We address the problem of real-time obstacle avoidance on low-friction road surfaces using spatial Nonlinear Model Predictive Control (NMPC). We use a nonlinear four-wheel vehicle dynamics model that includes load transfer. To overcome the computational difficulties we propose to use the ACADO Code Generation tool which generates NMPC algorithms based on the real-time iteration scheme for dynamic optimization. The exported plain C code is tailored to the model dynamics, resulting in faster run-times in effort for real-time feasibility. The advantages of the proposed method are shown through simulation.
An auto-generated nonlinear MPC algorithm for real-time obstacle avoidance of ground vehicles / Frasch, J V; Gray, A; Zanon, M; Ferreau, H J; Sager, S; Borrelli, F; Diehl, M. - (2013), pp. 6669836.4136-6669836.4141. ( European Control Conference 2013 (ECC'13) Zurich, Switzerland July 2013) [10.23919/ECC.2013.6669836].
An auto-generated nonlinear MPC algorithm for real-time obstacle avoidance of ground vehicles
Zanon M;
2013
Abstract
We address the problem of real-time obstacle avoidance on low-friction road surfaces using spatial Nonlinear Model Predictive Control (NMPC). We use a nonlinear four-wheel vehicle dynamics model that includes load transfer. To overcome the computational difficulties we propose to use the ACADO Code Generation tool which generates NMPC algorithms based on the real-time iteration scheme for dynamic optimization. The exported plain C code is tailored to the model dynamics, resulting in faster run-times in effort for real-time feasibility. The advantages of the proposed method are shown through simulation.| File | Dimensione | Formato | |
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