Fuzzy Hybrid Controller Model for Making Decision to Interpret Any Condition

2006 ◽  
Vol 111 ◽  
pp. 167-170
Author(s):  
M. Shahidul Karim ◽  
Rashed Mustafa
Keyword(s):  
Fuzzy Logic ◽  
Control Strategy ◽  
Room Temperature ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Electronic System ◽  
Comfort Level ◽  
Price Ratio ◽  
Hybrid Controller ◽  
Software Development System

The constantly increasing performance/price ratio of microcontrollers means electronic system can replace more and more electromechanical ones. In design, the goal is not to just replace the solution but also to improve it by adding new functionalities. The paper presents a model of industrial controller having possibility of the classical programming controller, with added elements of the fuzzy logic. Here fuzzy logic offers a technical control strategy that uses elements of everyday language. In this application, it is used to design a control strategy that adapts to the need of individual user. It achieves a higher comfort level and reduces energy consumption. Here we have used a fuzzy method which selects the contractions that best meet the specifications, where human knowledge is involved in a decision making process. With a fuzzy-logic software development system, the entire system, which includes conventional code for signal preprocessing as well as the fuzzy logic system, can be implemented on an industry-standard microcontroller. Using fuzzy logic on such a low-cost platform makes this a possible solution with most AC systems. Each home AC has a sensor that measures room temperature and compares it with the temperature set on the dial. The fuzzy logic controller uses a bimetallic switch and compares the set temperature with room temperature.

Hybrid Neural-Fuzzy Controller for Motorized Robot Arm

2011 ◽  
Vol 403-408 ◽  
pp. 5068-5075
Author(s):  
Fatma Zada ◽  
Shawket K. Guirguis ◽  
Walied M. Sead
Keyword(s):  
Fuzzy Logic ◽  
Design Methodology ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
System Response ◽  
Robot Arm ◽  
Neural Controller ◽  
Hybrid Controller ◽  
Neural Fuzzy ◽  
Transient And Steady State

In this study, a design methodology is introduced that blends the neural and fuzzy logic controllers in an intelligent way developing a new intelligent hybrid controller. In this design methodology, the fuzzy logic controller works in parallel with the neural controller and adjusting the output of the neural controller. The performance of our proposed controller is demonstrated on a motorized robot arm with disturbances. The simulation results shows that the new hybrid neural -fuzzy controller provides better system response in terms of transient and steady-state performance when compared to neural or fuzzy logic controller applications. The development and implementation of the proposed controller is done using the MATLAB/Simulink toolbox to illustrate the efficiency of the proposed method.

Low Cost Engine Management System (EMS) for the Cost Sensitive Two-Wheeler Application: Idle Speed and A/F Ratio Control Using PID and Fuzzy Logic Control Algorithms

2007 ◽  
Author(s):  
P. V. Manivannan ◽  
A. Ramesh
Keyword(s):  
Fuzzy Logic ◽  
Fuel Consumption ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Engine Management System ◽  
Position Sensor ◽  
Idle Speed ◽  
The Cost ◽  
Two Wheeler ◽  
Speed Fluctuations

In this work an Engine Management System (EMS) using a low cost 8-bit microcontroller specifically for the cost sensitive small two-wheeler application was designed and developed. Only the Throttle Position Sensor (TPS) and the cam position sensor (also used for speed measurement) were used. A small capacity 125CC four stroke two-wheeler was converted into a Port Fuel Injected (PFI) engine and was coupled to a fully instrumented Eddy Current Dynamometer. Air-fuel ratio was controlled using the open loop, lookup-table [speed (N) and throttle (α)] based technique. Spark Time was controlled using a proportional / fuzzy logic based close loop control algorithm for the idle speed control to reduce fuel consumption and emissions. Test results show a significant improvement in engine performance over the original carbureted engine, in terms of fuel consumption, emissions and idle speed fluctuations. The Proportional controller resulted in significantly lower speed fluctuations and HC / CO emissions than the fuzzy logic controller. Though the fuzzy logic controller resulted in low cycle by cycle variations than the original carbureted engine, it leads to significantly higher HC levels. The performance fuzzy logic can be improved by modifying the membership function shapes with more engine test data.

