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In the field of dynamic system control, precise tuning of controllers is essential for achieving optimal performance. This paper explores the tuning of the linear quadratic regulator (LQR) controller in a two-degree-of-freedom (2-DoF) helicopter using optimization techniques. The 2-DoF helicopter, known for its application in control and flight dynamics research, is employed here to evaluate the effectiveness of two optimization techniques. A genetic algorithm (GA) and particle swarm optimization (PSO) were implemented and compared to adjust the LQR controller parameters of the helicopter, aiming to enhance its performance in terms of stability and accuracy. The results show that the applied optimization methods enable effective tuning of the LQR controller, significantly improving the system’s performance.

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LQR Control Tuning Applied in a 2-DoF Helicopter Based on Optimization Algorithms

  • 会议论文

  • 发表日期：

    2025年

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  • García Jaime Jhovani,
  • García Mejía Juan Fernando,
  • Granda Gutiérrez Everardo Efrén,
  • Flores Fuentes Allan Antonio

摘要

In the field of dynamic system control, precise tuning of controllers is essential for achieving optimal performance. This paper explores the tuning of the linear quadratic regulator (LQR) controller in a two-degree-of-freedom (2-DoF) helicopter using optimization techniques. The 2-DoF helicopter, known for its application in control and flight dynamics research, is employed here to evaluate the effectiveness of two optimization techniques. A genetic algorithm (GA) and particle swarm optimization (PSO) were implemented and compared to adjust the LQR controller parameters of the helicopter, aiming to enhance its performance in terms of stability and accuracy. The results show that the applied optimization methods enable effective tuning of the LQR controller, significantly improving the system’s performance.