This paper presents a stable, suboptimal, collision-free target tracking technique for a quadcopter based on convex Model Predictive Control. It develops an approximate linear state-space model for the quadcopter dynamics by linearizing around a hover condition. The quadcopter’s path is constrained by a sequence of planes tangent to the surface of obstacles. When implemented in a receding horizon, the orientation of these planes adapt to changes in the environment. A softened terminal constraint is used to improve stability characteristics while avoiding feasibility errors. The sequence of control actions are expressed as perturbations on a stabilizing feedback law expanded over a finite prediction horizon. Simulations demonstrate the technique can be used to avoid spherical obstacles in a target tracking scenario.
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