Adaptive Control of Dual-Rotor Rotational System with Unknown Geometry and Unknown Inertia
Mohammad Mirtaba, Jhon Manuel Portella Delgado, Ankit Goel
TL;DR
The paper tackles controlling a dual-rotor rotational system (DRRS) with unknown inertia and rotor geometry. It combines input-output feedback linearization with a finite-time convergent parameter estimator to form an adaptive controller, and applies a linear controller on the resulting linearized dynamics to achieve tracking for the outputs $\phi_{\rm h}$ and $\phi_{\rm v}$. Key contributions include a complete adaptive augmentation for unknown parameters $\Theta_1,\Theta_2$, a structured strict-feedback formulation, and thorough numerical validation showing constant and harmonic command tracking along with robustness to parameter variations. This approach provides stability guarantees and practical tracking performance for complex multicopter-like subsystems despite unknown geometry and inertia, highlighting its potential for robust aerial and rotor-based platforms.
Abstract
This paper develops an input-output feedback linearization-based adaptive controller to stabilize and regulate a dual-rotor rotational system (DRRS), whose inertial properties as well as the geometric configuration of rotors are unknown. First, the equations of motion governing the dynamics of DRRS are derived using the Newton-Euler approach. Next, an input-output feedback linearization technique is used to linearize the dynamics from the rotor speeds to the angular position of the system. A finite-time convergent estimator, based on the portion of the DRRS dynamics, is used to update the required parameters in the controller. Finally, the proposed controller is validated in both step and harmonic command-following problems, and the robustness of the controller to the system's parameters is demonstrated.