scholarly journals Modelling and Controller Design for Non- Linear Two Tank Interacting System

2020 ◽  
Vol 9 (6) ◽  
pp. 82-85
Keyword(s):  
Fuzzy Logic ◽  
Comparative Study ◽  
Mathematical Modelling ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Linear Process ◽  
Matlab Simulink ◽  
Non Linear ◽  
And Control

This paper explains the mathematical modelling and controller design of Two Tank Interacting System (TTIS) for a non-linear process. To design the non-linear process using Matlab Simulink and control the process using conventional PID controller and Fuzzy Logic Controller (FLC). A comparative study was conducted extensively made to examine which controller suits well for the non-linear process through the response observed.

scholarly journals Optimal PID and fuzzy logic based position controller design of an overhead crane using the Bees Algorithm

2021 ◽  
Vol 3 (10) ◽  
Author(s):  
Esmael Adem Esleman ◽  
Gürol Önal ◽  
Mete Kalyoncu
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Optimization Method ◽  
Industrial Applications ◽  
Bees Algorithm ◽  
Membership Functions ◽  
Overhead Crane ◽  
Target Values

AbstractDifferent industrial applications frequently use overhead cranes for moving and lifting huge loads. It applies to civil construction, metallurgical production, rivers, and seaports. The primary purpose of this paper is to control the motion/position of the overhead crane using a PID controller using Genetic Algorithms (GA) and Bee Algorithms (BA) as optimization tools. Moreover, Fuzzy Logic modified PID Controller is applied to obtain better controller parameters. The mathematical model uses an analytical method, and the PID model employs Simulink in MATLAB. The paper presents the PID parameters determination with a different approach. The development of membership functions, fuzzy rules employ the Fuzzy Logic toolbox. Both inputs and outputs use triangular membership functions. The result shows that the optimized value of the PID controller with the Ziegler-Nichols approach is time-consuming and will provide only the initial parameters. However, PID parameters obtained with the optimization method using GA and BA reached the target values. The results obtained with the fuzzy logic controller (0.227% overshoot) show improvement in overshoot than the conventional PID controller (0.271% overshoot).

scholarly journals PID and Fuzzy Logic Controller Design for Balancing Robot Stabilization

2018 ◽  
pp. 1-10
Keyword(s):  
Fuzzy Logic ◽  
Tilt Angle ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Controller Design ◽  
Point Of View ◽  
Relative Advantage ◽  
Balancing Robot ◽  
Time Required

This paper addresses the problem of position control and stabilization for the two wheeled balancing robot. A mathematical model is derived based on the robot’s position and tilt angle and a fuzzy logic control is proposed for the balancing robot control. The fuzzy logic controller performance is compared with a conventional PID controller to show the difference between them. Both controllers were tested on the balancing robot in simulation using MATLAB software and the results were put together for a comparative point of view. The simulations shows a relative advantage for the fuzzy logic controller over the conventional PID controller especially in reducing the time required for stabilization which takes about 2 seconds and almost without overshoot while in the PID case the robot will have about 10% overshoot in position and about 20 degrees in tilt angle.

scholarly journals Development of Centrifugation Straining Control System for Greek Yogurt Production Based on Weight of Whey Drain

2020 ◽  
Vol 2 (1) ◽  
pp. 15-20
Author(s):  
Daniel Christianto ◽  
Cuk Supriyadi Ali Nandar ◽  
Widi Setiawan
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Process Time ◽  
Motor Speed ◽  
Speed Controller ◽  
Speed Up ◽  
And Control

Greek yogurt production needs a straining process that takes 10 hours or more. This paper proposes automation and control method for the centrifugation system to speed up the process time and to optimize the accuracy of quantity of whey drainage. Using system identification, the estimated mathematical model of straining process has been developed based on the traditional process of straining the yogurt. Then, the simulation and control design optimization has been carried out by using the estimated mathematical model. Based on the simulation results using whey mass controller, motor speed controller, and the combination of whey mass and motor speed controller, the controller that used are PID controller and fuzzy logic controller. The fastest controller is a PID controller as motor speed controller and fuzzy logic controller as whey mass controller that can speed up the production time and optimize the accuracy of quantity of whey drainage.

Fuzzy Logic in Hole Drilling of Composites

1994 ◽  
Author(s):  
Aditya Thadani ◽  
Athamaram H. Soni
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Thrust Force ◽  
Cutting Speed ◽  
Research Data ◽  
Theoretical Research ◽  
Hole Drilling ◽  
Tool Geometry ◽  
Drilling Process ◽  
And Control

Abstract Experimental and theoretical research data was utilized in building a Fuzzy Logic Controller model applied to simulate the drilling process of composite materials. The objective is to have a better understanding and control of delamination of composites during the drilling process and at the same time to improve the hole finish by controlling fraying and splintering. By controlling the main issues in the drilling process such as feed rate, cutting speed, thrust force, and torque generated in addition to the tool geometry, it is possible to optimize the drilling process avoiding the conventionally encountered problems.

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