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PSO tuned Adaptive Neuro-fuzzy Controller for Vehicle Suspension Systems

Rajeswari Kothandaraman, Lakshmi Ponnusamy
2012 Journal of Advances in Information Technology  
Index Terms-Vehicle suspension, Quarter car model, ANFIS, FLC, ride comfort.  ...  In this paper, Particle Swarm Optimization (PSO) technique is applied to tune the Adaptive Neuro Fuzzy Controller (ANFIS) for vehicle suspension system.  ...  A.Adaptive neuro-fuzzy architecture An ANFIS is proposed as a core neuro-fuzzy model that can incorporate human expertise as well as adapt itself through repeated learning.  ... 
doi:10.4304/jait.3.1.57-63 fatcat:337jka7j4zczjbijb677cqgyiu

A Modified Neuro-Fuzzy System Using Metaheuristic Approaches for Data Classification [chapter]

Mohd Najib Mohd Salleh, Noureen Talpur, Kashif Hussain Talpur
2018 Artificial Intelligence - Emerging Trends and Applications  
ANFIS (Adaptive Neuro-Fuzzy Inference system) is an efficient combination of ANN and fuzzy logic for modeling highly non-linear, complex and dynamic systems.  ...  Moreover, the standard learning process of ANFIS involves gradient based learning which has prone to fall in local minima.  ...  As an adaptive neuro-fuzzy model; it has advantage of being flexible, adaptive and effective for non-linear complex problems [6] .  ... 
doi:10.5772/intechopen.75575 fatcat:jbetigmd7vg6vp24t7pherqqfu

Trajectory Estimation And Control Of Vehicle Using Neuro-Fuzzy Technique

B. Selma, S. Chouraqui
2012 Zenodo  
This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning.  ...  non linear system.  ...  In this study, a new approach based on ANFIS was presented for control of the car to follow his path.  ... 
doi:10.5281/zenodo.1073148 fatcat:p2a3ntlcinfu3dyb3mvvolkwnq

Low-Speed Longitudinal Controllers for Mass-Produced Cars: A Comparative Study

Vicente Milanes, Jorge Villagra, Joshué Perez, Carlos Gonzalez
2012 IEEE transactions on industrial electronics (1982. Print)  
based on human experience; and an adaptive-network-based fuzzy inference system.  ...  A Citroen C3 Pluriel car was modified to permit autonomous action on the accelerator and the brake pedals-i.e., longitudinal control. The controllers were tested in two stages.  ...  to the PI; a fuzzy controller based on human experience; and an adaptive-networkbased fuzzy inference system.  ... 
doi:10.1109/tie.2011.2148673 fatcat:2wysjdmhavdhxg4dgmc2cjj7j4

Embedding a Neuro-Fuzzy Mode Choice Tool in Intelligent Agents

Maria Nadia Postorino, Mario Versaci, Giuseppe M. L. Sarné
2021 Workshop From Objects to Agents  
The neuro-fuzzy model proposed in this paper has been thought to be embedded in an agent-based methodological framework where user agents -representing travelers -make travel choices based on the rules  ...  learnt by means of the neuro-fuzzy system.  ...  Different strategies have been adopted at different levels (e.g., local, national and supranational) to manage such effects, mainly by providing solutions based on transit modes and new technologies [  ... 
dblp:conf/woa/PostorinoVS21 fatcat:yrpqjfmhpfctzhdwbf7jewkhvy

Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

Anish Pandey
2017 International Robotics & Automation Journal  
Several techniques have been applied by the various researchers for mobile robot navigation and obstacle avoidance.  ...  The present article focuses on the study of the intelligent navigation techniques, which are capable of navigating a mobile robot autonomously in static as well as dynamic environments.  ...  Fuzzy logic systems are inspired by human reasoning, which works based on perception.  ... 
doi:10.15406/iratj.2017.02.00023 fatcat:m6viumq36zf5zbfeexua475gjy

Abstracts

2020 IEEE Transactions on Intelligent Vehicles  
Human driver tests on a driving simulator show the leading vehicle velocity can be predicted by the proposed method.  ...  Herein, a state observer-based modified sliding mode interval fuzzy type-2 neural network (FT2NN) controller is designed to suppress the vibrations from a typical rough terrain imposed to the nonlinear  ...  GTMPC first selects one target vehicle (TV) within multiple GCVs based on the Stackelberg equilibrium, followed by estimating TV's aggressiveness based on the interaction between SV and TV, then completes  ... 
doi:10.1109/tiv.2020.2971873 fatcat:af7apwjygrajxeenbiwv7grzii

Robust Hybrid Intelligent Based Motion Control of Industrial Robot Manipulators for Unstructured Dynamic Environment

M Dev Anand, N Ramasamy
2019 Sun International Journal of Engineering and Basic Sciences  
This is possible only with neuro fuzzy techniques since several of its controllers are trained using simple data received from human control of robotic arm and this study quantifies and compares their  ...  Neuro fuzzy systems are excellent in determining the input and output relationships using a simple data. The traditional fuzzy logic system is replaced with the back propagation neural network.  ...  The Robot arm encodes from human automobile driver intelligence, while driving a car.  ... 
doi:10.30558/ijebs.20190202001 fatcat:wv3lv7annbcg5mjzobv2d5zfwq

