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

Zanon M;
2013-01-01

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.
2013
978-3-033-03962-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11771/7196
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