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A comparison between HMLP and HRBF for attitude control.

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Summary

New hypercomplex algebra control strategies enhance spacecraft attitude control. Neural networks, particularly the hypercomplex multilayer perceptron, show superior performance against disturbances compared to traditional methods.

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Area of Science:

  • Aerospace Engineering
  • Control Systems Theory
  • Hypercomplex Algebra

Background:

  • Spacecraft attitude control is crucial for mission success.
  • Traditional control methods face challenges with complex dynamics and external disturbances.
  • Hypercomplex algebra offers a novel framework for advanced control strategies.

Purpose of the Study:

  • To introduce and evaluate two novel attitude control strategies for rigid bodies using hypercomplex algebra.
  • To compare the performance of these new strategies against classical and adaptive controllers.
  • To investigate the efficacy of hypercomplex neural networks in spacecraft attitude control.

Main Methods:

  • Development of two parallel controllers based on quaternion algebra: a proportional-derivative (PD) feedback controller and a feedforward controller.
  • Implementation of the feedforward controller using a hypercomplex multilayer perceptron (HMLP) or a hypercomplex radial basis function (HRBF) neural network.
  • Extensive simulations to assess controller performance under various conditions, including external disturbances.

Main Results:

  • The proposed hypercomplex control strategies demonstrate improved performance over classical PD and adaptive controllers.
  • Hypercomplex neural network controllers, especially the HMLP, exhibit enhanced robustness against external disturbances.
  • The HMLP network shows superior adaptability to novel trajectories not encountered during the learning phase.

Conclusions:

  • Hypercomplex algebra provides an effective framework for developing advanced spacecraft attitude control systems.
  • The integration of hypercomplex neural networks offers significant advantages in terms of performance and robustness.
  • The HMLP controller presents a promising solution for challenging attitude control scenarios, particularly those involving unpredicted maneuvers or disturbances.