Noise ◽  
Algebraic Equations ◽  
Working Space ◽  
Closure Scheme ◽  
Gaussian Density ◽  
The Moment ◽  
Non Gaussian ◽  
Parametric And External Excitations

A Fourier-series closure scheme is developed for the prediction of the stationary stochastic response of a stochastic parametrically and externally excited oscillator with a nonpolynomial type nonlinearity and under states constraint. The technique is implemented by deriving the moment relations and employing the Fourier series as the expansion of a non-Gaussian density for constructing and solving a set of algebraic equations with unknown Fourier coefficients. A single-arm robot manipulator operated in a constrained working space and subjected to parametric and/ or external noise excitations is selected to illustrate the present approach. The validity of the present scheme is further supported by some exact solutions and Monte Carlo simulations.

Non-Gaussian Linearization Method for Stochastic Parametrically and Externally Excited Nonlinear Systems

1992 ◽  
Vol 114 (1) ◽  
pp. 20-26 ◽  
Author(s):  
R. J. Chang
Keyword(s):  
Monte Carlo ◽  
Nonlinear System ◽  
Nonlinear Systems ◽  
Stochastic System ◽  
Linearization Method ◽  
Weighted Sum ◽  
Gaussian Density ◽  
Parametric Noise ◽  
Non Gaussian ◽  
Parametric And External Excitations

A new practical non-Gaussian linearization method is developed for the problem of the dynamic response of a stable nonlinear system under both stochastic parametric and external excitations. The non-Gaussian linearization system is derived through a non-Gaussian density that is constructed as the weighted sum of undetermined Gaussian densities. The undetermined Gaussian parameters are then derived through solving a set of nonlinear algebraic moment relations. The method is illustrated by a Duffing-type stochastic system with/without parametric noise excited term. The accuracy in predicting the stationary and nonstationary variances by the present approach is compared with some exact solutions and Monte Carlo simulations.

scholarly journals Modelling with star-shaped distributions

2020 ◽  
Vol 8 (1) ◽  
pp. 45-69
Author(s):  
Eckhard Liebscher ◽  
Wolf-Dieter Richter
Keyword(s):  
Probabilistic Models ◽  
Arbitrary Dimension ◽  
Probability Density Functions ◽  
Density Functions ◽  
Wide Range ◽  
Gaussian Density ◽  
Spherical Distributions ◽  
Data Points ◽  
Non Gaussian ◽  
General Method

AbstractWe prove and describe in great detail a general method for constructing a wide range of multivariate probability density functions. We introduce probabilistic models for a large variety of clouds of multivariate data points. In the present paper, the focus is on star-shaped distributions of an arbitrary dimension, where in case of spherical distributions dependence is modeled by a non-Gaussian density generating function.

scholarly journals Under-Actuated Robot Manipulator Positioning Control Using Artificial Neural Network Inversion Technique

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Ali T. Hasan
Keyword(s):  
Inverse Dynamics ◽  
Robot Manipulator ◽  
Positioning Control ◽  
Passive Joint ◽  
Inversion Technique ◽  
Working Space ◽  
Neural Network Inversion ◽  
Gear Trains ◽  
Artificial Neural ◽  
Underactuated Robot

This paper is devoted to solve the positioning control problem of underactuated robot manipulator. Artificial Neural Networks Inversion technique was used where a network represents the forward dynamics of the system trained to learn the position of the passive joint over the working space of a 2R underactuated robot. The obtained weights from the learning process were fixed, and the network was inverted to represent the inverse dynamics of the system and then used in the estimation phase to estimate the position of the passive joint for a new set of data the network was not previously trained for. Data used in this research are recorded experimentally from sensors fixed on the robot joints in order to overcome whichever uncertainties presence in the real world such as ill-defined linkage parameters, links flexibility, and backlashes in gear trains. Results were verified experimentally to show the success of the proposed control strategy.

scholarly journals A Matrix Formulation for the Moment Distribution Method Applied to Continuous Beams

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Arlindo Pires Lopes ◽  
Adriana Alencar Santos ◽  
Rogério Coelho Lopes
Keyword(s):  
Structural Analysis ◽  
Algebraic Equations ◽  
Displacement Method ◽  
Matrix Formulation ◽  
Distribution Method ◽  
Continuous Beams ◽  
Moment Distribution ◽  
Moment Distribution Method ◽  
Carry Over ◽  
The Moment

The Moment Distribution Method is a quite powerful hand method of structural analysis, in which the solution is obtained iteratively without even formulating the equations for the unknowns. It was formulated by Professor Cross in an era where computer facilities were not available to solve frame problems that normally require the solution of simultaneous algebraic equations. Its relevance today, in the era of personal computers, is in its insight on how a structure reacts to applied loads by rotating its nodes and thus distributing the loads in the form of member-end moments. Such an insight is the foundation of the modern displacement method. This work has a main objective to present an exact solution for the Moment Distribution Method through a matrix formulation using only one equation. The initial moments at the ends of the members and the distribution and carry-over factors are calculated from the elementary procedures of structural analysis. Four continuous beams are investigated to illustrate the applicability and accuracy of the proposed formulation. The use of a matrix formulation yields excellent results when compared with those in the literature or with a commercial structural program.

