MATLAB Examples

# Demo3: Constraints Placed Not at Nodes

The function dopGenConstrained has the possability of placing constraints at points which are nodes in the basis functions, i.e. at points where the polynomials are nor evaluated. This can be a hlepfull procedure in solving boundary value problems which may otherwise be singular at a point.

(c) 2013 Paul O'Leary and Matthew Harker Institute for Automation University of Leoben A-8700 Leoben Austria

URL: automation.unileoben.ac.at Email: office@harkeroleary.org

## Contents

close all; clear all; % % Set some defaults % FontSize = 12; set(0,'DefaultaxesFontName','Times'); set(0,'DefaultaxesFontSize',FontSize); set(0,'DefaulttextFontName','Times'); set(0,'DefaulttextFontSize',FontSize); set(0,'DefaultfigurePaperType','A4'); set(0,'DefaultTextInterpreter', 'latex'); 

## Define the Number of Basis Functions and x

nrBfs = 10; % % Generate the vector of x values % nrPts = 15; x = dopNodes( nrPts, 'Gramends'); 

## Definig the Triplets for the Constraints

t1 = [0,1,1]; t2 = [1,1,0]; t3 = [0,-0.35,0]; % % Concatinate the triplets to form an array of triplest which define all % the constraints. % T = [t1; t2; t3]; 

## Call dopGenConstrained

The function dopGenConstrained computes a particular solution y_p and determine a set of basis functions Bh suche that the homogeneous solution y_h = Bh * \beta. In this manner the possible solutions to y are of the form: y = y_p + y_h = y_p + Bh * \beta.

[yp, Bh, S] = dopGenConstrained( x, nrBfs, T ); 

## Display Prticular Solutions

Here the minimum degree and minimum norm psrticular solutions are displayed.

fig1 = figure; plot(x, yp, 'b'); hold on; xlabel( 'Support' ); ylabel( '$$y_p(x)$$' ); grid on; plot( x, zeros( size(x)), 'ko', 'MarkerFaceColor', 'w'); legend( 'Min degree', 'Nodes', 'Location', 'NorthWest'); 
[nt, mt] = size( T ); for k = 1:nt if T(k,1) == 0 plot( T(k,2), T(k,3), 'ko', 'MarkerFaceColor', 'k'); else plot( T(k,2), 0, 'ko', 'MarkerFaceColor', 'k'); end; end; % title( 'Note the constraint not located at a node of the basis functions'); % 

## Display the Homogeneously Constrained Basis Functions

The basis functions are interpolated to show them more smoothly

Extract the recurrence coefficients from the structure S

rC = S.rC; 

## Interpolate the basis functions

This figure shows the homogeneously constrained basis functions and the nodes at which the basis functions were computed prior to interpolation. Note the constraints are located at points which do not correspond to nodes.

noInt = 200; xi = linspace( x(1), x(end), noInt )'; [~, Bi] = dopInterpolate( ones( nrBfs, 1), rC, xi ); Bih = Bi * S.R; % fig1 = figure; plot( xi, Bih, 'k'); xlabel( 'Support' ); ylabel( '$$B_h(x)$$' ); grid on; hold on; plot( x, zeros( size(x)), 'ko', 'MarkerFaceColor', 'w'); % [nt, mt] = size( T ); for k = 1:nt if T(k,1) == 0 plot( T(k,2), T(k,3), 'ko', 'MarkerFaceColor', 'k'); else plot( T(k,2), 0, 'ko', 'MarkerFaceColor', 'k'); end; end;