APPLYING MODEL PREDICTIVE CONTROL FOR QUADROTOR STATE STABILIZATION IN THE PRESENCE OF DYNAMIC OBSTACLES
Abstract
This paper proposes a Nonlinear Model Predictive Control (NMPC) approach applied to a quadrotor to simultaneously maintain position and avoid 3D dynamic obstacles. Based on a 6-degree-of-freedom (6-DOF) dynamic model, the NMPC controller continuously solves a nonlinear programming problem subject to constraints regarding a safe spatial region—incorporating a buffer zone to compensate for mechanical inertia—and actuator capacity limits. Numerical simulations utilizing the CasADi/IPOPT solver were conducted to evaluate the system under two scenarios: abrupt avoidance (prioritizing position tracking) and smooth avoidance (optimizing control signals). The results demonstrate that the algorithm not only successfully prevents collisions with continuously moving obstacles but also offers flexibility in fine-tuning flight behavior through the prediction horizon and weighting matrices, thereby satisfying diverse practical operational requirements.
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