High speed optimised reconfigurable architecture of fuzzy logic controller

2007 ◽  
Author(s):  
M.A. Saeed ◽  
M. Hasan ◽  
N. Ahmad
Keyword(s):  
Fuzzy Logic ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Reconfigurable Architecture

scholarly journals Intelligent Traffic Management Service Using Fuzzy Logic Controller in High Speed Networks

2019 ◽  
pp. 95-98
Author(s):  
Muppineni Sravanthi
Keyword(s):  
Fuzzy Logic ◽  
Traffic Management ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
System Simulation ◽  
Core Area ◽  
Management Service ◽  
High Speed Networks ◽  
Simulation Results

Network traffic management is a core area of research that is of great importance in the field of communication. This paper proposes a new scheme for controlling router side traffic in networks by updating source sending rate according to its IQ size. A new fuzzy controller is to be modelled to implement the proposed system. Simulation results and comparisons has verified the effectiveness and showed that our proposed scheme can achieve better performances than the existing protocols.

Extended fuzzy logic controller for high speed train

2011 ◽  
Vol 22 (2) ◽  
pp. 321-328 ◽  
Author(s):  
Hai-rong Dong ◽  
Shi-gen Gao ◽  
Bin Ning ◽  
Li Li
Keyword(s):  
Fuzzy Logic ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
High Speed Train

scholarly journals Fuzzy Logic Controller sebagai Penentu Gerak Mobile Robot Pembasmi Hama

2020 ◽  
Vol 1 (01) ◽  
pp. 19-24
Author(s):  
Muhammad Ridho Kenawas ◽  
Pola Risma ◽  
Tresna Dewi ◽  
Selamet Muslimin ◽  
Yurni Oktarina
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Pulse Width Modulation ◽  
Robot Motion ◽  
Crop Failure ◽  
Driving System ◽  
Dc Motors ◽  
Autonomous Decision

A mobile robot is one of the solutions to overcome crop failure caused by chili pests. The mobile robot discussed in this paper is used to spray pesticide liquid into chili plant stems to prevent pests attack on the plants. This paper discusses the design of pesticide spraying robot motion with the application of Fuzzy Logic Controller. This robot employment is expected to reduce farmers' workload and to help to produce a good harvest.  Robot motions are divided into two conditions, which can be controlled by remote control as a controller (manual) and by means of a sensor (automatic). Mobile robot movements have a significant impact on navigation and the design of the driving system. Robot speed is controller by adjusting Pulse Width Modulation of DC motors attached to the robots' wheel, which set to be  90 for slow and 220  for high speed. The Fuzzy Logic Controller in this mobile robot functions as an autonomous decision-making driver to detect obstacles in front of the mobile robot and the targeted stems.

scholarly journals A simplify fuzzy logic controller design based safe experimentation dynamics for pantograph-catenary system

2019 ◽  
Vol 14 (2) ◽  
pp. 903 ◽  
Author(s):  
Mohd Faisal Farhan ◽  
Nor Sakinah Abdul Shukor ◽  
Mohd Ashraf Ahmad ◽  
Mohd Helmi Suid ◽  
Mohd Riduwan Ghazali ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Contact Force ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Essential Feature ◽  
Fast Response ◽  
Model Free ◽  
Catenary System ◽  
Three Degree Of Freedom

Contact force between catenary and pantograph of high speed train is a crucial system to deliver power to the train. The inconsistence force between them can cause the contact wire oscillate a lot and it can damage the mechanical structure of system and produce electric arc that can reduce the performance of system. This project proposes a single-input fuzzy logic controller (SIFLC) to control the contact force between the pantograph-catenary by implement Safe Experimentation Dynamics (SED) method to tune the SIFLC parameters. The essential feature of SIFLC is that it is model-free type controller design with less pre-defined variables as compared to other existing model-based controllers. The performance of the SIFLC is analyzed in terms of input tracking of contact force of pantograph-catenary and time response specifications. A simplified model of three degree of freedom (3-DOF) pantograph-catenary system is considered. In this study, the simulation result shows that the SIFLC successfully track the given contact force with less overshoot with percentage different of peak to peak response  from actual force 2% and fast response within 5.27s

