Model predictive control for a basic adaptive cruise control

A model predictive control (MPC) approach is implemented on a basic Adaptive Cruise Control (ACC) system. A vehicle is moving with a constant velocity and a following vehicle approaches the preceding vehicle and should maintain the same velocity. Using a MPC controller, the required stability with the specified input constraints and the target velocity for a constant preceding vehicle velocity was achieved. Linear-Quadratic Regulator (LQR) controller was applied in this work for comparison purpose. An MPC controller would hence be preferred in this paper. With the implementation of state constraints as well, the controller would be able to achieve the required stability for a variety of cases, especially where the distance between the vehicles is large. This destabilizes the plant and the controller is unable to achieve the stability. Hence, in this case where the difference in distance between the host and preceding vehicle is low, the controller performs satisfactorily. The controller is also tested for different prediction horizons and performs well at a horizon of N=20\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N = 20$$\end{document}, beyond which no significant improvement is observed. Through simulations in MATLAB, it was shown that the proposed MPC strategy was able to maintain a vehicle in designated constraints, and satisfactory results were implemented fast due to the simplicity of the proposed model.