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The complex tasks such as surveillance, construction, search and rescue canbenefit of the maneuverability of multirotor Micro Aerial Vehicles (MAVs) toobtain robust, cooperative system behavior and formation control is a prominentcomponent of the these complex tasks. This work focuses on the problem ofthree-dimensional formation control of multirotor MAVs by using exclusivelyrelative sensory information. It proposes a centralized Nonlinear ModelPredictive Control (NMPC) approach in a leader-follower scheme. A realistic sixdegrees of freedom mathematical model of a multirotor MAVs is introduced andleveraged in the control laws. The formulation of the problem is performedbased on NMPC and relative sensing framework with respect to local coordinateframes of the robots. This type of formulation makes the formation independentof the full knowledge of global or common reference frames and the utilizationof expensive global localization sensors. Real-time Iteration (RTI) basedsolution to optimal control problem (OCP) is proposed by taking the novelformulation into account. An extensive scenario is designed to test andvalidate the strategy. Evaluation of the results suggests that satisfactoryrobust performance is achieved and maintained under model uncertainty and noisein local sensors and even in cases where the dynamics of the formation suddenlychanges.

Nonlinear Model Predictive Control for 3D Formation of Multirotor Micro Aerial Vehicles with Relative Sensing in Local Coordinates