Adaptive integral sliding mode control strategy for vehicular platoon with prescribed performance

This article studies the prescribed tracking performance control issue for vehicular platoon with external disturbances and unknown nonlinearities. A new tunnel prescribed performance function (TPPF) is designed to ensure that the design of vehicular platoon controller is independent of the initial tracking error (ITE), which can effectively reduce the design complexity. The performance boundaries defined by TPPF are distributed on the same side of the coordinate system, which leads to a more compact convergence process of the tracking error, and improves the tracking performance. Additionally, an adaptive mechanism is developed for estimating external disturbances, and the neural adaptive compensation term based on the radial basis function neural network (RBFNN) is proposed to approximate the unknown nonlinearities. Based on the designed TPPF, neural adaptive compensation term, and adaptive mechanism, a novel adaptive integral sliding mode control (ISMC) strategy for vehicular platoon is designed to ensure the string stability and achieve predefined tracking performance. Finally, the effectiveness and superiority of the designed strategy are verified through comparative numerical examples.