Robust Approximate Constraint‐Following Control for Autonomous Vehicle Platoon Systems

Abstract

We consider an autonomous vehicle platoon system consisting of N + 1 vehicles in the presence of modeling uncertainty. The uncertainty may be due to parameter variations, aerodynamics, external disturbances, etc., which is nonlinear and time-varying. Subject to the collision avoidance consideration, the original state is one-sided restricted. To resolve this restriction, we propose a state transformation to convert the bounded state into a globally unbounded state. Furthermore, motivated by the properties of artificial swarm systems, we incorporate the swarm system performance into the platoon system by treating it as a d'Alembert's constraint. By the Udwadia and Kalaba's approach, we obtain the analytic (closed-form) expression of the constraint force. Based on this, a class of robust controls for each vehicle (except the leading vehicle) is proposed to drive the platoon system to follow the ideal swarm model. Four major system performances are accomplished: (i) compact vehicle formation, (ii) collision avoidance, (iii) stable platoon system formation, (iv) global behavior.

Utilising bidirectional inequality constraints in optimal robust control for heterogeneous vehicular platoons

“…The distributed approaches can be roughly divided into three categories: (i) optimisation-based control [11,[16][17][18], (ii) linear feedback and feedforward control [19][20][21][22] and (iii) non-linear control [12,[23][24][25]. The optimisation-based method (e.g.…”

“…Therefore, attention has been paid to non-linear control methods. For instance, Zhao et al [23] formulated the platoon as an artificial swarm system and proposed a constraint-following controller by treating the well-designed swarm system performances as the constraints for the platoon. Yan et al designed a neural slidingmode controller for a vehicular platoon (may be heterogeneous) with unknown driving resistance.…”

Adaptive neural network output-feedback control of multiple Ackermann steering vehicles formation including motor dynamics with a guaranteed performance

“…However, all the previous works in the literature 1–17 address the different aspects of the formation control problem of differentially driven wheeled mobile robots 1–17 which are not applicable to automobiles and car-like robots. In spite of various theoretical results on the formation and cooperative control of multiple mobile robots, available papers in the literature 1–26 have at least one of the following shortfalls: (1) almost all the papers in the literature focus on the coordinated control of multiple differential-drive robots. Except a few elementary results in previous studies, 18–21 the literature is still sparse on the control of multiple Ackermann steering robots formation which is the main topic of this paper; (2) the cooperati...…”

“…In spite of various theoretical results on the formation and cooperative control of multiple mobile robots, available papers in the literature 1–26 have at least one of the following shortfalls: (1) almost all the papers in the literature focus on the coordinated control of multiple differential-drive robots. Except a few elementary results in previous studies, 18–21 the literature is still sparse on the control of multiple Ackermann steering robots formation which is the main topic of this paper; (2) the cooperative control of platoon systems and car-following algorithms 22–26 only consider a single-dimensional control of vehicles’ motions and their results are not applicable to the planar motion of multiple vehicles; (3) most of the previous controllers require the linear and angular velocities or even acceleration measurements for the practical implementation of the controller; (4) most of the proposed observers rely on the robot dynamics to estimate the velocity; (5) most of the controllers could not guarantee the transient and steady-state performance specifications and they may be subjected to unwanted singularities; and (6) the other formation controllers provide torque signals and they ignore the motors dynamic model and its uncertainties. Based on a strong motivation inspired from the above discussion, and from the above literature review, main contributions and novelties of this work are expressed below 1…”

Robust control of connected vehicles via V2V communication

“…There are plenty of recent research on subjects such as autonomous vehicles, vehicle platooning and enhancing the safety of vehicles. In 2018 Xiaomin Zhao et al used a robust controller for autonomous vehicle platoon . Again in 2018 Shi‐Ming Yu et al used MPC for vehicle platoons, considering sensors with limited measurement range and actuator with time delay .…”