📄 lv45.m
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function [T,X]=lv45(t0,tf,x0,initfun,delay,eps1,gamma1,gamma2,F1,F2,tol)
%LV45 Solves the Lotke-Volterra systems with delay of kind
%
% x1`(t)=[ eps1-gamma1*x2(t)-integral(-tau,0,F1(s)*y2(s))ds]*x1(t)
% x2`(t)=[-eps1+gamma2*x1(t)+integral(-tau,0,F2(s)*y1(s))ds]*x2(t)
%
% LV45 integrates a Lotke-Volterra system of functional-differential
% equations using 4th and 5th order Runge-Kutta formulas
% as well interpolation by degenerate cubic splines.
% [T,X] = lv45(t0,tf,x0,initfun,delay,eps1,gamma1,gamma2,F1,F2)
% integrates the system of functional-differential equations
% over the segment from t0 to tf, with the initial value
% x0 = x(t0) and the initial function y0(s) = x(t0+s) for s<0.
% [T,X] = lv45(t0,tf,x0,initfun,delay,eps1,gamma1,gamma2,F1,F2,tol)
% uses tolerance tol.
% Invoked without left-hand arguments LV45 produces the graph.
%
% INPUT:
% t0 - Initial value of t.
% tf - Final value of t.
% x0 - Initial value column-vector.
% initfun - String variable with column-vector of initial
% function depending on variable s.
% delay - Constant delay tau.
% eps1 - Scalar parameter.
% gamma1 - Scalar parameter.
% gamma2 - Scalar parameter.
% F1,F2 - String variables with scalar functions F1(s), F2(s).
% tol - The desired accuracy. (by default: tol=1.e-4)
%
% OUTPUT:
% T - Returned integration time points (column-vector).
% X - Returned solution, one solution vector per T-value.
%
% The result can be displayed by: plot(T, X).
%
% See also dde45.
% Check input parameters
if tf <= t0
error('The final point of integration must be greater than initial one');
end;
if delay < 0
error('Delay must be nonnegative constant');
end;
if (size(x0)~=[2, 1])
error('Initial state x0 must be two-element column-vector');
end;
s=t0;
if (size(eval(initfun))~=[2, 1])
error('Initial function must be two-element column-vector');
end;
% The Fehlberg coefficients:
alpha = [1/4 3/8 12/13 1 1/2]';
beta = [ [ 1 0 0 0 0 0]/4
[ 3 9 0 0 0 0]/32
[ 1932 -7200 7296 0 0 0]/2197
[ 8341 -32832 29440 -845 0 0]/4104
[-6080 41040 -28352 9295 -5643 0]/20520 ]';
gamma = [ [902880 0 3953664 3855735 -1371249 277020]/7618050
[ -2090 0 22528 21970 -15048 -27360]/752400 ]';
pow = 1/5;
if nargin <11, tol = 1.e-4; end
% Initialization
t1 = t0;
hmax = (tf - t1)/16;
h = hmax/8;
x = x0(:);
f = zeros(length(x),6);
chunk = 128;
tout = zeros(chunk,1);
xout = zeros(chunk,length(x));
k = 1;
tout(k) = t1;
xout(k,:) = x.';
% The main loop
while (t1 < tf) & (t1 + h > t1)
if t1 + h > tf, h = tf - t1; end
% Compute the slopes
f(:,1)=[(eps1-gamma1*x(2)-...
int1(-delay,0,t1,tout(1:k),xout(1:k,:),initfun,F1,2))*x(1);
(-eps1+gamma2*x(1)+...
int1(-delay,0,t1,tout(1:k),xout(1:k,:),initfun,F2,1))*x(2)];
for j = 1:5
t=t1+alpha(j)*h;
x1=x+h*f*beta(:,j);
f(:,j+1)=[(eps1-gamma1*x1(2)-...
int1(-delay,0,t,tout(1:k),xout(1:k,:),initfun,F1,2))*x1(1);
(-eps1+gamma2*x1(1)+...
int1(-delay,0,t,tout(1:k),xout(1:k,:),initfun,F2,1))*x1(2)];
end
% Estimate the error and the acceptable error
delta = norm(h*f*gamma(:,2),'inf');
tau = tol*max(norm(x,'inf'),1.0);
% Update the solution only if the error is acceptable
if delta <= tau
t1 = t1 + h;
x = x + h*f*gamma(:,1);
k = k+1;
if k > length(tout)
tout = [tout; zeros(chunk,1)];
xout = [xout; zeros(chunk,length(x))];
end
tout(k) = t1;
xout(k,:) = x.';
end
% Update the step size
if delta ~= 0.0
h = min(hmax, 0.8*h*(tau/delta)^pow);
end
end
if (t1 < tf)
disp('Singularity likely.')
t1
end
% Plot Graph
if nargout == 0
plot(tout(1:k),xout(1:k,:));
return;
end;
T = tout(1:k);
X = xout(1:k,:);
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