Optimization imposition upon drone gimbal control electronics

  • Erhe Zheng Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14853, USA
  • Timothy Sands Department of Mechanical Engineering (SCPD), Stanford University, Stanford, CA 94305, USA
Ariticle ID: 69
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Keywords: proportional plus velocity controller, double integrator patching filter, control law inversion patching filter, real-time optimal control, open loop control, feedback control, Monte Carlo model


The goal of the manuscript is to design a relatively good control structure for the noise suppression of a drone’s camera gimbal action. The gimbal’s movement can be simplified as a rest-to-rest reorientation system that can achieve the boundary result of a dynamic system. Six different control architectures are proposed and evaluated based on their ability to control the trajectory of the dynamic-system position and speed, their running time, and their quadratic cost. The robustness of the control architecture to uncertainties in inertia and sensor noise is also analyzed. Monte Carlo figures are used to assess the performance of the six control systems. The conditions for applying different architectures are identified through this analysis. The analysis and experimental tests reveal the most suitable control of the drone’s camera gimbal rotation.


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How to Cite
Zheng, E., & Sands, T. (2023). Optimization imposition upon drone gimbal control electronics. Journal of AppliedMath, 1(2), 69. https://doi.org/10.59400/jam.v1i2.69