This work presents an embedded nonlinear model predictive control (NMPC) strategy for autonomous vehicles under a minimum time objective. The time-optimal control problem is stated in a path-parametric formulation such that existing reliable numerical methods for real-time nonlinear MPC can be used. Building on previous work on timeoptimal driving, we present an approach based on a sequential quadratic programming type algorithm with online propagation of second order derivatives. As an illustration of our method, we provide closed-loop simulation results based on a vehicle model identified for small-scale electric race cars.
Time-optimal Race Car Driving using an Online Exact Hessian based Nonlinear MPC Algorithm
Zanon M;
2016-01-01
Abstract
This work presents an embedded nonlinear model predictive control (NMPC) strategy for autonomous vehicles under a minimum time objective. The time-optimal control problem is stated in a path-parametric formulation such that existing reliable numerical methods for real-time nonlinear MPC can be used. Building on previous work on timeoptimal driving, we present an approach based on a sequential quadratic programming type algorithm with online propagation of second order derivatives. As an illustration of our method, we provide closed-loop simulation results based on a vehicle model identified for small-scale electric race cars.File | Dimensione | Formato | |
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