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Tuning Protocol Changes Quadrotor Controller Rankings

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Xuan-Quy Dao et al. compared cascaded PID, hovering LQR, BL-SMC, linear MPC with LQR fallback (LMPC-F), LMPC-F with preview enabled, and a geometric SO(3) controller on a nonlinear plant that includes rotor gyroscopic coupling, motor lag, and saturation. The study found that after adopting a unified twelve-candidate tuning protocol, the average RMSE ranking under a fixed baseline changed, with BL-SMC rising from last place to first; this ranking was reproduced on 50 new implementations and remained unchanged under a 48-candidate budget. The main study included 556 50 Hz episodes, 400 paired evaluation episodes, and a 48-cell MPC factor experiment; the confirmation study used 1462 episodes to repeat evaluations on 50 new implementations, with tuning budgets of 12, 24, and 48 candidates. In timing tests, replaying measured command-call latency caused three of the four nominal MPC configurations to terminate on a desktop computer, and all four to terminate on a Raspberry Pi 5; after setting the solver iteration cap to 100, no deadline misses occurred among the tested nominal timing configurations.

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  1. Reproducible Simulation Study of How Tuning, Reference Preview, Actuator Modeling, and Fallback Policies Affect Quadrotor Controller Comparisons

    The study compares cascade PID, hover LQR, BL-SMC, linear MPC with LQR fallback (LMPC-F), a preview-enabled LMPC-F, and a geometric SO(3) controller on a nonlinear plant with rotor gyroscopic coupling, motor lag, and saturation. It finds that a unified twelve-candidate tuning protocol changed the mean-RMSE ranking obtained under fixed baseline settings, moving BL-SMC from last to first; the new ranking recurred on 50 fresh realizations and remained unchanged under a 48-candidate budget.

    arXiv cs.RO ·

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