A fuzzy controller can be seen as an algorithm that, given a fuzzy set (input) and a set of linguistic rules, computes the degree of possibility of every control value. Using a valid and complete proof system for possibilistic logic, we will prove that fuzzy controllers enjoy the following property: every possibility measure that satisfies the degrees of possibility of the input and of the linguistic rules also satisfies, for every control value, the degree of possibility computed by the fuzzy controller. We will call such property the coherence between input, task description and output. A general definition of coherent function is given, and we will see that coherent functions form a class of functions that properly contains fuzzy controllers. Moreover, we will present an application of coherent control functions to a task different from control, namely localization in mobile robotics.
Coherent functions in autonomous systems
Sossai Claudio;Chemello Gaetano
2003
Abstract
A fuzzy controller can be seen as an algorithm that, given a fuzzy set (input) and a set of linguistic rules, computes the degree of possibility of every control value. Using a valid and complete proof system for possibilistic logic, we will prove that fuzzy controllers enjoy the following property: every possibility measure that satisfies the degrees of possibility of the input and of the linguistic rules also satisfies, for every control value, the degree of possibility computed by the fuzzy controller. We will call such property the coherence between input, task description and output. A general definition of coherent function is given, and we will see that coherent functions form a class of functions that properly contains fuzzy controllers. Moreover, we will present an application of coherent control functions to a task different from control, namely localization in mobile robotics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.