seminar on fuzzy controller

INTRODUCTION

Conventional Proportional Integral Derivative(PID) controllers have been well developed & applied , are extensively used for industrial automation & process control. PID controllers do not work well for non linear systems, complex & vague systems. To overcome this difficulties autotuning & adaptive PID controllers employing fuzzy logic are developed.

FUZZY CONTROLLER

PID controllers are designed for linear systems and they provide a preferable cost/benefit ratio. However, the presences of nonlinear effects limit their performances. Fuzzy controllers are successful applied to non-linear system because of their knowledge based nonlinear structural characteristics. Hybridization of these two controller structures comes to ones mind immediately to exploit the beneficial sides of both categories

FUZZY PID CONTROLLER FEATURES

Has same linear structure ,self tuned control gains.

Integral & derivative gains for non linear function of input signals.

Fuzzification & defuzzification rules are embedded in final formulation of fuzzy control.

FUZZY PI + D CONTROLLERS

Fuzzy PI+D controller is a digital controller

Arrangement is often desirable if the reference input contains discontinuities

FUZZY PI + D CONTROLLERS

BLOCK DIAGRAM OF HYBRID TYPE FUZZY PIDCONTROLLER

CLASSIFICATION OF FUZZY PID CONTROLLERS

“THREE-TERM” FUNCTIONALITIES ARE

Proportional term is providing an overall control action proportional to the error signal

Integral term is reducing steady-state errors through low-frequency compensation by an integrator

Derivative term is improving transient response through high-frequency compensation by a differentiator

FUZZY PID CONTROLLER STRUCTURE

FUZZY PI CONTROLLER

Output of the conventional analog PI controller in the frequency domain “s” as can be verified easily

With a fuzzy control action , we arrive at

KuPI is a constant control gain

FUZZY D CONTROLLER

D controller in the PID control system,is given by

Incremental control output of the fuzzy D controller

FUZZY PI D CONTROLLER

Overall fuzzy PI D control law can be obtained by algebraically summing the fuzzy PI control law and the fuzzy D law

FUZZY CONTROLLERS DESIGN

Fuzzification

Fuzzy Control Rules

Defuzzification

FUZZIFICATION

Fuzzify the PI and D components of the PID control system individually and then combine the desired fuzzy control rules for each of them, taking into consideration the overall PI D fuzzy control law. The input and output membership functions of the PI component

MEMBERSHIP FUNCTIONS FOR THE PI COMPONENT. (A) INPUT MEMBERSHIPFUNCTIONS. (B) OUTPUT MEMBERSHIP FUNCTIONS

MEMBERSHIP FUNCTIONS FOR THE D COMPONENT. (A) INPUT MEMBERSHIP FUNCTIONS. (B) OUTPUT MEMBERSHIP FUNCTIONS

FUZZY CONTROL RULES

Using the aforementioned membership functions, the following control rules are established for the fuzzy PI controller.

FUZZY CONTROL RULES

Membership functions of the fuzzy D controller, the following control rules are used for the D component

DEFUZZIFICATION

For both fuzzy PI and D controllers, the centroidformula is employed to defuzzify the incremental control of the fuzzy control law

The two membership functions then overlap and form the third-dimensional picture.

OUTPUT RESPONSE OF THE FUZZY PID CONTROLLER.

CONCLUSION

A novel design methodology that blends the classical PID and the fuzzy controllers in an intelligent way is thus a new intelligent hybrid controller. Many simulations done on various processes using the new hybrid fuzzy PID controller have provided ‘better’ system responses in terms of transient and steady-state performances. The proposed hybrid structure has provided a good and effective performance on system response.