Fuzzy Logic Control Based PID Controller for Diesel Engine with Variable Sampling Rate Control Theory

2019 ◽  
Author(s):  
Xuemin Li ◽  
Chunyue Feng ◽  
Runzhi Wang ◽  
Yufei Liu ◽  
Yunlong Yang ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Diesel Engine ◽  
Control Theory ◽  
Rate Control ◽  
Fuzzy Logic Control ◽  
Pid Controller ◽  
Sampling Rate ◽  
Logic Control ◽  
Variable Sampling

scholarly journals MATHEMATICAL ALGORITHM OF FUZZY LOGIC CONTROLLER FOR MULTILEVEL INVERTER CREATING VERTICAL DIVIDED VOLTAGE

2019 ◽  
Vol 59 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Erol Can
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Pid Controller ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Boost Converter ◽  
Multilevel Inverter ◽  
Logic Control ◽  
Multi Level

A 9-level inverter with a boost converter has been controlled with a fuzzy logic controller and a PID controller for regulating output voltage applications on resistive (R) and inductive (L), capacitance (C). The mathematical model of this system is created according to the fuzzy logic controlling new high multilevel inverter with a boost converter. The DC-DC boost converter and the multi-level inverter are designed and explained, when creating a mathematical model after a linear pulse width modulation (LPWM), it is preferred to operate the boost multi-level inverter. The fuzzy logic control and the PID control are used to manage the LPWM that allows the switches to operate. The fuzzy logic algorithm is presented by giving necessary mathematical equations that have second-degree differential equations for the fuzzy logic controller. After that, the fuzzy logic controller is set up in the 9-level inverter. The proposed model runs on different membership positions of the triangles at the fuzzy logic controller after testing the PID controller. After the output voltage of the converter, the output voltage of the inverter and the output current of the inverter are observed at the MATLAB SIMULINK, the obtained results are analysed and compared. The results show the demanded performance of the inverter and approve the contribution of the fuzzy logic control on multi-level inverter circuits.

scholarly journals The Optimization of Marine Diesel Engine Rotational Speed Control Process by Fuzzy Logic Control Based on Particle Swarm Optimization Algorithm

2018 ◽  
Vol 10 (10) ◽  
pp. 99 ◽  
Author(s):  
Tien Tran
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Diesel Engine ◽  
Fuzzy Logic Control ◽  
Engine Speed ◽  
Fuzzy Logic Controller ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Logic Control

The marine main diesel engine rotational speed automatic control plays a significant role in determining the optimal main diesel engine speed under impacting on navigation environment conditions. In this article, the application of fuzzy logic control theory for main diesel engine speed control has been associated with Particle Swarm Optimization (PSO). Firstly, the controller is designed according to fuzzy logic control theory. Secondly, the fuzzy logic controller will be optimized by Particle Swarm Optimization (PSO) in order to obtain the optimal adjustment of the membership functions only. Finally, the fuzzy logic controller has been completely innovated by Particle Swarm Optimization algorithm. The study results will be represented under digital simulation form, as well as comparison between traditional fuzzy logic controller with fuzzy logic control–particle swarm optimization speed controller being obtained.

Implementing Fuzzy Logic in the Control of a Biologically Inspired Robotic Cat Leg

2008 ◽  
Author(s):  
Anthony L. Crawford ◽  
Dean B. Edwards
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Pid Controller ◽  
Vertical Displacement ◽  
Skeletal Structure ◽  
Governing Equations ◽  
Biologically Inspired ◽  
Logic Control ◽  
Forcing Function ◽  
Force Range

This research discusses the implementation of a fuzzy logic control system to drive the movement of a simplified cat leg model. The system’s movement in this paper addresses a planar motion where the model experiences a fixed horizontal velocity and a harmonic vertical displacement. The fuzzy logic (FL) controller applies membership functions to fuzzify the position and velocity errors and applies height defuzzification to generate the time dependant forcing function for the system’s horizontal and vertical governing equations. A PID controller is also applied as a benchmark for this research. Both controllers are optimized using the simplex method for which the FL controller performed just as well as the PID controller with more promise of accounting for the nonlinear influences that were neglected in this simplified cat leg model and requiring actuators with a lower required force range. This research provides the skeletal structure for which an effective total controller can be built on.

Interval Type-2 Fuzzy Logic Control of Maglev Test Stand

2015 ◽  
Vol 759 ◽  
pp. 71-76
Author(s):  
Ireneusz Dominik
Keyword(s):  
Magnetic Field ◽  
Fuzzy Logic ◽  
Computational Complexity ◽  
Fuzzy Logic Control ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Test Stand ◽  
Logic Control ◽  
Interval Type

The paper contains a description of a research into applying classic algorithm of PID controller as well as advanced Type-2 Fuzzy logic controller to ensure stability of the levitating object in magnetic field. The implemented algorithm can handle uncertainties without increasing drastically the computational complexity, which is crucial in case of PLCs. The issues concerning the construction of the unit, where the experiments were carried out, are presented, as well as the characteristics of the object for different controllers.

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