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Implementation of a Leader-Follower Multi-Agent Model Predictive Control Algorithm on Micro Helicopters


Marvin Rüppel

Master Thesis, FS123 (10252)

In this master thesis we show the successful implementation of several fast model predictive control schemes (MPC) on micro helicopters, flying by themselves and in formation, in an indoor flightspace. On the real testbed, the helicopters positions are sampled at 50fps by an infrared camera system and the closed-loop system is controlled by a controller running on in-house software. The convex multi-stage problems of the receding horizon method are solved using code, which is generated by Forces, a fast optimization solver, that is based on interior-point methods. The resulting model predictive controller is based on linear time invariant dynamics, with a state space size of 11 and input space of 4 for each helicopter. The terminal cost is chosen as the solution to the discrete algebraic Ricatti equation. This choice is shown to improve tracking performance. Further, with the achieved fast computation times and the implementation of a special initialization routine, we are able to fly up to 5 helicopters simultaneously, a number only limited by the number of radio controllers. The second main contribution is a formation control scheme for multiple micro helicopters, which are connected based on a leader-follower principle. In this approach, one helicopter, identified as the leader, shares information with the other helicopters present, all defined as followers. The leader solves its own multi-stage problem in MPC fashion. This solution contains the current position and the forecasted position and velocity information. This data is transmitted to the followers, which take this into account to optimize their own position while maintaining a constant distance.


Type of Publication:

(12)Diploma/Master Thesis

S. M. Huck

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2013:IFA_4637
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