Fuzzy Logic Controller for Force Feedback Control of Quadcopter via Tether

2020 ◽  
Author(s):  
Bennett Breese ◽  
Drew Scott ◽  
Shraddha Barawkar ◽  
Manish Kumar
Keyword(s):  
Fuzzy Logic ◽  
Control Strategy ◽  
Fuzzy Logic Controller ◽  
Force Feedback ◽  
Power Transmission ◽  
Extensive Simulation ◽  
Control Scheme ◽  
Area Surveillance ◽  
Simulation Results ◽  
Long Endurance

Abstract Tethered drone systems can be used to perform long-endurance tasks such as area surveillance and relay stations for wireless communication. However, all the existing systems use tethers only for data and power transmission from a stationary point on the ground. This work presents a control strategy that enables a quadcopter to follow a moving tether anchor. A force feedback controller is implemented using Fuzzy Logic. Using force-based strategy provides effective compliance between the tether’s anchor and the drone. The drone can thus be controlled by mere physical movement/manipulation of tether. This enhances the safety of current tethered drone systems and simplifies the flying of drones. Fuzzy Logic provides an intuitive edge to the control of such systems and allows handling noise in force sensors. Extensive simulation results are presented in this paper showing the effectiveness of the proposed control scheme.

Obstacle avoidance and path planning of humanoid robot using fuzzy logic controller aided owl search algorithm in complicated workspaces

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhishek Kumar Kashyap ◽  
Dayal R. Parhi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Search Algorithm ◽  
Optimal Path ◽  
Humanoid Robots ◽  
Steering Angle ◽  
Content Type ◽  
Hybrid Controller ◽  
Humanoid Nao

Purpose This paper aims to outline and implement a novel hybrid controller in humanoid robots to map an optimal path. The hybrid controller is designed using the Owl search algorithm (OSA) and Fuzzy logic. Design/methodology/approach The optimum steering angle (OS) is used to deal with the obstacle located in the workspace, which is the output of the hybrid OSA Fuzzy controller. It is obtained by feeding OSA's output, i.e. intermediate steering angle (IS), in fuzzy logic. It is obtained by supplying the distance of obstacles from all directions and target distance from the robot's present location. Findings The present research is based on the navigation of humanoid NAO in complicated workspaces. Therefore, various simulations are performed in a 3D simulator in different complicated workspaces. The validation of their outcomes is done using the various experiments in similar workspaces using the proposed controller. The comparison between their outcomes demonstrates an acceptable correlation. Ultimately, evaluating the proposed controller with another existing navigation approach indicates a significant improvement in performance. Originality/value A new framework is developed to guide humanoid NAO in complicated workspaces, which is hardly seen in the available literature. Inspection in simulation and experimental workspaces verifies the robustness of the designed navigational controller. Considering minimum error ranges and near collaboration, the findings from both frameworks are evaluated against each other in respect of specified navigational variables. Finally, concerning other present approaches, the designed controller is also examined, and major modifications in efficiency have been reported.

scholarly journals A Fuzzy Logic-Based Control Algorithm for the Recharge/V2G of a Nine-Phase Integrated On-Board Battery Charger

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 946 ◽  
Author(s):  
Felice De Luca ◽  
Vito Calderaro ◽  
Vincenzo Galdi
Keyword(s):  
Fuzzy Logic ◽  
Control Strategy ◽  
Energy Demand ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Energy Resource ◽  
Reference Value ◽  
Active Role ◽  
Effective Control ◽  
Battery Charger

Energy demand associated with the ever-increasing penetration of electric vehicles on worldwide roads is set to rise exponentially in the coming years. The fact that more and more vehicles will be connected to the electricity network will offer greater advantages to the network operators, as the presence of an on-board battery of discrete capacity will be able to support a whole series of ancillary services or smart energy management. To allow this, the vehicle must be equipped with a bidirectional full power charger, which will allow not only recharging but also the supply of energy to the network, playing an active role as a distributed energy resource. To manage recharge and vehicle-to-grid (V2G) operations, the charger has to be more complex and has to require a fast and effective control structure. In this work, we present a control strategy for an integrated on-board battery charger with a nine-phase electric machine. The control scheme integrates a fuzzy logic controller within a voltage-oriented control strategy. The control has been implemented and simulated in Simulink. The results show how the voltage on the DC-bus is controlled to the reference value by the fuzzy controller and how the CC/CV charging mode of the battery is possible, using different charging/discharging current levels. This allows both three-phase fast charge and V2G operations with fast control response time, without causing relevant distortion grid-side (Total Harmonic Distortion is maintained around 3%), even in the presence of imbalances of the machine, and with very low ripple stress on the battery current/voltage.

Path optimization for navigation of a humanoid robot using hybridized fuzzy-genetic algorithm

2019 ◽  
Vol 7 (3) ◽  
pp. 112-119 ◽  
Author(s):  
Asita Kumar Rath ◽  
Dayal R. Parhi ◽  
Harish Chandra Das ◽  
Priyadarshi Biplab Kumar ◽  
Manoj Kumar Muni ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Path Planning ◽  
Humanoid Robot ◽  
Fuzzy Logic Controller ◽  
Target Location ◽  
Target Position ◽  
Content Type ◽  
Hybrid Controller ◽  
Fuzzy Genetic

