Experimental Investigation on Swash Plate Axial Piston Pumps With Conical Cylinder Blocks Using Fuzzy Logic Control

2002 ◽  
Author(s):  
M. K. Bahr Khalil ◽  
J. Svoboda ◽  
R. B. Bhat
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Real Time Control ◽  
Axial Piston Pumps ◽  
Time Control ◽  
Logic Control ◽  
Swash Plate ◽  
Axial Piston

Analytical studies on the dynamic performance of variable displacement swash plate axial piston pumps show that the pump performance can significantly improved by replacing the conventional PD process controller with fuzzy logic controller. Electrically controlled, constant power regulated, swash plate pumps with conical cylinder blocks have been recently extensively studied. Comparative study has been carried out to compare the pump dynamic performance when the conventional PD process controller is replaced by a proposed fuzzy logic one. The study reveals some superior performance characteristics when fuzzy logic controller is used. In the present study an experimental setup is built to measure the dynamic performance of a typical 9-piston pump that has conical shaped cylinder block. The pump is of 40 cc/rev geometrical size, type A4VSO, that is manufactured by Rexroth. The experimental setup consists of a hydraulic test bed interfaced with real time control and data acquisition system. The setup is used firstly for testing the pump static characteristics. Subsequently, the setup is used to measure the time response of the pump, which is equipped with the conventional PD controller, to the stepwise changes in the load pressure. Pump model verification is then discussed based on the comparison between the theoretical and experimental results. The pump is afterwards interfaced with real time control software for prototyping the proposed fuzzy logic controller that replaces the currently used PD one. With the fuzzy logic control, measuring the pump time response under the same loading conditions is repeated. Experimental results are presented, compared with the analytical findings and discussed.

Performance of Constant Power Operated Swash Plate Axial Piston Pumps With Fuzzy Logic Controllers

2013 ◽  
Author(s):  
Yasser H. Anis ◽  
Saad A. Kassem
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Control Valve ◽  
Step Response ◽  
Pd Controller ◽  
Constant Power ◽  
Axial Piston Pumps ◽  
Swash Plate ◽  
Axial Piston

In this paper, simulation of the step response of electro hydromechanically controlled constant power regulated swash plate axial piston pumps with conical cylinder blocks has been carried out when a new fuzzy logic controller (FLC) is proposed to replace the PD controller in current use. The theoretically deduced performance shows that the proposed FLC renders better performance when compared to both the PD controller and a previously proposed FLC. The effects of the control valve supply pressure, valve port width, and control piston leakage coefficient on the pump step response has been investigated. Results show that the proposed FLC renders better dynamic performance, when compared with the previously proposed FLC and the PD controller, at all practical values of the investigated three parameters.

Fuzzy Logic Control of Constant Power Regulated Swash Plate Axial Piston Pumps

2001 ◽  
Author(s):  
S. A. Kassem ◽  
M. K. Bahr
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Pd Controller ◽  
Constant Power ◽  
Practical Applications ◽  
Axial Piston Pumps ◽  
Swash Plate ◽  
The Impact ◽  
Axial Piston

Abstract This paper presents a theoretical study of some aspects of the dynamics of electrically controlled constant power regulated swash plate axial piston pumps with conical cylinder blocks. The mathematical model of the pump is derived. Simulation of the pump dynamic characteristics is carried out when the controller is a conventional PD one used currently in practical applications. The good agreement between the simulation and the experimental results validates the derived model. A fuzzy logic controller (FZC) is proposed to replace the PD controller. The simulation results show that the FZC yields better dynamic performance and is more robust as compared with the PD controller. The FZC is also shown to reduce the oscillations of the proportional valve spool at each swash plate inclination angle, which increases the valve service life and reduces the generated heat in it. In case of pumps of large geometric volumes the FZC is found also to reduce the impact of the control piston at the end of the stroke.

scholarly journals Power System Stabilization By Fuzzy Set Theory Based Control Of SMES

1970 ◽  
Vol 6 (2) ◽  
pp. 33-41 ◽  
Author(s):  
Md Rafiqul Islam Sheikh ◽  
Rion Takahashi ◽  
Junji Tamura
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Power System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Magnetic Energy ◽  
Dynamic Performance ◽  
Superior Performance ◽  
Logic Control

At present fuzzy logic control is receiving increasing emphasis in process control applications. The paper describes the application of fuzzy logic control in a power system that uses a 12- pulse bridge converter associated with Superconductive Magnetic Energy Storage (SMES) unit. The fuzzy control is used in both the frequency and voltage control loops, replacing the conventional control method. The control algorithms have been developed in detail and simulation results are presented. These results clearly indicate the superior performance of fuzzy control during the dynamic period of energy transfer between the power system and SMES unit. Keywords: Fuzzy logic controller; power system dynamic performance; SMES unit. DOI: http://dx.doi.org/10.3329/diujst.v6i2.9343 DIUJST 2011; 6(2): 33-41

Applying fuzzy logic control to analyze real-time control for charging and discharging power of electric vehicles

2021 ◽  
pp. 1-7
Author(s):  
Feng Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuzzy Logic Control ◽  
Power Grid ◽  
Regional Distribution ◽  
Real Time Control ◽  
Time Control ◽  
Logic Control

The disorderly charging of large-scale electric vehicles will aggravate the peak-valley difference of the power grid, and affect the power quality and life of the transformer. The fuzzy logic control strategy for charging and discharging optimization of charging vehicles under the framework of fuzzy logic control from the perspective of the group is considered in this article. A real-time control method based on the clustering characteristics of the charging end time is proposed according to the different charging requirements of the connected electric vehicles and fuzzy logic control is adopted to solve the problem of optimal charging and discharging power of the entire cluster and a single electric vehicle. A fuzzy logic control model considering the charging and discharging of electric vehicles is established orienting at minimize daily load fluctuations and control penalties in the upper layer. The charging and discharging cost of electric vehicle owners is considered to solve the optimal control problem of the charging and discharging power of a single electric vehicle. Taking the data of the typical regional distribution network load as an example, it is verified that the real-time charging optimization strategy under fuzzy logic control through simulation can ensure the reliable operation of the power grid while considering the interests of all parties.

