【正文】 products of decades of development and theoretical analysis, and are highly effectiveIf PID and other traditional control systems are so welldeveloped, why bother with fuzzy control? It has some advantages. In many cases, the mathematical model of the control process may not exist, or may be too expensive in terms of puter processing power and memory, and a system based on empirical rules may be more effective. Furthermore, fuzzy logic is well suited to lowcost implementations based on cheap sensors, lowresolution analogtodigital converters, and 4bit or 8bit onechip microcontroller chips. Such systems can be easily upgraded by adding new rules to improve performance or add new features. In many cases, fuzzy control can be used to improve existing traditional controller systems by adding an extra layer of intelligence to the current control method. Fuzzy control in detail Fuzzy controllers are very simple conceptually. They consist of an input stage, a processing stage, and an output stage. The input stage maps sensor or other inputs, such as switches, thumbwheels, and so on, to the appropriate membership functions and truth values. The processing stage invokes each appropriate rule and generates a result for each, then bines the results of the rules. Finally, the output stage converts the bined result back into a specific control output valueThe most mon shape of membership functions is triangular, although trapezoidal and bell curves are also used, but the shape is generally less important than the number of curves and their placement. From three to seven curves are generally appropriate to cover the required range of an input value, or the universe of discourse in fuzzy jargonAs discussed earlier, the processing stage is based on a collection of logic rules in the form of IFTHEN statements, where the IF part is called the antecedent and the THEN part is called the consequent This rule uses the truth value of the temperature input, which is some truth value of cold, to generate a result in the fuzzy set for the heater output, which is some value of high. This result is used with the results of other rules to finally generate the crisp posite output. Obviously, the greater the truth value of cold, the higher the truth value of high, though this does not necessarily mean that the output itself will be set to high since this is only one rule among many. In some cases, the membership functions can be modified by hedges that are equivalent to adjectives. Common hedges include about, near, close to, approximately, very, slightly, too, extremely, and somewhat. These operations may have precise definitions, though the definitions can vary considerably between different implementations. Very, for one example, squares membership functions。 a conductivity sensor, to measure detergent level from the ions present in the wash。 optical fuzzy systems。 Fuzzy Control From Wikipedia20 November 2021 Overview Fuzzy logic is widely used in machine control. The term itself inspires a certain skepticism, sounding equivalent to halfbaked logic or bogus logic, but the fuzzy part does not refer to a lack of rigour in the method, rather to the fact that the logic involved can deal with concepts that cannot be expressed as true or false but rather as partially true. Although geic algorithms and neural works can perform just as well as fuzzy logic in many cases, fuzzy logic has the advantage that the solution to the problem can be cast in terms that human operators can understand, so that their experience can be used in the design of the controller. This makes it easier to mechan