What question did this study set out to answer?

To develop a robust hierarchical control framework that achieves precise position tracking and stable attitude regulation in quadrotors facing nonlinear dynamics and time-varying disturbances.

November 18, 2025SensorsOpen Access

A Hierarchical PSMC–LQR Control Framework for Accurate Quadrotor Trajectory Tracking

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Authors

SCS.-C. Chen XZXinyu Zhu YFYichao Fang

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Overview

Simulation study demonstrates enhanced quadrotor trajectory tracking using hierarchical predictive and linear quadratic control, indicating improved flight stability under wind disturbances.

Key Points

To develop a robust hierarchical control framework that achieves precise position tracking and stable attitude regulation in quadrotors facing nonlinear dynamics and time-varying disturbances.
Designed an outer-loop particle swarm optimization-compensated model predictive controller (PSMC) to reduce prediction errors and an inner-loop linear quadratic regulator (LQR) with gain scheduling for rapid attitude stabilization.
Conducted a Lyapunov-based stability analysis to ensure closed-loop convergence under control constraints.
Evaluated tracking performance against a standard MPC-LQR baseline using numerical simulations along a helical reference trajectory in calm air and under wind disturbances.
Under calm conditions, reduced mean tracking error by more than 13.2% in the x-direction, 17.1% in the y-direction, and 28.0% in the z-direction relative to the MPC-LQR baseline.
Under wind disturbances, decreased mean tracking error by more than 34.0% along the x-axis, 26.2% along the y-axis, and 46.8% along the z-axis compared to conventional baseline control.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/6a882f6017733fb165eb338b https://doi.org/10.3390/s25227032

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November 18, 2025SensorsOpen Access

A Hierarchical PSMC–LQR Control Framework for Accurate Quadrotor Trajectory Tracking

View Full Paper

Ask AI

Bookmark

Authors

SCS.-C. Chen XZXinyu Zhu YFYichao Fang

Discussion

Member takes

Overview

Simulation study demonstrates enhanced quadrotor trajectory tracking using hierarchical predictive and linear quadratic control, indicating improved flight stability under wind disturbances.

Key Points

To develop a robust hierarchical control framework that achieves precise position tracking and stable attitude regulation in quadrotors facing nonlinear dynamics and time-varying disturbances.
Designed an outer-loop particle swarm optimization-compensated model predictive controller (PSMC) to reduce prediction errors and an inner-loop linear quadratic regulator (LQR) with gain scheduling for rapid attitude stabilization.
Conducted a Lyapunov-based stability analysis to ensure closed-loop convergence under control constraints.
Evaluated tracking performance against a standard MPC-LQR baseline using numerical simulations along a helical reference trajectory in calm air and under wind disturbances.
Under calm conditions, reduced mean tracking error by more than 13.2% in the x-direction, 17.1% in the y-direction, and 28.0% in the z-direction relative to the MPC-LQR baseline.
Under wind disturbances, decreased mean tracking error by more than 34.0% along the x-axis, 26.2% along the y-axis, and 46.8% along the z-axis compared to conventional baseline control.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/6a882f6017733fb165eb338b https://doi.org/10.3390/s25227032

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