ABS control via extremum seeking with parameter tuning

A self-optimization routine integrated with the adaptation of the analytical tire model parameters is proposed for maximizing braking force without utilizing optimum slip value information. Most common extremum seeking algorithms in the open literature are searching for optimal operating point in order to maximize or minimize a given cost function which is measured on a real-time basis. The control algorithm introduced in this paper removes the on-line cost function measurement requirement and instead, an analytic approach with adaptive parameter tuning is developed along the extremum seeking algorithm. Stability, parameter convergence and reaching to the global maximum operating point of the unknown cost function is proven on a Lyapunov stability basis. Simulation study for ABS control under different road pavement conditions is given to illustrate the effectiveness of the proposed approach.