This paper presents genetic algorithms (GAs) to perform the optimal design of an auto-tuning fuzzy proportional-integral-derivative (PID) controller and to determine the minimal number of fuzzy rules simultaneously. Different from PID controllers with fixed gains, the fuzzy PID controller is expressed in terms of fuzzy rules, in which the input variables are the error signals and their derivati...

Objective of this paper is to design various controllers for a temperature process control. PID controller is the well known and most widely used in the industries. Internal Model Control (IMC) has become the leading form of advanced control in the process industry. Modified form of IMC-PID and Fuzzy PID Controllers are designed for First Order Plus Dead Time (FOPTD) process model. The comparat...

In this paper we have designed a DC motor whose speed can be controlled using PID controller. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are adjusted according to FUZZY LOGIC. First, the fuzzy logic controller is designed according to fuzzy rules so that the systems are fundamentally robust. There are 25 fuzzy rules for self-tuning of each parameter of PID ...

Industry applications mainly use linear PID algorithms might deliver an insufficient performance dealing with nonlinear operating systems. A fuzzy PID controller results in a nonlinear control surface which can be adjusted to a controlled plant by rule based modification, nonlinear membership function application and inference rule selection. The tuning process is one of the most difficult step...

According to the nonlinear and time-varying uncertainty characteristics of direct drive electrohydraulic servo control system, a self-tuning fuzzy PID control method with speed change integral and differential ahead optimizing operator is put forward by combining fuzzy inference and traditional PID control in this paper. The rule of fuzzy logic is designed, the membership function of the fuzzy ...

Considering complex factors of affecting ambient temperature in Aircraft cabin, and some shortages of traditional PID control like the parameters difficult to be tuned and control ineffective, this paper puts forward the intelligent PID algorithm that makes fuzzy logic method and neural network together, scheming out the fuzzy neural net PID controller. After the correction of the fuzzy inferen...

Because simulation turntable servo system is highly nonlinear and uncertainty plants, a fuzzy neural network PID controller is proposed based on the Radial Basis Function (RBF). Up to now, various kinds of nonlinear PID controllers have been designed in order to satisfactorily control this system and some of them applied in actual systems with different degrees. Given this background, the step ...

Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains compared to proportional-integral-derivative (PID) controllers. This research paper proposes a design procedure and a tuning procedure that carries tuning rules from the PID domain over to fuzzy single-loop controllers. The idea is to start with a tuned, conventional PID controller, replace it with an equiva...

Aiming at the characteristics of a certain thermostat control system such as non-linear and time varying, combining the traditional PID controller with modern fuzzy control theory, and using the EP1C12 FPGA as the core controller, the fuzzy adaptive PID temperature controller is going to be designed and achieved. The deviation and deviation rate are the inputs of fuzzy PID controller. PID param...

In this paper, a PID fuzzy controller structure is presented. To be successful in implementing fuzzy PID controllers in large applications we must also considered their operating principles. Fuzzy logic controllers are based on empirical control rules. A study case for the validation of the proposed tunning mechanism is presented and analyzed with control application for a synchronous generator...