Nonlinear Model Predictive Control of a Dual-Axis Tilting Quadcopter

The dual-axis tilting quadcopter holds great promise for applications that demand both high performance and full actuation in a 6DOF Cartesian task space; however, control system design is complicated by its complex dynamics and over-actuation. In this paper, we propose a real-time optimization-based framework for controlling this system. Our formulation, which combines Nonlinear Model Predictive Control (NMPC) with a control allocation stage, allows the optimizer to fully exploit the rotors’ tilt actuation despite their strongly nonlinear dynamics, input constraints, and actuator redundancy. Numerical simulation is provided to illustrate the performance of the proposed control algorithm.