Fehlberg's 3rd and 4th Order Embedded Runge-Kutta Method

Function List

C Source

////////////////////////////////////////////////////////////////////////////////
// File: embedded_fehlberg_3_4.c                                              //
// Routines:                                                                  //
//    Embedded_Fehlberg_3_4                                                   //
////////////////////////////////////////////////////////////////////////////////

////////////////////////////////////////////////////////////////////////////////
//                                                                            //
//  Description:                                                              //
//     The Runge-Kutta-Fehlberg method is an adaptive procedure for approxi-  //
//     mating the solution of the differential equation y'(x) = f(x,y) with   //
//     initial condition y(x0) = c.  This implementation evaluates f(x,y) five//
//     times per step using embedded third order and fourth order Runge-Kutta //
//     estimates to estimate the not only the solution but also the error.    //
//     The next step size is then calculated using the preassigned tolerance  //
//     and error estimate.                                                    //
//     For step i+1,                                                          //
//        y[i+1] = y[i] +  h * ( 229 / 1470 * k1 + 1125 / 1813 * k3           //
//                              + 13718 / 81585 * k4 + 1 / 18 * k5 )          //
//     where                                                                  //
//     k1 = f( x[i],y[i] ),                                                   //
//     k2 = f( x[i]+2h/7, y[i] + 2/7h*k1 ),                                   //
//     k3 = f( x[i]+7h/15, y[i]+h*(77/900 k1 + 343/900 k2) ),                 //
//     k4 = f( x[i]+35h/38, y[i]+h*(805/1444 k1 - 77175/54872 k2              //
//                                                     + 97125/54872 k3) ),   //
//     k5 = f( x[i]+h, y[i]+h*(79/490 k1 + 2175/3626 k3 + 2166/9065 k4)),     //
//     x[i+1] = x[i] + h.                                                     //
//                                                                            //
//     The error is estimated to be                                           //
//        err = h * ( - 888 k1 + 3375 k3 - 11552 k4 + 9065 k5 ) / 163170      //
//     The step size h is then scaled by the scale factor                     //
//         scale = 0.8 * | epsilon * y[i] / [err * (xmax - x[0])] | ^ 1/3     //
//     The scale factor is further constrained 0.125 < scale < 4.0.           //
//     The new step size is h := scale * h.                                   //
////////////////////////////////////////////////////////////////////////////////

#include 

#define max(x,y) ( (x) < (y) ? (y) : (x) )
#define min(x,y) ( (x) < (y) ? (x) : (y) )

#define ATTEMPTS 12
#define MIN_SCALE_FACTOR 0.125
#define MAX_SCALE_FACTOR 4.0
#define ORDER 3.0

static double Runge_Kutta(double (*f)(double,double), double *y, double x,
                                                                   double h);

////////////////////////////////////////////////////////////////////////////////
// int Embedded_Fehlberg_3_4( double (*f)(double, double), double y[],        //
//       double x, double h, double xmax, double *h_next, double tolerance )  //
//                                                                            //
//  Description:                                                              //
//     This function solves the differential equation y'=f(x,y) with the      //
//     initial condition y(x) = y[0].  The value at xmax is returned in y[1]. //
//     The function returns 0 if successful or -1 if it fails.                //
//                                                                            //
//  Arguments:                                                                //
//     double *f  Pointer to the function which returns the slope at (x,y) of //
//                integral curve of the differential equation y' = f(x,y)     //
//                which passes through the point (x0,y0) corresponding to the //
//                initial condition y(x0) = y0.                               //
//     double y[] On input y[0] is the initial value of y at x, on output     //
//                y[1] is the solution at xmax.                               //
//     double x   The initial value of x.                                     //
//     double h   Initial step size.                                          //
//     double xmax The endpoint of x.                                         //
//     double *h_next   A pointer to the estimated step size for successive   //
//                      calls to Runge_Kutta_Fehlberg.                        //
//     double tolerance The tolerance of y(xmax), i.e. a solution is sought   //
//                so that the relative error < tolerance.                     //
//                                                                            //
//  Return Values:                                                            //
//     0   The solution of y' = f(x,y) from x to xmax is stored y[1] and      //
//         h_next has the value to the next size to try.                      //
//    -1   The solution of y' = f(x,y) from x to xmax failed.                 //
//    -2   Failed because either xmax < x or the step size h <= 0.            //
//                                                                            //
////////////////////////////////////////////////////////////////////////////////
//                                                                            //
int Embedded_Fehlberg_3_4( double (*f)(double, double), double y[], double x,
                   double h, double xmax, double *h_next, double tolerance ) {

   static const double err_exponent = 1.0 / ORDER;
   double scale;
   double temp_y[2];
   double err;
   double yy;
   int i;
   int last_interval = 0;
   
      // Verify that the step size is positive and that the upper endpoint //
      // of integration is greater than the initial enpoint.               //

   if (xmax < x || h <= 0.0) return -2;
   
