The word “Fuzzy” means hazy, blurred, confused or not clear. When it comes to binary logic, the statement is either true or false i.e. “1” or “0”. For example we say “The velocity of a body is 100 Km/h”, which may be either true or false. But in many cases we come across such situations where we cannot predict such behavior lack of clarity and the answer could be either “not sure’-“may be”-“that depends on” and so on.
On a pleasant summer day the statement “the temperature is too high”, is neither true nor false. This is a qualitative statement and signifies an opinion rather than an objective fact. On the other hand a person sitting in a snow storm on the top of a hill feels a bit cooler than a person sitting at lower height in the foothills.
It means that the real world is too complicated for precise description of certain situations, therefore approximation (fuzziness) must be introduced in order to get a traceable and reasonable model. It means there is no certainty and it all depend on the context. In this article we will see about fuzzy logic implementation in various applications such as information systems and their engineering uses.
Fuzzy logic from engineering point of view
Fuzzy logic deals with the uncertainty by attaching degree of certainty in your answer to logical questions. Fuzzy systems are widely used in commercial and practical engineering. Fuzzy logic is simple and can be easily implemented, even by a person who is not a specialist in control theory. In most cases some one with intermediate technology background could implement the fuzzy logic. The control system will not be optimal, but would be acceptable.
Fuzzy logic is not the answer to all technical problems, but mainly for the control situations, where simplicity and speed are of high priority.
Fuzzy logic control in contrast to binary logic Yes (1) and No (0), reacts more like a human being. Thus yes and No might be replaced by:
Definitely Yes
Probably Yes
May Be
Probably No
Definitely No
What Are fuzzy systems?
Fuzzy systems are knowledge-based or rule based systems. The heart of fuzzy system is a knowledge base consisting of statements like “IF-THEN”. Following statement is a fuzzy if-then rule:
IF car speed is high, THEN apply less force to the accelerator. A fuzzy system is developed on the basis of “IF-THEN” statement. Suppose we need to control the speed of a car, we have two approaches
- Develop a PID based controller
- To emulate the human drivers
Broadly speaking, human drivers use the following three types of rules, in a normal situation while driving:
- IF speed is low, THEN apply more force to accelerator
- IF speed is medium, THEN apply normal force to the accelerator
- IF speed is high, THEN apply less force to the accelerator
Where the words: low, more, medium, normal, High are characterized by membership function.
Where are fuzzy systems used and how?
Fuzzy systems are widely used in a variety of fields, ranging from control signal processing, communication, integrated circuit manufacturing, expert systems to business and medicine. However the most significant application is focused on control systems.
A typical fuzzy control system can be open loop or closed loop . When used as an open loop, the fuzzy system sets up some control parameters, and then the system operates according to these parameters. Many of consumer electronics applications are open loop. When used in a closed loop the, the fuzzy system measures the output of the process and takes control action/s on the process continuously. Such applications can be found in industries.
