Scilab Function

armax1 - armax identification

### Sequence d'appel

  `[arc,resid]=armax1(r,s,q,y,u [,b0f])`

### Parametres

- `y` : output signal
- `u` : input signal
- `r,s,q` : auto regression orders with r >=0, s >=-1.
- `b0f` : optional parameter. Its default value is 0 and it means that the coefficient b0 must be identified. if bof=1 the b0 is supposed to be zero and is not identified
- `arc` : is tlist with type "ar" and fields a, b, d, ny, nu, sig

- `a` : is the vector [1,a1,...,a_r]
- `b` : is the vector [b0,......,b_s]
- `d` : is the vector [1,d1,....,d_q]
- `sig` : resid=[ sig*echap(1),....,];

### Description

armax1 is used to identify the coefficients of a 1-dimensional ARX process:

       A(z^-1)y= B(z^-1)u + D(z^-1)sig*e(t)
       e(t) is a 1-dimensional white noise with variance 1.
       A(z)= 1+a1*z+...+a_r*z^r; ( r=0 => A(z)=1)
       B(z)= b0+b1*z+...+b_s z^s ( s=-1 => B(z)=0)
       D(z)= 1+d1*z+...+d_q*z^q  ( q=0 => D(z)=1)

for the method, see Eykhoff in trends and progress in system identification) page 96. with z(t)=[y(t-1),..,y(t-r),u(t),..., u(t-s),e(t-1),...,e(t-q)] and coef= [-a1,..,-ar,b0,...,b_s,d1,...,d_q]' y(t)= coef'* z(t) + sig*e(t).

a sequential version of the AR estimation where e(t-i) is replaced by an estimated value is used (RLLS). With q=0 this method is exactly a sequential version of armax

### Auteur

J.-Ph.C; ;