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===Nonlinearity=== |
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Revision as of 08:50, 29 March 2018
Description
The nonlinear RC-ladder is an electronic test circuit introduced in [1]. This nonlinear first-order system models a resistor-capacitor network that exhibits a distinct nonlinear behavior caused by the nonlinear resistors consisting of a parallel connected resistor with a diode.
Model
The underlying model is given by a (SISO) gradient system of the form [2]:
\[ \dot{x}(t) = \begin{pmatrix} -g(x_1(t)) - g(x_1(t) - x_2(t)) \\ g(x_1(t)-x_2(t)) - g(x_2(t)-x_3(t)) \\ \vdots \\ g(x_{k-1}(t) - x_k(t)) - g(x_k(t) - x_{x+1}(t)) \\ \vdots \\ g(x_{N-1}(t) - x_N(t)) \end{pmatrix}+\begin{pmatrix}u(t) \\ 0 \\ \vdots \\ 0 \\ \vdots \\ 0 \end{pmatrix}, \]
\[ y(t) = x_1(t), \]
where the \(g\) is a mapping \(g(x_i):\mathbb{R} \to \mathbb{R}\):
\[ g(x_i) = g_D(x_i) + x_i, \]
which combines the effect of a diode and a resistor.
Nonlinearity
The nonlinearity \(g_D\) models a diode as a nonlinear resistor, based on the Shockley model [3]:
\[ g_D(x_i) = i_S (\exp(u_P x_i) - 1), \]
with material parameters \(i_S > 0\) and \(u_P > 0\).
For this benchmark the parameters are selected as\[i_S = 1\] and \(u_P = 40\) as in [1].
Input
As external input several alternatives are presented in [4], which are listed next. A simple step function is given by: \[ u_1(t)=\begin{cases}0 & t < 4 \\ 1 & t \geq 4 \end{cases}, \]
an exponential decaying input is provided by: \[ u_2(t) = e^{-t}. \]
Additional input sources are given by conjunction of sine waves with different periods [5]: \[ u_3(t) = \sin(2\pi 50t)+\sin(2\pi 1000t), \]
\[ u_4(t) = \sin(2\pi 50t) \sin(2\pi 1000t). \]
Data
A sample procedural MATLAB implementation of order \(N\) is given by:
function [f,B,C] = nrc(N)
%% Procedural generation of "Nonlinear RC Ladder" benchmark system
% nonlinearity
g = @(x) exp(40.0*x) + x - 1.0;
A0 = sparse(N,N);
A0(1,1) = 1;
A1 = spdiags(ones(N-1,1),-1,N,N) - speye(N);
A1(1,1) = 0;
A2 = spdiags([ones(N-1,1);0],0,N,N) - spdiags(ones(N,1),1,N,N);
% input matrix
B = sparse(N,1);
B(1,1) = 1;
% output matrix
C = sparse(1,N);
C(1,1) = 1;
% vector field and output functional
f = @(x) -g(A0*x) + g(A1*x) - g(A2*x);
end
Here the nonlinear part of the vectorfield is realized in a vectorized form as a closure.
Dimensions
System structure: \[ \begin{align} \dot{x}(t) &= f(x(t)) + Bu(t) \\ y(t) &= Cx(t) \end{align} \]
System dimensions\[f : \mathbb{R}^N \to \mathbb{R}^N\], \(B \in \mathbb{R}^{N \times 1}\), \(C \in \mathbb{R}^{1 \times N}\).
Citation
To cite this benchmark, use the following references:
- For the benchmark itself and its data:
- The MORwiki Community. Nonlinear RC Ladder. MORwiki - Model Order Reduction Wiki, 2018. http://modelreduction.org/index.php/Nonlinear_RC_Ladder
@MISC{morwiki_modgyro,
author = {The {MORwiki} Community},
title = {Nonlinear RC Ladder},
howpublished = {{MORwiki} -- Model Order Reduction Wiki},
url = {http://modelreduction.org/index.php/Nonlinear_RC_Ladder},
year = {2018}
}
References
- ↑ 1.0 1.1 Y. Chen, "Model Reduction for Nonlinear Systems", Master Thesis, 1999.
- ↑ M. Condon and R. Ivanov, "Empirical balanced truncation for nonlinear systems", Journal of Nonlinear Science 14(5):405--414, 2004.
- ↑ T. Reis. "Mathematical Modeling and Analysis of Nonlinear Time-Invariant RLC Circuits", In: Large-Scale Networks in Engineering and Life Sciences. Modeling and Simulation in Science, Engineering and Technology: 125--198, 2014.
- ↑ Y. Chen and J. White, "A quadratic method for nonlinear model order reduction", Int. conference on modelling and simulation of Microsystems semiconductors, sensors and actuators, 2000.
- ↑ M. Condon and R. Ivanov, "Model Reduction of Nonlinear Systems", COMPEL 23(2): 547--557, 2004