Analytical structure for a fuzzy PID controller is introduced by employing two fuzzy sets for each of the three input variables and four fuzzy sets for the output variable. This structure is derived via left and right trapezoidal membership functions for inputs, trapezoidal membership functions for output, algebraic product triangular norm, bounded sum triangular co-norm, Mamdani minimum infere...

Abstract: In this paper, we present the design and simulation of a new fuzzy logic supervisory control approach that is designed to improve the performance of a PID controlled magnetic levitation system, such systems are inherently unstable and require means of control to stabilize their operation; the fuzzy logic controller continuously monitors system variables (error signal, and its derivati...

A novel intelligent multiple-controller framework incorporating a fuzzy-logic based switching supervisor is presented for adaptive control of non-linear systems . The proposed methodology provides the designer with an automated choice of using either: a conventional Proportional-Integral-Derivative (PID) controller, a PID structure based pole (only) placement controller, or a PID structure base...

A novel design a fuzzy proportional integral derivative (PID) controller is using Matlab and programmable logic controllers (PLCs) for a set point voltage control problem in the automatic voltage regulator (AVR) system. The controller objective is to maintain the terminal voltage all the time under any loads and operational conditions by attaining to the desired range via the regulation of the ...

Fuzzy PI controllers are using in the place of linear PI controller with success in process control, assuring better control quality criteria. The paper presents some methods, with a higher grade of generality, to design PI fuzzy controllers, to assure internal and external stability to control systems and better control quality criteria. Families of input-output transfer characteristics and ga...

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...

In the sewage treatment system, the dissolved oxygen concentration control, due to its nonlinear, time-varying, large time delay and uncertainty, is difficult to establish the exact mathematical model. While the conventional PID controller only works with good linear not far from its operating point, it is difficult to realize the system control when the operating point far off. To solve the ab...

: In this paper we used transfer function of second order of separately excited dc motor and compare their performance of speed regulation using PID controller and GA based hybrid fuzzy controller. In this paper our approached to tune the fuzzy logic controller using genetic algorithm. Fuzzy logic controller tuned by the lesser number of design parameter and all the control strategies utilize. ...

According to the character of the volume-lag of the controlled process of three-tank-system, Smith predictor was adopted to compensate three-tank-system fuzzy adaptive control system. Fuzzy adaptive Smith predictive control system is composed with Smith predictor and fuzzy adaptive controller. The PID parameters were setting on line. This algorithm uses fuzzy adaptive PID control to improve the...

In this paper, hysteretic behavior modeling, system identification and control of a mechanism that is actuated by shape memory alloy (SMA) wires are presented. The mechanism consists of two airfoil plates and the rotation angle between these plates can be changed by SMA wire actuators. This mechanism is used to identify the unknown parameters of a hysteresis model. Prandtl–Ishlinskii method is ...