scholarly journals Evaluation of the High Performance Indirect Field Oriented Controlled Dual Induction Motor Drive Fed by a Single Inverter using Type-2 Fuzzy Logic Control

2020 ◽  
Vol 10 (5) ◽  
pp. 6301-6308
Author(s):  
A. Bounab ◽  
A. Chaiba ◽  
S. Belkacem
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Control ◽  
High Performance ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Voltage Source ◽  
Switching Frequency ◽  
Logic Control

In this paper, a high-performance indirect field-oriented controlled dual Induction Motor (IM) drive fed by a single inverter using type-2 fuzzy logic control will be presented. At first, the mathematical model of the IM is implemented in the d-q reference frame. Then, the speed control of the Dual Induction Motor (DIM) operating in parallel configuration with Indirect Field Oriented Control (IFOC) using PI and type-2 Fuzzy Logic Controller (T2-FLC) will be presented. For the control of this system, a DC supply and a Space Vector Pulse Width Modulation (SVPWM) voltage source inverter are introduced with constant switching frequency. Also, the performance of T2-FLC, which is based on the IFOC, is tested and compared to those achieved using the PI controller. The simulation results demonstrate that the T2-FLC is more robust, efficient, and has superior dynamic performance for traction system applications.

Fuzzy logic control for a hydraulic hybrid excavator based on torque prediction and genetic algorithm optimization

2017 ◽  
Vol 232 (8) ◽  
pp. 983-994 ◽  
Author(s):  
Hua Zhou ◽  
Peng-Yu Zhao ◽  
Ying-Long Chen
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Membership Functions ◽  
Real Time Control ◽  
Hydraulic Hybrid ◽  
Time Control ◽  
Logic Control ◽  
Hybrid Excavator

Optimization of the control strategy, whose primary mission is to solve the problem associated with energy management, is an effective way to minimize the fuel consumption of the hydraulic hybrid excavator. As a widely used control strategy, fuzzy logic control can be adopted to realize suboptimal power split with robustness and adaptation, which is one of the most logical approaches for multidomain, nonlinear and time-varying plant. However, the membership functions are difficult to determine according to manual experiences; meanwhile, the optimization-based membership functions are difficult to utilize in real time control. This paper aims to improve the fuel consumption of a hydraulic hybrid excavator by proposing a fuzzy control strategy whose membership functions are optimized by the genetic algorithm, which considers predicted torque of the internal combustion engine (ICE) as a known quantity to realize real time control. The needed torque of the ICE is predicted by superposition of the previous torque. A fuzzy logic control strategy is then designed with membership functions optimized by the genetic algorithm according to the predicted needed torque to achieve better performance. Finally, a numerical experiment is carried out to verify the proposed control strategy.

A contribution to the identification in fuzzy-logic control

1990 ◽  
Vol 55 (4) ◽  
pp. 951-963 ◽  
Author(s):  
Josef Vrba ◽  
Ywetta Purová
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Automatic Generation ◽  
Linguistic Variable ◽  
Fuzzy Subset ◽  
Input Output ◽  
Logic Control ◽  
Correlation Tables

A linguistic identification of a system controlled by a fuzzy-logic controller is presented. The information about the behaviour of the system, concentrated in time-series, is analyzed from the point of its description by linguistic variable and fuzzy subset as its quantifier. The partial input/output relation and its strength is expressed by a sort of correlation tables and coefficients. The principles of automatic generation of model statements are presented as well.

Comparison of a Fuzzy Logic Controller With a P + D Control Law

1989 ◽  
Vol 111 (2) ◽  
pp. 128-137 ◽  
Author(s):  
S. Daley ◽  
K. F. Gill
Keyword(s):  
Fuzzy Logic ◽  
Attitude Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Good Control ◽  
Control Law ◽  
Dynamic Coupling ◽  
Process Knowledge ◽  
Logic Control ◽  
Limited Process

A study is described that compares the performance of a self-organizing fuzzy logic control law (SOC) with that of the more traditional P + D algorithm. The multivariate problem used for the investigation is the attitude control of a flexible satellite that has significant dynamic coupling of the axes. It is demonstrated that the SOC can provide good control, requires limited process knowledge and compares favorably with the P + D algorithm.

scholarly journals DC Motor Speed Control Using Mamdani Fuzzy Logic Based on Microcontroller

Jurnal Teknik ◽  
2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Sumardi Sadi
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Logic Control ◽  
Control Command ◽  
Arduino Uno

DC motors are included in the category of motor types that are most widely used both in industrial environments, household appliances to children's toys. The development of control technology has also made many advances from conventional control to automatic control to intelligent control. Fuzzy logic is used as a control system, because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this research is to study and apply the fuzzy mamdani logic method to the Arduino uno microcontroller, to control the speed of a DC motor and to control the speed of the fan. The research method used is an experimental method. Global testing is divided into three, namely sensor testing, Pulse Width Modulation (PWM) testing and Mamdani fuzzy logic control testing. The fuzzy controller output is a control command given to the DC motor. In this DC motor control system using the Mamdani method and the control system is designed using two inputs in the form of Error and Delta Error. The two inputs will be processed by the fuzzy logic controller (FLC) to get the output value in the form of a PWM signal to control the DC motor. The results of this study indicate that the fuzzy logic control system with the Arduino uno microcontroller can control the rotational speed of the DC motor as desired.

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.

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