Industrial applications of soft computing: a review

Y. Dote, S.J. Ovaska
2001 Proceedings of the IEEE  
SC provides an attractive opportunity to represent the ambiguity in human thinking with real life uncertainty.  ...  Fuzzy logic (FL), neural networks (NN), and evolutionary computation (EC) are the core methodologies of soft computing.  ...  Each neuron represents a local linear model with its corresponding validity function (membership function).  ... 
doi:10.1109/5.949483 fatcat:erzs7fqa35dixgm7mq2efptpai

The SOC Estimation of Power Li-Ion Battery Based on ANFIS Model

Tiezhou Wu, Mingyue Wang, Qing Xiao, Xieyang Wang
2012 Smart Grid and Renewable Energy  
On basis of traditional battery performance model, paper analyzed the advantage and disadvantage of SOC estimation methods, introduced Adaptive Neuro-Fuzzy Inference Systems which integrated artificial  ...  By analyzing the battery charge and discharge process, the key parameters of SOC are determined and the experimental model is modified in MATLAB platform.Experimental results show that the difference of  ...  modeling. p q r SOC Estimation Based on ANFIS SOC Estimation Model Based on ANFIS Hybrid operation process is very complicated.  ... 
doi:10.4236/sgre.2012.31007 fatcat:fspmrzsykfbubbyfjo7oryuoyq

Different Nature-Inspired Techniques Applied for Motion Planning of Wheeled Robot: A Critical Review

Anish Pandey, Abhishek Kumar Kashyap
2018 International Journal of Advanced Robotics and Automation  
This article presents a critical review on motion planning of wheeled robot by using different nature-inspired techniques like evolutionary algorithm and swarm-based optimization algorithm.  ...  Motion planning is one of the most important parts when we design any wheeled or walking robots.  ...  [49] have developed a wheeled robot with the help of Neuro-Fuzzy algorithm is like a car. Algabri, et al.  ... 
doi:10.15226/2473-3032/3/2/00136 fatcat:7feu6x3hrncdbgflwo23qowqvm

Fuzzy Control Strategies in Human Operator and Sport Modeling [article]

Tijana T. Ivancevic, Bojan Jovanovic, Sasa Markovic
2009 arXiv   pre-print
In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal  ...  As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.  ...  However, the conventional controller they are comparing it to is a PID controller based on a linear system model.  ... 
arXiv:0907.1212v1 fatcat:wfjnuxnf3rgnbenz7kay453mve

A comprehensive study for robot navigation techniques

Faiza Gul, Wan Rahiman, Syed Sahal, Kun Chen
2019 Cogent Engineering  
Regarding this matter, several techniques have been explored by researchers for robot navigation path planning.  ...  Smooth and safe navigation of mobile robot through cluttered environment from start position to goal position with following safe path and producing optimal path length is the main aim of mobile robot  ...  Fuzzy logic systems are naturally inspired by human reasoning, which works based on perception.  ... 
doi:10.1080/23311916.2019.1632046 fatcat:tbbzjgdbyzhflki37teqcyotmm

Wheeled Mobile Robot Path Planning and Path Tracking Controller Algorithms: A Review

Oluwaseun. O. Martins, Department of Mechatronics Engineering, Federal University Oye-Ekiti Ekiti State, Nigeria, Adefemi. A. Adekunle, Samuel. B. Adejuyigbe, Oluwole. H. Adeyemi, Michael. O. Arowolo
2020 Journal of Engineering Science and Technology Review  
The sustained integration of wheeled mobile robot to task that further require their operation within the human environment characterized with uncertainty makes a review of these solution approaches very  ...  Baturone et al [101] describe a car-like mobile robot control using an embedded neuro-fuzzy controller.  ...  This approach adopts the master and slave controller to control the linear and angular velocity of the robot base on it kinematic and dynamic model respectively.  ... 
doi:10.25103/jestr.133.17 fatcat:qvad4rqszbf5nm2oymv4i2sroa

Development of Quantum-Based Adaptive Neuro-Fuzzy Networks

Sung-Suk Kim, Keun-Chang Kwak
2010 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
In this study, we are concerned with a method for constructing quantum-based adaptive neuro-fuzzy networks (QANFNs) with a Takagi-Sugeno-Kang (TSK) fuzzy type based on the fuzzy granulation from a given  ...  Index Terms-Fuzzy granulation, fuzzy subtractive quantum clustering (FSQC), incremental model, quantum-based adaptive neuro-fuzzy networks (QANFNs).  ...  On the other hand, we compared fuzzy models with the same number of rules obtained by a fuzzy model identification toolbox based on GK clustering and a GG-LS method based on Gath-Geva clustering, with  ... 
doi:10.1109/tsmcb.2009.2015671 pmid:19622441 fatcat:bmn6hbotvjh4dcjdfvqkjapxx4
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