<p>To address the issue of poor performance in traditional collective pitch feedforward control for tilt-rotor propulsion systems, an adaptive feedforward control method based on the invariance principle and least square method is proposed. First, a nonlinear estimator is utilized to estimate the load torque at the turboshaft engine. Once obtained, this load torque serves as the measurable disturbance variable. Subsequently, a design approach for the feedforward controller of the turboshaft engine is presented based on the invariance principle, replacing the conventional proportional feedforward controller with a dynamic one. Additionally, to enhance robustness, online identification of parameters for the state space equation of the turboshaft engine is performed using least square estimation. The adaptive law for adjusting parameters of the feedforward controller is derived from considering both transfer function and state space relationships. Furthermore, ℒ<sub>2</sub> stability analysis demonstrates closed-loop system stability. Finally, simulation verification using a comprehensive tiltrotor/engine model confirms that our proposed adaptive feedforward control method effectively reduces power turbine overshoot.</p>

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Adaptive Feedforward Control Method of Turboshaft Engine Based on Invariance Principle and Least Square Method

  • Shancheng Li,
  • Yong Wang,
  • Bo Huang,
  • Haibo Zhang

摘要

To address the issue of poor performance in traditional collective pitch feedforward control for tilt-rotor propulsion systems, an adaptive feedforward control method based on the invariance principle and least square method is proposed. First, a nonlinear estimator is utilized to estimate the load torque at the turboshaft engine. Once obtained, this load torque serves as the measurable disturbance variable. Subsequently, a design approach for the feedforward controller of the turboshaft engine is presented based on the invariance principle, replacing the conventional proportional feedforward controller with a dynamic one. Additionally, to enhance robustness, online identification of parameters for the state space equation of the turboshaft engine is performed using least square estimation. The adaptive law for adjusting parameters of the feedforward controller is derived from considering both transfer function and state space relationships. Furthermore, ℒ2 stability analysis demonstrates closed-loop system stability. Finally, simulation verification using a comprehensive tiltrotor/engine model confirms that our proposed adaptive feedforward control method effectively reduces power turbine overshoot.