       // If the upper endpoint of the independent variable agrees with the //
       // initial value of the independent variable.  Set the value of the  //
       // dependent variable and return success.                            //

   *h_next = h;
   y[1] = y[0];
   if (xmax == x) return 0; 

       // Insure that the step size h is not larger than the length of the //
       // integration interval.                                            //
  
   h = min(h, xmax - x);

        // Redefine the error tolerance to an error tolerance per unit    //
        // length of the integration interval.                            //

   tolerance /= (xmax - x);

        // Integrate the diff eq y'=f(x,y) from x=x to x=xmax trying to  //
        // maintain an error less than tolerance * (xmax-x) using an     //
        // initial step size of h and initial value: y = y[0]            //

   temp_y[0] = y[0];
   while ( x < xmax ) {
      scale = 1.0;
      for (i = 0; i < ATTEMPTS; i++) {
         err = fabs(Runge_Kutta(f, temp_y, x, h));
         if (err == 0.0) { scale = MAX_SCALE_FACTOR; break; }
         yy = (temp_y[0] == 0.0) ? tolerance : fabs(temp_y[0]);
         scale = 0.8 * pow( tolerance * yy /  err , err_exponent );
         scale = min( max(scale,MIN_SCALE_FACTOR), MAX_SCALE_FACTOR);
         if ( err < ( tolerance * yy ) ) break;
         h *= scale;
         if ( x + h > xmax ) h = xmax - x;
         else if ( x + h + 0.5 * h > xmax ) h = 0.5 * h;
      }
      if ( i >= ATTEMPTS ) { *h_next = h * scale; return -1; };
      temp_y[0] = temp_y[1];         
      x += h;
      h *= scale;
      *h_next = h;
      if ( last_interval ) break;
      if (  x + h > xmax ) { last_interval = 1; h = xmax - x; }
      else if ( x + h + 0.5 * h > xmax ) h = 0.5 * h;
   }
   y[1] = temp_y[1];
   return 0;
}


////////////////////////////////////////////////////////////////////////////////
//  static double Runge_Kutta(double (*f)(double,double), double *y,          //
//                                                       double x0, double h) //
//                                                                            //
//  Description:                                                              //
//     This routine uses Fehlberg's embedded 3rd and 4th order methods to     //
//     approximate the solution of the differential equation y'=f(x,y) with   //
//     the initial condition y = y[0] at x = x0.  The value at x + h is       //
//     returned in y[1].  The function returns err / h ( the absolute error   //
//     per step size ).                                                       //
//                                                                            //
//  Arguments:                                                                //
//     double *f  Pointer to the function which returns the slope at (x,y) of //
//                integral curve of the differential equation y' = f(x,y)     //
//                which passes through the point (x0,y[0]).                   //
//     double y[] On input y[0] is the initial value of y at x, on output     //
//                y[1] is the solution at x + h.                              //
//     double x   Initial value of x.                                         //
//     double h   Step size                                                   //
//                                                                            //
//  Return Values:                                                            //
//     This routine returns the err / h.  The solution of y(x) at x + h is    //
//     returned in y[1].                                                      //
//                                                                            //
////////////////////////////////////////////////////////////////////////////////

static const double a2 = 2.0 / 7.0;
static const double a3 = 7.0 / 15.0;
static const double a4 = 35.0 / 38.0;

static const double b31 = 77.0 / 900.0;
static const double b32 = 343.0 / 900.0;
static const double b41 = 805.0 / 1444.0;
static const double b42 = -77175.0 / 54872.0;
static const double b43 = 97125.0 / 54872.0;
static const double b51 = 79.0 / 490.0;
static const double b53 = 2175.0 / 3626.0;
static const double b54 = 2166.0 / 9065.0;

static const double c1 = 229.0 / 1470.0;
static const double c3 = 1125.0 / 1813.0;
static const double c4 = 13718.0 / 81585.0;
static const double c5 = 1.0 / 18.0;

static const double d1 = -888.0 / 163170.0;
static const double d3 = 3375.0 / 163170.0;
static const double d4 = -11552.0 / 163170.0;
static const double d5 = 9065.0 / 163170.0;

//                                                                            //
////////////////////////////////////////////////////////////////////////////////
//                                                                            //

static double Runge_Kutta(double (*f)(double,double), double *y, double x0,
                                                                   double h) {
   
   double k1, k2, k3, k4, k5;
   double h2 = a2 * h;

   k1 = (*f)(x0, *y);
   k2 = (*f)(x0+h2, *y + h2 * k1);
   k3 = (*f)(x0+a3*h, *y + h * ( b31*k1 + b32*k2) );
   k4 = (*f)(x0+a4*h, *y + h * ( b41*k1 + b42*k2 + b43*k3) );
   k5 = (*f)(x0+h,  *y + h * ( b51*k1 + b53*k3 + b54*k4) );
   *(y+1) = *y +  h * (c1*k1 + c3*k3 + c4*k4 + c5*k5);
   return  d1*k1 + d3*k3 + d4*k4 + d5*k5;
}