Re: Adaptive time varying zero-order Sugeno system

Jairo Espinosa (Jairo.Espinosa@esat.kuleuven.ac.be)
Sun, 26 Jul 1998 16:30:55 +0200 (MET DST)

Rich J Lukas wrote:
>
> I have a fuzzy logic system of form
>
> if x1 is A11 and ... xm is A1m then y = f1(z)
> if x1 is A21 and ... xm is A2m then y = f2(z)
> ..
> if x1 is An1 and ... xm is Anm then y = fn(z)
>
> Y = (W1*f1(z) + ... Wn*fn(z))/(W1+W2+...Wn)
>
> where W1 = uA11*uA12... uAam. A is a fuzzy set and fi(z) is a function
> of vector z.
>
> I am not sure how to describe this system. Its not a first order Sugeno
> system since the outputs fi(z) are not functions of the inputs. Its not
> a zero order Sugeno system since the outputs are time varying, not fixed
> constants.
>
> I would like to find an adaptive method to optimize the memberships
> functions. The methods I am familiar with; lookup tables and clustering
> do not seem to apply to this problem. It there a general package, or a
> standard method for a system of this type?
>
> Thanks,
> Rich Lukas
If the outputs are time varying values which have no dependance on the
input, the values can be estimated using algorithms such as Recursive
Least Squares (RLS) or LMS.
I think matlab implements both algorithms!

Regards,

Jairo ESPINOSA
ESAT-SISTA
KULEUVEN

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