it is noted that fuzzy control should not be used for the class of linear systems!

However, for study the design approaches, see these references:

Kevin M. Passino, Stephen Yurkovich, Fuzzy Control, Addison Wesley Longman, 1998.

Jacek Kluska, Analytical Methods in Fuzzy Modeling and Control, Springer-Verlag Berlin Heidelberg, 2009

I'm not quite sure about your question, but Passino book is mostly on design of fuzzy controllers. If you are interested in Neuro-fuzzy or adaptive fuzzy controllers, Jang is the best reference. 

http://scholar.google.com/citations?user=xPAxmk0AAAAJ

http://www.cs.ox.ac.uk/people/zhenyu.wang/nfs/jang95.pdf

http://www.scribd.com/doc/46265946/Neuro-Fuzzy-and-Soft-Computing-Jang-Sun-Mizutani

http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=256541&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel1%2F21%2F6499%2F00256541

In order to a good and fast introduction about that, you can visit a Mathworks website:

http://www.mathworks.com/help/fuzzy/fuzzylogiccontroller.html 

I hope it help you!

If you know the system is linear then you probably know the system model. In such case, I would use a "traditional" controller, like PID or Linear Quadratic Regulator (LQR).

If you need adaptation, you can estimate model parameters by using online system identification techniques like recursive least square.

For a basic introduction on linear model construction and control design see for instance:

http://it.mathworks.com/help/ident/ug/linear-model-structures.html

http://it.mathworks.com/help/control/index.html#linear-system-modeling

First of all , I think you should to know why you want to control linear system by nonlinear model free controller? do you have uncertainty? your system's mathematical formulation is difficult to identification? 

I think this controller is not suitable for linear systems. in linear system most of researcher used traditional (classical) controller. to adaption i think you can find the better methodology.