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Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study.

H A Hashim1, M A Abido2

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Summary
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This study compares evolutionary algorithms for optimizing fuzzy controllers in twin rotor systems. Gravitational Search Algorithm (GSA) demonstrated superior performance in enhancing system stability and tracking accuracy.

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Area of Science:

  • Control Engineering
  • Robotics
  • Computational Intelligence

Background:

  • The twin rotor multi-input multi-output (MIMO) system (TRMS) presents significant control challenges due to its inherent nonlinearities and cross-coupling effects.
  • Fuzzy Proportional Derivative (PD) controllers offer a robust approach for managing complex systems like the TRMS.

Purpose of the Study:

  • To comparatively evaluate the efficacy of prominent evolutionary optimization techniques for designing fuzzy PD controllers for the TRMS.
  • To determine the most effective optimization method for improving TRMS stability, nonlinearity cancellation, and trajectory tracking performance.

Main Methods:

  • Optimization of fuzzy PD controller gains for the TRMS using four evolutionary algorithms: Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Differential Evolution (DE).
  • Comparative analysis of controller performance under various disturbances to assess system response, stability, and tracking accuracy.

Main Results:

  • All investigated evolutionary techniques successfully optimized fuzzy PD controller gains, leading to improved TRMS performance.
  • The Gravitational Search Algorithm (GSA) exhibited superior performance regarding solution quality and convergence speed compared to PSO, ABC, and DE.
  • GSA-optimized controllers demonstrated enhanced system stability, effective nonlinearity cancellation, reduced coupling effects, and accurate trajectory tracking for pitch and yaw angles.

Conclusions:

  • Gravitational Search Algorithm (GSA) is identified as the most effective evolutionary technique for optimizing fuzzy PD controllers for the twin rotor system (TRMS).
  • The optimized controllers significantly improve the TRMS's ability to handle disturbances and achieve precise control of pitch and yaw angles.