Throttle valve control using an inverse local linear model tree based on a Fuzzy neural network

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

A robust throttle valve control has always been an attractive problem since throttle by wire systems were established in the mid-nineties. Often in control strategy, a feedforward controller is adopted in which an inverse model is used. Mathematical inversions of models imply a high order of differentiation of the state variables and consequently noise effects. In general, neural networks are a very effective and popular tool mostly used for modeling. The inversion of a neural network produces real possibilities to involve the networks in the 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 in which two control loops are explicitly compared.
OriginalspracheEnglisch
Titel2008 7th IEEE International Conference on Cybernetic Intelligent Systems, CIS 2008
HerausgeberRichard A. Comley
Anzahl der Seiten6
VerlagIEEE - Institute of Electrical and Electronics Engineers Inc.
Erscheinungsdatum01.09.2008
Seiten234-239
Aufsatznummer4798943
ISBN (Print)978-1-4244-2914-1
ISBN (elektronisch)978-1-4244-2915-8
DOIs
PublikationsstatusErschienen - 01.09.2008
Extern publiziertJa
Veranstaltung7th Institute of Electrical and Electronics Engineers International Conference on Cybernetic Intelligent Systems - CIS2008 - London, Großbritannien / Vereinigtes Königreich
Dauer: 09.09.200810.09.2008
Konferenznummer: 7
http://www.cybernetic.org.uk/cis2008

DOI

Zuletzt angesehen

Publikationen

  1. Evaluation of Time/Phase Parameters in Frequency Measurements for Inertial Navigation Systems
  2. Isocodal and isospectral points, edges, and pairs in graphs and how to cope with them in computerized symmetry recognition
  3. The Influence of Note-taking on Mathematical Solution Processes while Working on Reality-Based Tasks
  4. Backstepping-based Input-Output Linearization of a Peltier Element for Ice Clamping using an Unscented Kalman Filter
  5. Understanding reading as a form of language-use
  6. What would Colin say?
  7. Are criminals better lie detectors? Investigating offenders' abilities in the context of deception detection
  8. Planar Multipole Resonance Probe: A kinetic model based on a functional analytic description
  9. How generative drawing affects the learning process
  10. Trajectory tracking using MPC and a velocity observer for flat actuator systems in automotive applications
  11. Encoding the law of State responsibility with courage and resolve
  12. How and Why Different Forms of Expertise Moderate Anchor Precision in Price Decisions
  13. Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic
  14. 3D characterization of beta-phases in AZ91D by synchrotron-radiation based microtomography
  15. More Evidence for Three Types of Cognitive Style
  16. Planar multipole resonance probe
  17. What goes around, comes around? Access and allocation problems in Global North-South waste trade
  18. Combined experimental–numerical study on residual stresses induced by a single impact as elementary process of mechanical peening
  19. Toward Automated Topology Optimization
  20. What is normal?
  21. Umweltrechtsschutz in China
  22. Argentine clustering of soy biodiesel production
  23. Instructional animation versus static pictures
  24. Mindfulness at work
  25. Daniel Fiott (ed.), The csdp in 2020: The EU’s legacy and ambition in security and defence
  26. Deep Rolling for Tailoring Residual Stresses of AA2024 Sheet Metals