An improved sliding mode control (SMC) approach for enhancement of communication delay in vehicle platoon system

Abstract

Vehicle platoon systems are widely recognized as key enablers to address mass-transport. Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) are two technologies that drive platooning. The inter-vehicle spacing and collaboration velocity in the platoon are important parameters that must be controlled. A new mass-transport system called the Tracked Electric Vehicles (TEV) has been proposed which has reduced the inter-vehicular spacing to only a quarter of the regular car length. This enables mass transport at uniform speed for cars with speed of 200km/h. However, conventional radar based adaptive cruise control (ACC) system fail to control each vehicle in these scenarios. Lately, sliding mode control (SMC) has been applied to control platoons with communication technology but with low speed and without delay. This paper proposes a novel SMC design for TEV using global dynamic information with the communication delay. Also, graph theory has been employed to investigate different V2V communication topology structures. To address issues of node vehicle stability and string stability, Lyapunov candidate function is chosen and developed. Additionally, this paper uses first-order vehicle models with different acceleration/deceleration parameters for simulation validations under communication delay. The results show that this SMC has a significant tolerance ability and meets the design requirements of TEV.

Cooperative predictive control for arbitrarily mixed vehicle platoons with guaranteed global optimality

“…Another hot research topic is the control for mixed vehicle platoons. Common methods include PID control [15], sliding mode control [16], neural network control [17], and etc. The main limitation of these control methods is that they are unable to deal with state and control constraints.…”

An adaptive fuzzy control technique for a high‐speed vehicular platoon experiencing communication delays

“…Moreover, some researchers have examined dynamic network consistency while examining the vehicle platoon system, addressing the problems of nodes, edges, and network topology [15]. Furthermore, other researchers have investigated the platoon system through four basic modules [16,17], including the four-element vehicle platoon model based on the algebraic graph theory, feedback linearization, and matrix analysis.…”

“…For instance, model predictive control (MPC) has been shown to be an effective approach to the presence of constraints in non-linear systems [22]. Additionally, adaptive control techniques, such as sliding mode control (SMC) [17] and backstepping control [23], have also been applied to non-linear systems with some success. However, fuzzy logic shows more potential to improve the stability and robustness of the vehicle platoon, some researchers attempt to integrate the fuzzy method with other algorithms.…”