Health-aware Optimization-based Control Design: Application to Autonomous Racing based State of Charge

Abstract

In this paper, an innovative health-aware control approach is presented for autonomous racing vehicles. Based on a dynamical model of the vehicle, a controller is computed with the general objective is maximize progress on the track subject to win racing and save energy. The main contribution of the paper consists in preserving the state of charge (SoC) and optimizing a lap time to achieve the best path of a racing vehicle. The control design is divided into two parts, path planner and controller. The first optimization problem is related to the path planner where the objective is to optimize the lap time and maximize the SoC to obtain the best trajectory under the constraints of the circuit. The proposed approach is solved by LMI based Model Predictive Control (MPC) driven from Lyapunov stability. The second part is focused on a controller gain synthesis solved by LMI formulation with integral action for tracking the trajectory obtained by the planner. The proposed approach is evaluated in simulation and results show the effectiveness of the proposed planner for optimizing the lap time and especially for maximizing the SoC of the battery.