CMOS CIRCUIT DESIGN OF A TAKAGI-SUGENO FUZZY LOGIC CONTROLLER

2009 ◽  
Vol 18 (04) ◽  
pp. 841-856
Author(s):  
WEIWEI SHAN ◽  
YAN LIANG ◽  
DONGMING JIN
Keyword(s):  
Fuzzy Logic ◽  
Low Power ◽  
Integrated Circuit ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
High Accuracy ◽  
Real Time Control ◽  
Chip Area ◽  
Takagi Sugeno

This paper presents a low power CMOS analog integrated circuit of a Takagi–Sugeno fuzzy logic controller with voltage/voltage interface, small chip area, relatively high accuracy and medium speed, which is composed of several improved functional blocks. Z-shaped, Gaussian and S-shaped membership function circuits with compact structures are designed, performing well with low power, high speed and small areas. A current minimization circuit is provided with high accuracy and high speed. A follower-aggregation defuzzification block composed of several multipliers for center of gravity (COG) defuzzification is presented without using a division circuit. Based on these blocks, a two-input one-output singleton fuzzy controller with nine rules is designed under a CMOS 0.6 μm standard technology provided by CSMC. HSPICE simulation results show that this controller reaches an accuracy of ±3% with power consumption of only 3.5 mW (at ±2.5 V). The speed of this controller goes up to 0.625M Fuzzy Logic Inference per Second (FLIPS), which is fast enough for real-time control.

Robust Adaptive Fuzzy Logic Controllers for Intelligent Universal Transformers in ADA

2011 ◽  
Vol 403-408 ◽  
pp. 5038-5044
Author(s):  
Maryam Sadeghi ◽  
Majid Gholami
Keyword(s):  
Fuzzy Logic ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Voltage Regulation ◽  
System Stability ◽  
Distribution Automation ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Logic ◽  
Robust Adaptive ◽  
Output Stages

Intelligent Universal Transformer (IUT) will comprise in Advanced Distribution Automation (ADA) with a new invention in control and management in future. It evolves with a high speed traditional transformer in addition to power electronic base construction will eventuate to oil elimination, dimensional size and weight reduction. Adaptive Fuzzy Logic Control (AFLC) is an adaptive progressed method with the high system performance capability being raised even on the uncertainty conditions. It enhances system stability, improves flexibility and releases designers from precise mathematical model utilization. Expert designer Knowledge is a critical requirement for conventional fuzzy logic controller (FLC), in contrast the AFLC rules and parameters are generated by adaptive model and human knowledge will downright initialize the first parameters values. In this approach four layers IUT topology is considered for developing the end user service options as 48V DC, reliable power as 240V AC 400HZ and three phase power option. AFLC schemes are proposed for employing current and voltage controllers in input output stages. Real time voltage regulation, automatic sag correction, Harmonic Filtering, energy storage option and dynamic system monitoring are the resulting benefits of using IUT four layers topology. AFLC methodology, leading the system robustness in any cases of grid and load disturbances.

Hardware-in-the-loop simulation and implementation of a fuzzy logic controller with FPGA: case study of a magnetic levitation system

2018 ◽  
Vol 41 (8) ◽  
pp. 2150-2159 ◽  
Author(s):  
Onur Akbatı ◽  
Hatice Didem Üzgün ◽  
Sirin Akkaya
Keyword(s):  
Fuzzy Logic ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Magnetic Levitation ◽  
Order System ◽  
Membership Functions ◽  
Inference System ◽  
Levitation System ◽  
Magnetic Levitation System

This paper presents the design and implementation of a fuzzy logic controller using Very High Speed Integrated Circuit Hardware Description Language (VHDL) on a field programmable gate array (FPGA). First, a Sugeno-type fuzzy logic controller with five triangular and trapezoidal membership functions for two inputs and with nine singleton membership functions for one output is examined. The proposed structure is tested with second- and third-order system model using FPGA-in-the-loop simulation via a MATLAB/Simulink environment. Then, for different kinds of fuzzy logic controllers, a new look-up table (LUT) and interpolation-based controller implementation is proposed to eliminate the computational complexity of the primarily designed structure. As a case study, a magnetic levitation system is controlled with an adaptive neuro-fuzzy inference system (ANFIS) trained fuzzy logic controller, then it is simulated and implemented using a LUT-based controller. Finally, we provide a comparison of results.

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