Purpose Humanoids have become the center of attraction for many researchers dealing with robotics investigations by their ability to replace human efforts in critical interventions. As a result, navigation and path planning has emerged as one of the most promising area of research for humanoid models. In this paper, a fuzzy logic controller hybridized with genetic algorithm (GA) has been proposed for path planning of a humanoid robot to avoid obstacles present in a cluttered environment and reach the target location successfully. The paper aims to discuss these issues. Design/methodology/approach Here, sensor outputs for nearest obstacle distances and bearing angle of the humanoid are first fed as inputs to the fuzzy logic controller, and first turning angle (TA) is obtained as an intermediate output. In the second step, the first TA derived from the fuzzy logic controller is again supplied to the GA controller along with other inputs and second TA is obtained as the final output. The developed hybrid controller has been tested in a V-REP simulation platform, and the simulation results are verified in an experimental setup. Findings By implementation of the proposed hybrid controller, the humanoid has reached its defined target position successfully by avoiding the obstacles present in the arena both in simulation and experimental platforms. The results obtained from simulation and experimental platforms are compared in terms of path length and time taken with each other, and close agreements have been observed with minimal percentage of errors. Originality/value Humanoids are considered more efficient than their wheeled robotic forms by their ability to mimic human behavior. The current research deals with the development of a novel hybrid controller considering fuzzy logic and GA for navigational analysis of a humanoid robot. The developed control scheme has been tested in both simulation and real-time environments and proper agreements have been found between the results obtained from them. The proposed approach can also be applied to other humanoid forms and the technique can serve as a pioneer art in humanoid navigation.

scholarly journals Design of microcontroller-based decentralized controller board to drive chiller systems using PID and fuzzy logic algorithms

2019 ◽  
Vol 234 (1) ◽  
pp. 98-107 ◽  
Author(s):  
Yalcin Isler ◽  
Savas Sahin ◽  
Orhan Ekren ◽  
Cuneyt Guzelis
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Variable Speed ◽  
Proportional Integral Derivative ◽  
Scroll Compressor ◽  
Proportional Integral ◽  
Output Controller ◽  
Expansion Valve ◽  
Controller Board

This study deals with designing a decentralized multi-input multi-output controller board based on a low-cost microcontroller, which drives both parts of variable-speed scroll compressor and electronic-type expansion valve simultaneously in a chiller system. This study aims to show the applicability of commercial low-cost microcontroller to increase the efficiency of the chiller system, having variable-speed scroll compressor and electronic-type expansion valve with a new electronic card. Moreover, the refrigerant system proposed in this study provides the compactness, mobility, and flexibility, and also a decrease in the controller unit’s budget. The study was tested on a chiller system that consists of an air-cooled condenser, a variable-speed scroll compressor, and a stepper driven electronic-type expansion valve. The R134a was used as a refrigerant fluid and its flow was controlled by electronic-type expansion valve in this setup. Both variable-speed scroll compressor and electronic-type expansion valve were driven by the proposed hardware using either proportional integral derivative or fuzzy logic controller, which defines four distinct controller modes. The experimental results show that fuzzy logic controlled electronic-type expansion valve and proportional integral derivative controlled variable-speed scroll compressor mode give more robustness by considering the response time.

scholarly journals Active tremor control in human-like hand tremor using fuzzy logic

2021 ◽  
Vol 24 (1) ◽  
pp. 108
Author(s):  
Hafiz Bin Jamaludin ◽  
Azizan As'arry ◽  
R. Musab ◽  
Khairil Anas Md Rezali ◽  
Raja Mohd Kamil Bin Raja Ahmad ◽  
...  
Keyword(s):  
Experimental Study ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Initial Step ◽  
Daily Activities ◽  
Hand Tremor ◽  
Hybrid Controller ◽  
A Value ◽  
Power Spectral ◽  
Reduction Percentage

<span>Tremor<span>is the vibration in sinusoidal orientation that is experienced regularly by a person with Parkinson’s disease (PD), which disturbs their daily activities. One solution that may be used to counter this tremor effect is by developing an active tremor control system in LabVIEW for linear voice coil actuator (LVCA), where the system uses proportional (P) controller and various types of fuzzy logic controller (FLC) as a hybrid controller to reduce tremor vibration. From this research, it can be concluded that the best controller for tremor reduction is the P+FLC 1<sup>st</sup> set of rules, compared to P+FLC 2<sup>nd</sup> set of rules, and P controller only, with the highest percentage of 88.39% of tremor reduction with the actual tremor vibration of PD patients as the reference result. The P+FLC 2<sup>nd</sup> set of rules has the highest percentage of tremor reduction with a value of 86.81%, whereas P controller only has the highest tremor reduction percentage of 67.10%. This percentage of tremor reduction is based on the power spectral density (PSD) values, in which it represents the intensity of the tremor vibration. This experimental study can be used as an initial step for researchers and engineers to design and develop an anti-tremor device in the future.</span></span>

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