Given the increase in computing power over the last decade, model predictive control has received renewed attention as a technique for accomplishing high-level vehicle control. However, tire nonlinearities present a challenge for rapidly solving the optimization problem required to do model predictive control. This paper presents an approach which extracts the tire nonlinearities outside the MPC optimization, leaving a convex problem that can be solved rapidly and with guaranteed optimality. Experimental results are presented from an MPC controller using this technique that demonstrate the controller’s ability to handle tire nonlinearities during highly dynamic manuevers that saturate the tires and induce lateral-longitudinal force coupling effects.

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