A Theoretical Series Solution for the Dynamics of Finite-Length Bearings and Squeeze-Film Dampers

2003 ◽  
Author(s):  
Jose´ Antunes ◽  
Miguel Moreira ◽  
Philippe Piteau
Keyword(s):  
Fourier Series ◽  
Galerkin Method ◽  
Finite Length ◽  
Reynolds Equation ◽  
Double Fourier Series ◽  
Squeeze Film ◽  
Algebraic Equations ◽  
Squeeze Film Dampers ◽  
Galerkin Solution ◽  
The Galerkin Method

In this paper we develop a non-linear dynamical solution for finite length bearings and squeeze-film dampers based on a Spectral-Galerkin method. In this approach the gap-averaged pressure is approximated, in the lubrication Reynolds equation, by a truncated double Fourier series. The Galerkin method, applied over the residuals so obtained, generate a set of simultaneous algebraic equations for the time-dependent coefficients of the double Fourier series for the pressure. In order to assert the validity of our 2D–Spectral-Galerkin solution we present some preliminary comparative numerical simulations, which display satisfactory results up to eccentricities of about 0.9 of the reduced fluid gap H/R. The so-called long and short-bearing dynamical solutions of the Reynolds equation, reformulated in Cartesian coordinates, are also presented and compared with the corresponding classic solutions found on literature.

scholarly journals Inverse Problem for a Mixed Type Integro-Differential Equation with Fractional Order Caputo Operators and Spectral Parameters

Axioms ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 121
Author(s):  
Tursun K. Yuldashev ◽  
Erkinjon T. Karimov
Keyword(s):  
Differential Equation ◽  
Inverse Problem ◽  
Fourier Series ◽  
Fractional Order ◽  
Mixed Type ◽  
Algebraic Equations ◽  
Negative Part ◽  
Spectral Parameters ◽  
Fredholm Type ◽  
Integro Differential Equation

The questions of the one-value solvability of an inverse boundary value problem for a mixed type integro-differential equation with Caputo operators of different fractional orders and spectral parameters are considered. The mixed type integro-differential equation with respect to the main unknown function is an inhomogeneous partial integro-differential equation of fractional order in both positive and negative parts of the multidimensional rectangular domain under consideration. This mixed type of equation, with respect to redefinition functions, is a nonlinear Fredholm type integral equation. The fractional Caputo operators’ orders are smaller in the positive part of the domain than the orders of Caputo operators in the negative part of the domain under consideration. Using the method of Fourier series, two systems of countable systems of ordinary fractional integro-differential equations with degenerate kernels and different orders of integro-differentation are obtained. Furthermore, a method of degenerate kernels is used. In order to determine arbitrary integration constants, a linear system of functional algebraic equations is obtained. From the solvability condition of this system are calculated the regular and irregular values of the spectral parameters. The solution of the inverse problem under consideration is obtained in the form of Fourier series. The unique solvability of the problem for regular values of spectral parameters is proved. During the proof of the convergence of the Fourier series, certain properties of the Mittag–Leffler function of two variables, the Cauchy–Schwarz inequality and Bessel inequality, are used. We also studied the continuous dependence of the solution of the problem on small parameters for regular values of spectral parameters. The existence and uniqueness of redefined functions have been justified by solving the systems of two countable systems of nonlinear integral equations. The results are formulated as a theorem.

A Practical Technique for Spectral Analysis of Nonlinear Systems Under Stochastic Parametric and External Excitations

1991 ◽  
Vol 113 (4) ◽  
pp. 516-522 ◽  
Author(s):  
R. J. Chang
Keyword(s):  
Nonlinear System ◽  
Linear System ◽  
Spectral Response ◽  
Duffing Oscillator ◽  
Gaussian White Noise ◽  
Matching Condition ◽  
External Noise ◽  
Equivalent Linearization ◽  
Parametric Noise ◽  
Parametric And External Excitations

A practical approach is developed for analyzing the spectral response of a nonlinear system subjected to both parametric and external Gaussian white noise excitations. The technique is implemented through the combined methods of equivalent external excitation and equivalent linearization to derive an equivalent linear system under equivalent external noise excitation. The spectral response is then obtained through utilizing the input/output spectral relation and covariance matching condition. A parametric noise excited linear system, Duffing oscillator, and nonlinear system with hysteretic nonlinearity are selected for investigation. The validity of the proposed method for analyzing spectral response is further supported by some analytical solutions and FFT technique through Monte Carlo simulations.

M-Ary Alpha-Stable Noise Modulation in Spread-Spectrum Communication

2015 ◽  
Vol 14 (03) ◽  
pp. 1550022 ◽  
Author(s):  
Mehmet Emre Cek
Keyword(s):  
Gaussian Noise ◽  
Spread Spectrum ◽  
Additive White Gaussian Noise ◽  
Characteristic Exponent ◽  
Random Signal ◽  
Spread Spectrum Communication ◽  
Order Moment ◽  
Gaussian Density ◽  
Shift Keying ◽  
Non Gaussian

In this paper, a spread-spectrum communication system based on a random carrier is proposed which transmits M-ary information. The random signal is considered as a single realization of a random process taken from prescribed symmetric α-stable (SαS) distribution that carries digital M-ary information to be transmitted. Considering the noise model in the channel as additive white Gaussian noise (AWGN), the transmitter sends the information carrying random signal from non-Gaussian density. Alpha-stable distribution is used to encode the M-ary message. Inspired by the chaos shift keying techniques, the proposed method is called M-ary symmetric alpha-stable differential shift keying (M-ary SαS-DSK). The main purpose of preferring non-Gaussian noise instead of conventional pseudo-noise (PN) sequence is to overcome the drawback of self-repeating noise-like sequences which are detectable due to the periodic behavior of the autocorrelation function of PN sequences. Having infinite second order moment in α-stable random carrier offers secrecy of the information due to the non-constant autocorrelation behavior. The bit error rate (BER) performance of the proposed method is illustrated by Monte Carlo simulations with respect to various characteristic exponent values and different data length.

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