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Lifting Body Reentry Vehicle Guidance in Landing using Fuzzy Algorithms

Mohammadi, Hamid Reza | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 42702 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Technology
  6. Advisor(s): Asadian, Nima
  7. Abstract:
  8. In this thesis, active guidance of a reentry vehicle using fuzzy logic is investigated. The guidance commands of the reentry vehicle (pitch and bank angles) are computed based on estimation of the final conditions, including range and cross-range errors and time-to-go. The final conditions are predicted utilizing a neural network. Inputs of this neural network are the current states of the vehicle and flight time. The first advantage of this approach is that no reference trajectory is required, which is mostly generated optimally for ideal conditions. Moreover, the methods based on keeping the nominal trajectory produce severe guidance commands for sudden disturbances (e.g. wind gusts), which is not the case in our approach. On the other hand, the path constraints (e.g. angle of attack, dynamic pressure, and heat flux) can be included in the guidance logic directly. To assess the capabilities of the proposed active fuzzy guidance logic, a Monte-Carlo simulation is carried out for a variety of initial conditions errors of the reentry vehicle. The results show that the active guidance based on final condition prediction is accurate in guiding the vehicle through the atmosphere and also produces smoother guiding commands. Anyhow, moderate guidance command rates are seen for the times that fuzzy logic switches between fuzzy rules
  9. Keywords:
  10. Guidance ; Neural Network ; Monte Carlo Method ; Reentry Vehicles ; Space Shuttle ; Fuzzy Guidance

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