A Study on a New Design Method of the PD-type Fuzzy Logic Controller
Byung-Jae Choi, Seong Woo Kwak, Byung Kook Kim
Abstract
Byung-Jae Choi, Seong Woo Kwak, Byung Kook Kim
Abstract
This paper proposes a new design method for the PD(Proportional-Derivative)-type FLC(Fuzzy Logic Control). The conventional PD-type FLC is the most general type of the FLC and uses error and change-of-error as input variables of the FLC which are process state variables representing the contents of the rule-antecedent. That is, the conventional PD-type FLC generates control actions according to error and change-of-error. Then the fuzzy rule table is constructed on two-dimensional space of error and change-of-error and commonly has the skew symmetric property. This property allows us to introduce a new variable, which is called a signed distance, and it is used as only an input variable of the FLC. That is, in the proposed PD-type FLC a signed distance is used as the unique input variable of the FLC instead of two variables of error and change-of-error. Then the number of total rules is greatly reduced as well as the control performances are almost the same as the cases of the conventional PD-type FLC. These are showed by computer simulations of two examples.
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This paper proposes a new design method for the PD(Proportional-Derivative)-type FLC(Fuzzy Logic Control). The conventional PD-type FLC is the most general type of the FLC and uses error and change-of-error as input variables of the FLC which are process state variables representing the contents of the rule-antecedent. That is, the conventional PD-type FLC generates control actions according to error and change-of-error. Then the fuzzy rule table is constructed on two-dimensional space of error and change-of-error and commonly has the skew symmetric property. This property allows us to introduce a new variable, which is called a signed distance, and it is used as only an input variable of the FLC. That is, in the proposed PD-type FLC a signed distance is used as the unique input variable of the FLC instead of two variables of error and change-of-error. Then the number of total rules is greatly reduced as well as the control performances are almost the same as the cases of the conventional PD-type FLC. These are showed by computer simulations of two examples.
Key concepts: Variable (mathematics), Control theory (sociology), Type (biology), Fuzzy logic, Computer science, Mathematics, Algorithm, Controller (irrigation)