This paper presents a guaranteed cost adaptive control (GCAC) algorithm for vehicular platoons with nonlinear dynamics (i.e., combined nonlinearities of manifold dynamics, aerodynamic drag, unmodeled dynamics, etc.) and actuator delay (i.e., fueling and braking delay). First of all, a nonlinear mathematic model of the platoon’s longitudinal movement is established, which is shown to be a great improvement of the existing models. The controller is designed by splitting the new model into a linear part and a nonlinear one. In particular, we use a radial basis function neural network (RBFNN) to compensate for the nonlinear part by making precise estimation of it based on a decentralized adaptation law. Then a guaranteed cost controller is designed based on the linear part and the adaptive neural network compensator. The obtained control scheme achieves the objective of both individual vehicle stability and platoon string stability. Simulations are given to demonstrate the effectiveness of the proposed method.

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