The application of a simple microcontroller to deal with a three variable input and a single output fuzzy logic controller, with Proportional – Integral – Derivative (PID) response control built-in has been tested for an automatic voltage regulator. The fuzzifiers are based on fixed range of the variables of output voltage. The control output is used to control the wiper motor of the auto trans...

The main objectives of vehicle motion control on an automated highway system are stable and safe automatic longitudinal and/or lateral path following in a platoon of vehicles. Various controllers can be used to satisfy the same objectives, but they may require different variables to be sensed or different conditions to be met. Supervision can select a controller and switch to a different contro...

The paper investigates delay-dependent control and stability analysis for T−S fuzzy systems with a sensor delay. Based on a Lyapunov-Krasovskii function (LKF), a less conservative delay-dependent stability condition in the form of parameterized linear matrix inequalities (PLMIs) is established. In the derivation process, Jensen inequality is introduced to estimate the upper bound of the derivat...

A concept called the decomposition of multivariable control rules is presented. Fuzzy control is the application of the compositional rule of inference and it is shown how the inference of the rule base with complex rules can be reduced to the inference of a number of rule bases with simple rules. A fuzzy logic based controller is applied to a simple magnetic suspension system. The controller h...

In this paper, new non-quadratic stability conditions are derived based on the parallel distributed compensation scheme to stabilize Takagi-Sugeno (T-S) fuzzy systems. We use a non-quadratic Lyapunov function as a fuzzy mixture of multiple quadratic Lyapunov functions. The quadratic Lyapunov functions share the same membership functions with the T-S fuzzy model. The stability conditions we prop...

In this study, the self-tuning method for fuzzy PID controllers that has been developed in a previous study of the authors is implemented on PLC in order to control some standard processes formed on FEEDBACK PCS 327 Process Control Simulator. In this tuning method, the input scaling factor corresponding to the derivative coefficient and the output scaling factor corresponding to the integral co...

Brushless DC (BLDC) motors are commonly used in applications that require high reliability, high efficiency and high power-to-volume ratio such as industrial automations, manufacturing, robotics and aerospace. The speed of a brushless dc motor can be controlled in a closed loop by measuring the actual speed of the motor.PI (Proportional Integral), PID (Proportional Integral Derivative) and fuzz...

Our aim is to design a pattern classifier using fuzzy relational calculus (FRC) which was initially proposed by Pedrycz (1990). In the course of doing so, we first consider a particular interpretation of the multidimensional fuzzy implication (MFI) to represent our knowledge about the training data set. Subsequently, we introduce the notion of a fuzzy pattern vector to represent a population of...

The design of controllers for nonlinear systems in industry is a complex and difficult task. One approach which has shown promise for solving nonlinear control problems is the use of fuzzy logic control. This paper proposes a new method utilizing proportional–integral-derivative (PID) control as a hybrid fuzzy PID controller for nonlinear system. The salient feature of the proposed approach is ...