# Adaptive Sliding Mode Control Incorporating Improved Integral Compensation Mechanism for Vehicle Platoon with Input Delays

## TL;DR

This paper proposes a new adaptive control method for vehicle platoons to handle input delays and changing control conditions, improving stability and performance.

## Contribution

An improved integral compensation mechanism and RBFNN-based adaptive updating method are combined for vehicle platoon control with input delays.

## Key findings

- The improved ICM enhances robustness against input delays in vehicle platoons.
- The RBFNN-based adaptive mechanism effectively handles unknown time-varying control coefficients.
- The proposed control strategy outperforms existing methods in numerical comparisons.

## Abstract

This study focuses on investigating the adaptive sliding mode control (SMC) problem for connected vehicles with input delays and unknown time-varying control coefficients. As a result of wear and tear of mechanical components, throttle response lags, and the internal data processing time of the controller, input delays widely exist in vehicle actuators. Since input delays may lead to instability of the vehicle platoon, an improved integral compensation mechanism (ICM) with the adjustment factor for input delays is developed to improve the platoon’s robustness. As the actuator efficiency, drive mechanism, and load of the vehicle may change during operation, the control coefficients of vehicle dynamics are usually unknown and time-varying. A novel adaptive updating mechanism utilizing a radial basis function neural network (RBFNN) is designed to deal with the unknown time-varying control coefficients, thereby improving the vehicle platoon’s tracking performance. By integrating the improved ICM and the RBFNN-based adaptive updating mechanism (RBFNN−AUM), an innovative distributed adaptive control scheme using sliding mode techniques is proposed to guarantee that the convergence of state errors to a predefined region and accomplish the vehicle platoon’s control objectives. Comparative numerical results confirm the effectiveness and superiority of the developed control strategy over existing method.