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Decentralized nonlinear model predictive control of multiple flying robots

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3 Author(s)
Shim, D.H. ; Autonomously Controlled Advanced Platforms, Berkeley, CA, USA ; Kim, H.J. ; Sastry, S.

In this paper, we present a nonlinear model predictive control (NMPC) for multiple autonomous helicopters in a complex environment. The NMPC provides a framework to solve optimal discrete control problems for a nonlinear system under state constraints and input saturation. Our approach combines stabilization of vehicle dynamics and decentralized trajectory generation, by including a potential function that reflects the state information of possibly moving obstacles or other vehicles to the cost function. We present various realistic scenarios which show that the integrated approach outperforms a hierarchical structure composed of a separate controller and a path planner based on the potential function method. The proposed approach is combined with an efficient numerical algorithm, which enables the real-time nonlinear model predictive control of multiple autonomous helicopters.

Published in:

Decision and Control, 2003. Proceedings. 42nd IEEE Conference on  (Volume:4 )

Date of Conference:

9-12 Dec. 2003

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