Modeling Parasitic Dynamics of a 3-DOF Gimbal-Style Attitude Test Rig

Ground-based attitude test rigs are essential for safely evaluating Unmanned Aerial Vehicle (UAV) flight controllers and mission performance, yet the parasitic inertia, mechanical coupling, and joint friction of the rig hardware often influence the vehicle’s true free-flight dynamics. In larger and heavier systems, the test rig can be considered transparent relative to the vehicle dynamics, but this approximation fails when both the vehicle and the rig systems have comparable dynamics. 3-DOF gimbal test rigs similar to the one used in this work require complex modeling due to their configuration-dependent dynamics. This paper addresses this challenge by presenting a framework for inertia and friction modeling. We analytically derive the configuration-dependent generalized inertia matrix and coupling terms as a function of measurable joint configurations, describing the nonlinear kinematic and dynamic relations between the rig link frames and the mounted vehicle. To validate accuracy, the derived analytical model, including the systemic Jacobians and reference frame transformations, is cross-validated against an independent Simscape Multibody model of the physical system with good agreement. The resulting system model supports estimation of the parasitic rig effects directly from rig measurements. The identified friction parameters were verified using independent free-decay experiments across all three axes. The resulting angular response RMS errors ranged from 2.11∘ to 7.06∘, cycle-frequency errors remained below 0.043 Hz, peak-to-peak amplitude RMS errors below 6.86∘, and logarithmic-decrement RMS errors below 0.13. The inertia matrix and the Coriolis matrix terms have also been validated numerically with relative Frobenius norm errors up to 0.25% and 14.29% respectively, and a combined response NRMSE of less than 4.69%. The same Simscape model is used to verify the estimated parameter simulation errors across multiple representative experiments. This work is a basis for a scalable framework of high-fidelity ground testing of advanced UAV systems.