Search for dissertations about: "Fuzzy gain scheduling"

Found 3 swedish dissertations containing the words Fuzzy gain scheduling.

  1. 1. Fuzzy Control for an Unmanned Helicopter

    University dissertation from Institutionen för datavetenskap

    Author : Bourhane Kadmiry; Dimiter Driankov; [2002]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Helicopter; Robust control; Fuzzy gain scheduling; Gradient descent method; TECHNOLOGY Information technology Computer science; TEKNIKVETENSKAP Informationsteknik Datavetenskap;

    Abstract : The overall objective of the Wallenberg Laboratory for Information Technology and Autonomous Systems (WITAS) at Linköping University is the development of an intelligent command and control system, containing vision sensors, which supports the operation of a unmanned air vehicle (UAV) in both semi- and full-autonomy modes. One of the UAV platforms of choice is the APID-MK3 unmanned helicopter, by Scandicraft Systems AB. READ MORE

  2. 2. Observers and controllers for Takagi-Sugeno fuzzy systems

    University dissertation from Örebro : Örebro universitetsbibliotek

    Author : Pontus Bergsten; Örebro universitet.; [2001]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TECHNOLOGY Information technology Computer science; TEKNIKVETENSKAP Informationsteknik Datavetenskap; Computer and Systems Science; Data- och systemvetenskap;

    Abstract : This thesis studies analysis and design issues for observers anc controllers for Takagi-Sugeno (TS) fuzzy systems. Many physical systems are nonlinear in nature and using the well known linear techniques for such systems may result in bad performance, and even instability. READ MORE

  3. 3. Reinforcement Learning and Distributed Local Model Synthesis

    University dissertation from Linköping : Linköping University Electronic Press

    Author : Tomas Landelius; Hans Knutsson; Charles W. Anderson; [1997]
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TECHNOLOGY; TEKNIKVETENSKAP;

    Abstract : Reinforcement learning is a general and powerful way to formulate complex learning problems and acquire good system behaviour. The goal of a reinforcement learning system is to maximize a long term sum of instantaneous rewards provided by a teacher. READ MORE