An Introduction to Fuzzy Control - Fuzzy Logic: An Introductory Course for Engineering Students - page 171

Chapter 8
An Introduction to Fuzzy Control
8.1 Introduction
Probably one of the most successful developments of fuzzy reasoning, from the
industrial point of view, is the design of fuzzy control systems, also called linguistic
control systems, or simpler, the applications of fuzzy controllers.
A fuzzy control system is based on a set of fuzzy “if-then” rules of behavior
that consider the kind of stimuli from the environment, that the system will receive,
meanwhile at a given time, the values of these stimuli represent the facts, that the
rules have to consider to offer proper actions.
As it has been proved from its origins, fuzzy control should be useful in situations
where (a) There is no acceptable mathematical model for the plant, (b) There are
experienced human operators who can satisfactorily control the plant and provide
qualitative control rules in terms of vague and fuzzy sentences, and (c) In applica-
tions where there is a large uncertainty or unknown variation in plant parameters and
structures. In this cases, fuzzy control can be considered as a model-free approach
and it does not require a mathematical model of the objective plant. It is referred to
as a knowledge-based control approach, and it makes an effective use of all available
information related to the system, from sensors which provide numerical measure-
ments of key variables to human experts who provide linguistic descriptions about
the system and control instructions.
However, currently fuzzy control approach is mainly devoted to model-based
methods. On the one hand, there are cases in which operators cannot precisely tell
their action in a particular situation, or simply, operator's control may not be always
optimal with respect to some performance objective. In this sense, identification for
obtaining fuzzy models from process data is very important.
On the other hand, although the uncertainty in dynamic systems can be handled
using appropriate control actions (e.g., their sensitivity to external disturbances and
parameter changes can be reduced stabilizing an unstable system, or the systems
dynamic behavior could be modified speeding up a slow system), the application
of control action over a system can potentially destabilize stable plants. Thus,