1. //
  2. Start
  3. //
  4. Publikationen
  5. Inversion of Fuzzy Neural Networks for t...
  6. Formate
  7. //

Inversion of Fuzzy Neural Networks for the Reduction of Noise in the Control Loop for Automotive Applications

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Standard

Inversion of Fuzzy Neural Networks for the Reduction of Noise in the Control Loop for Automotive Applications. / Nentwig, M.; Mercorelli, Paolo.
in: JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems, Jahrgang 3, Nr. 3, 2009, S. 83-89.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Harvard

Nentwig, M & Mercorelli, P 2009, 'Inversion of Fuzzy Neural Networks for the Reduction of Noise in the Control Loop for Automotive Applications', JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems, Jg. 3, Nr. 3, S. 83-89. <http://www.jamris.org/images/ISSUES/ISSUE-2009-03/JAMRIS_No03_2009_P_83-89.pdf>

APA

Nentwig, M., & Mercorelli, P. (2009). Inversion of Fuzzy Neural Networks for the Reduction of Noise in the Control Loop for Automotive Applications. JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems, 3(3), 83-89. http://www.jamris.org/images/ISSUES/ISSUE-2009-03/JAMRIS_No03_2009_P_83-89.pdf

Vancouver

Nentwig M, Mercorelli P. Inversion of Fuzzy Neural Networks for the Reduction of Noise in the Control Loop for Automotive Applications. JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems. 2009;3(3):83-89.

Bibtex

@article{f0069ea0ac8543b8add98a97bc6b4eba,
title = "Inversion of Fuzzy Neural Networks for the Reduction of Noise in the Control Loop for Automotive Applications",
abstract = "A robust throttle valve control has been an attractive problem since throttle bywire systems were established in the mid-nineties. Control strategies often use afeed-forward controller which use an inverse model; however, mathematical model inversions imply a high order of differentiation of the state variables resulting in noise effects. In general, neural networks are a very effective and popular tool for modeling. The inversion of a neural network makes it possible to use these networks in control problem schemes. This paper presents a control strategy based upon an inversion of a feed-forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. Simulated results from real data measurements are presented, and two control loops are explicitly compared.",
keywords = "Engineering",
author = "M. Nentwig and Paolo Mercorelli",
year = "2009",
language = "English",
volume = "3",
pages = "83--89",
journal = "JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems",
issn = "1897-8649",
publisher = "Sciendo",
number = "3",

}

RIS

TY - JOUR

T1 - Inversion of Fuzzy Neural Networks for the Reduction of Noise in the Control Loop for Automotive Applications

AU - Nentwig, M.

AU - Mercorelli, Paolo

PY - 2009

Y1 - 2009

N2 - A robust throttle valve control has been an attractive problem since throttle bywire systems were established in the mid-nineties. Control strategies often use afeed-forward controller which use an inverse model; however, mathematical model inversions imply a high order of differentiation of the state variables resulting in noise effects. In general, neural networks are a very effective and popular tool for modeling. The inversion of a neural network makes it possible to use these networks in control problem schemes. This paper presents a control strategy based upon an inversion of a feed-forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. Simulated results from real data measurements are presented, and two control loops are explicitly compared.

AB - A robust throttle valve control has been an attractive problem since throttle bywire systems were established in the mid-nineties. Control strategies often use afeed-forward controller which use an inverse model; however, mathematical model inversions imply a high order of differentiation of the state variables resulting in noise effects. In general, neural networks are a very effective and popular tool for modeling. The inversion of a neural network makes it possible to use these networks in control problem schemes. This paper presents a control strategy based upon an inversion of a feed-forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. Simulated results from real data measurements are presented, and two control loops are explicitly compared.

KW - Engineering

M3 - Journal articles

VL - 3

SP - 83

EP - 89

JO - JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems

JF - JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems

SN - 1897-8649

IS - 3

ER -

In der gleichen Zeitschrift

Two cascaded and extended kalman filters combined with sliding mode control for sustainable management of marine fish stocks

Benz, K., Rech, C., Mercorelli, P. & Sergiyenko, O., 2020, in: Journal of Automation, Mobile Robotics and Intelligent Systems. 14, 3, S. 28-35 8 S.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Weitere Publikationen dieser Person(en)

An Over-Actuated Hexacopter Tilt-Rotor UAV Prototype for Agriculture of Precision: Modeling and Control

Pimentel, G. O., Santos, M. F. D., Lima, J., Mercorelli, P. & Fernandes, F. M., 15.01.2025, in: Sensors. 25, 2, 27 S., 479.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Automatic Tuning of Extended Kalman Filter in Synchronous Reluctance Motor Drives with a Master-Slave Configuration

Rigon, S., Haus, B., Mercorelli, P. & Zigliotto, M., 27.02.2025, (Elektronische Veröffentlichung vor Drucklegung) in: IEEE Open Journal of Power Electronics. 14 S.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Dynamic Performance Analysis and Fault Ride-Through Enhancement by a Modified Fault Current Protection Scheme of a Grid-Connected Doubly Fed Induction Generator

