Adaptative high-gain extended Kalman filter and applications

tel-00559107, version 1 - 24 Jan 2011
C.4 Innovation Computational Functions C Code
− to update the vector of past values of u from [u(t−d), ..., u(t−δ)] to [u(t−d+δ), ..., u(t)].
function name innovation number of zero crossing
surfaces
0
implicit n initial discrete state ⊛
input port size 5 real parameter vector []
output port size 1 integer parameter vector
[]
input event port size [1] initial firing vector []
output event port size [] direct feed through y
initial continuous state [] time dependence n
#include
#include
#include
/∗ i n p u t = [Y;V; z ( t−d ) ] ∗/
void f u n c t i o n ( double ∗ , double ∗) ;
Table C.3: Arguments of the Innovation Function.
⊛ = a null vector of length 2*(d/Dt)+2, (i.e. 22).
void i n n o v a t i o n ( s c i c o s b l o c k ∗ block , int f l a g )
{
double d=1,Dt =0.1;
int n=10; /∗ ( d/Dt ) ; ∗/ /∗ Auto conversion d o u b l e −> i n t ∗/
int nz , i , j ;
/∗ Remark t h a t t h e r e i s NO TEST: Dt has to d i v i d e d ! ! ∗/
nz=2∗n+2;
if ( f l a g ==4)
{/∗ INITIALISATION ∗/
/∗ Already done . I t i s i m p o s s i b l e to change t h e dimension o f ..
t h e s t a t e space from here ∗/
}
else if( f l a g ==1| f l a g ==6)
{/∗ OUTPUT ∗/
block−>outptr [ 0 ] [ 0 ] = block−>z [ nz −1];}
else if( f l a g ==2)
{/∗ DERIVATIVE ∗/
/∗ d e l a y e d i n p u t ( index 2 ,3 ,4) ∗/
double I , wr=block−>i n p t r [ 0 ] [ 3 ] , Tl=block−>i n p t r [ 0 ] [ 4 ] ;
if ( block−>i n p t r [ 0 ] [ 2 ] > 0 . 5 ) { I=block−>i n p t r [ 0 ] [ 2 ] ; }
else{ I =0.5;}
double Y=block−>i n p t r [ 0 ] [ 0 ] , V=block−>i n p t r [ 0 ] [ 1 ] ;
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