43 results for “Adaptive fuzzy”

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Research ArticleOpen accessPhrase in the titleAdaptive Fuzzy Knowledge Based Controller for Autonomous Robot Motion ControlMbaitiga ZacharieProblem statement: Research into robot motion control offers research opportunities that will change scientists and engineers for year to come. Autonomous robots are increasingly evident in many aspects of industry and everyday life and a robust robot motion control can be used for homeland security and many consumer applications. This study discussed the adaptive fuzzy knowledge based controller for robot … …Journal of Computer Science, Vol. 6, Issue 10 · 30 Jul 2010 · 6,909 accessesView PDF Cite

Research ArticleOpen accessPhrase in the titleSpeed Estimation of Adaptive Fuzzy-Controlled Piezo-Electric Motor using MLP-Neural NetworkShebel ALSABBAH, Tariq MUGHRABIThe speed of ultrasonic motor of piezo-electric type is usually measured using mechanical sensors such as pulse encoders. However, these sensors are costly and bulky. In this paper, a numerical speed estimation approach of a piezo-electric motor (PEM) is implemented using multilayer perception neural network (MLP-NN). The proposed model evaluates rotational speed and load torque based on the amplitude and … …American Journal of Applied Sciences, Vol. 5, Issue 11 · 30 Nov 2008 · 6,785 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleImprovement of Rooftop Solar Panels Efficiency using Maximum Power Point Tracking Based on an Adaptive Neural Network Fuzzy Inference SystemI Made Ari Nrartha, I Made Ginarsa, Agung Budi Muljono et al.Rooftop solar panels are a strategy for achieving Indonesia's renewable energy goals, but their non-linear characteristics make them difficult to control, especially in the face of extreme weather changes. An effective controller is needed to optimize the power output of solar panels. This study proposes a Maximum Power Point Tracking (MPPT) controller based on an Adaptive Neural network Fuzzy Inference … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 1 · 19 Jan 2023 · 5,769 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titlePROBABILISTIC PERIODIC REVIEW INVENTORYMODELUSING LAGRANGE TECHNIQUE AND FUZZY ADAPTIVE PARTICLE SWARM OPTIMIZATIONH. A. Fergany, N. A. El-Hefnawy, O. M. HollahThe integration between inventory model and Artificial Intelligent (AI) represents the rich area of research since last decade. In this study we investigate probabilistic periodic review <Q<qm, N> inventory model with mixture shortage (backorder and lost sales) using Lagrange multiplier technique and Fuzzy Adaptive Particle Swarm Optimization (FAPSO) under restrictions. The objective of these algorithms is to find the optimal … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 11 Aug 2014 · 7,017 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleAdaptive Neuro-Fuzzy Inference System-Particle Swarm Optimization Based Stability Maintenance of Power System NetworksR. Latha, J. KanakarajDuring faulty condition voltage instability is one of the major crisis in power system networks. This study proposes a hybrid learning algorithm to improve the stability performance of a power system with Distributed Generations (DGs). Here the distribution system stability is maintained with reduced power loss using an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Particle Swarm Optimization (PSO) techniques. In … …American Journal of Applied Sciences, Vol. 10, Issue 8 · 24 Jul 2013 · 6,906 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleComparative Evaluation of Adaptive Filter and Neuro-Fuzzy Filter in Artifacts Removal From Electroencephalogram SignalPaulchamy Balaiah, IlavennilaProblem statement: This study presents an effective method for removing mixed artifacts (EOG-Electro-ocular gram, ECG-Electrocardiogram, EMG-Electromyogram) from the EEG-Electroencephalogram records. The noise sources increases the difficulty in analyzing the EEG and obtaining clinical information. EEG signals are multidimensional, non-stationary (i.e., statistical properties are not invariant in time), time domain biological signals, which are not reproducible. It is supposed to contain … …American Journal of Applied Sciences, Vol. 9, Issue 10 · 15 Aug 2012 · 7,087 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleApplication of Adaptive Neuro-Fuzzy Inference System for Information SecuirtyAltyeb Altaher, Ammar Almomani, Sureswaran RamadassProblem statement: Computer networks are expanding at very fast rate and the number of network users is increasing day by day, for full utilization of networks it need to be secured against many threats including malware, which is harmful software with the capability to damage data and systems. Fuzzy rule based classification systems considered as an active research area in … …Journal of Computer Science, Vol. 8, Issue 6 · 23 Apr 2012 · 7,747 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleAn Adaptive Neuro-Fuzzy Inference System Based Modeling for Corrosion-Damaged Reinforced HSC Beams Strengthened with External Glass Fibre Reinforced Polymer LaminatesV. Balasubramaniam, P. N. Raghunath, K. SugunaProblem statement: This study presents the results of ANFIS based model proposed for predicting the performance characteristics of reinforced HSC beams subjected to different levels of corrosion damage and strengthened with externally bonded glass fibre reinforced polymer laminates. Approach: A total of 21 beams specimens of size 150, 250×3000 mm were cast and tested. Results: Out of the 21 specimens, … …Journal of Computer Science, Vol. 8, Issue 6 · 17 Mar 2012 · 7,084 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleDirect Model Reference Adaptive Controller Based-On Neural-Fuzzy Techniques for Nonlinear Dynamical SystemsHafizah Husain, Marzuki Khalid, Rubiyah YusofThis paper presents a direct neural-fuzzy-based Model Reference Adaptive Controller (MRAC) for nonlinear dynamical systems with unknown parameters. The two-phase learning is implemented to perform structure identification and parameter estimation for the controller. In the first phase, similarity index-based fuzzy c-means clustering technique extracts the fuzzy rules in the premise part for the neural-fuzzy controller. This technique enables the recruitment … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 6,939 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleA New Self-Adaptive Neuro Fuzzy Inference System for the Removal of Non-Linear Artifacts from the Respiratory SignalA. Bhavani Sankar, D. Kumar, K. SeethalakshmiProblem statement: In this study, a new ANFIS-based adaptive filter is proposed to remove the non-linear artifacts from the respiratory signal measured using MEMS based accelerometer sensor. The data recorded from the abdomen movement includes the respiratory signal, electromyogram, 50Hz power line interference and the random electrode noise. In order to avoid convergence into local extremes, the system employs ANFIS … …Journal of Computer Science, Vol. 8, Issue 5 · 16 Feb 2012 · 6,891 accessesView PDF Cite