Talani, R. A., Kaloi, G. S., Ali, A., Bijarani, M. A., Abbas, G., Hatatah, M., Mercorelli, P. & Touti, E., 02.2025, in: Machines. 13, 2, 20 S., 110.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Inner loop model predictive control and outer loop PI reference governor for PMSMs with input and state saturation for torque control

Zwerger, T. & Mercorelli, P., 01.02.2025, in: Mathematics and Computers in Simulation. 228, S. 178-201 24 S.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Neural Network-Based Finite-Time Control for Stochastic Nonlinear Systems with Input Dead-Zone and Saturation

Kharrat, M., Krichen, M., Alhazmi, H. & Mercorelli, P., 11.01.2025, (Elektronische Veröffentlichung vor Drucklegung) in: Arabian Journal for Science and Engineering. 11 S.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Dokumente

Links

Zuletzt angesehen

Publikationen

  1. Using the flatness of DC-Drives to emulate a generator for a decoupled MPC using a geometric approach for motion control in Robotino
  2. Dynamic Lot Size Optimization with Reinforcement Learning
  3. On robustness properties in permanent magnet machine control by using decoupling controller
  4. Classical PI Controllers with Anti-Windup Techniques Applied on Level Systems
  5. A model predictive control in Robotino and its implementation using ROS system
  6. Introducing parametric uncertainty into a nonlinear friction model
  7. Stepwise-based optimizing approaches for arrangements of loudspeaker in multi-zone sound field reproduction
  8. A geometric approach for controlling an electromagnetic actuator with the help of a linear Model Predictive Control
  9. A localized boundary element method for the floating body problem
  10. Mapping interest rate projections using neural networks under cointegration
  11. The Influence of Note-taking on Mathematical Solution Processes while Working on Reality-Based Tasks
  12. Robust Flatness Based Control of an Electromagnetic Linear Actuator Using Adaptive PID Controller
  13. Gaussian processes for dispatching rule selection in production scheduling
  14. Performance analysis for loss systems with many subscribers and concurrent services
  15. Comments on "Tracking Control of Robotic Manipulators With Uncertain Kinematics and Dynamics"
  16. A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints
  17. An analytical approach to evaluating bivariate functions of fuzzy numbers with one local extremum
  18. On the Nonlinearity Compensation in Permanent Magnet Machine Using a Controller Based on a Controlled Invariant Subspace
  19. An Orthogonal Wavelet Denoising Algorithm for Surface Images of Atomic Force Microscopy
  20. Stability analysis of a linear model predictive control and its application in a water recovery process
  21. Robust Control of Mobile Transportation Object with 3D Technical Vision System
  22. Data-Driven flood detection using neural networks
  23. Passive Peak Voltage Sensor for Multiple Sending Coils Inductive Power Transmission System
  24. A Gait Pattern Generator for Closed-Loop Position Control of a Soft Walking Robot
  25. A two-stage Kalman estimator for motion control using model predictive strategy
  26. Continuous 3D scanning mode using servomotors instead of stepping motors in dynamic laser triangulation
  27. A general structural property in wavelet packets for detecting oscillation and noise components in signal analysis
  28. A denoising procedure using wavelet packets for instantaneous detection of pantograph oscillations
  29. Perfect anti-windup in output tracking scheme with preaction
  30. Simulation based comparison of safety-stock calculation methods
  31. Primary Side Circuit Design of a Multi-coil Inductive System for Powering Wireless Sensors
  32. Continuous and Discrete Concepts for Detecting Transport Barriers in the Planar Circular Restricted Three Body Problem
  33. Convolutional Neural Networks
  34. A New Framework for Production Planning and Control to Support the Positioning in Fields of Tension Created by Opposing Logistic Objectives
  35. Cognitive load and instructionally supported learning with provided and learner-generated visualizations
  36. Using cross-recurrence quantification analysis to compute similarity measures for time series of unequal length with applications to sleep stage analysis
  37. PI and Fuzzy Controllers for Non-Linear Systems
  38. Long-term memory predictors of adult language learning at the interface between syntactic form and meaning
  39. Dynamically adjusting the k-values of the ATCS rule in a flexible flow shop scenario with reinforcement learning
  40. Modeling and numerical simulation of multiscale behavior in polycrystals via extended crystal plasticity
  41. Transductive support vector machines for structured variables
  42. Switching Dispatching Rules with Gaussian Processes
  43. A computational study of a model of single-crystal strain-gradient viscoplasticity with an interactive hardening relation
  44. Multi-view discriminative sequential learning
  45. Combining multiple investigative approaches to unravel functional responses to global change in the understorey of temperate forests
  46. Web-scale extension of RDF knowledge bases from templated websites
  47. Improving short-term academic performance in the flipped classroom using dynamic geometry software
  48. Positioning Improvement for a Laser Scanning System using cSORPD control