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The steering system plays a critical role in the vehicle's handling and directly influences its lateral dynamics. Faults or abnormal behavior in this system can affect performance, cause vehicle instability, and even lead to accidents. Therefore, considering these potential events is essential for designing robust controllers for autonomous vehicles. For this reason, in this work, a fault-tolerant path-tracking Static Output-Feedback controller is designed to handle steering actuator faults in autonomous vehicle steering systems. The controller adopts a Linear Parameter Varying approach to effectively handle nonlinearities associated with varying vehicle speeds and tire behavior. Furthermore, it only uses information from sensors, avoiding estimation stages. This controller can operate in two modes: a no-fault mode where only the steering is controlled to follow the reference path and a fault mode where the controller manages both the steering and torque vectoring. In fault mode, torque vectoring compensates for faults in the steering actuator. The design of the controller is completed considering gain faults in the steering system. The simulation results show that the proposed controller successfully maintains vehicle stability and significantly reduces tracking errors during high-risk maneuvers, achieving reductions of up to 50.65% in lateral error and 47.26% in heading error under worst-case fault scenarios. [ABSTRACT FROM AUTHOR]

This paper proposes a novel design method for a magnetorheological (MR) damper-based semi-active suspension system. An improved MR damper model that accurately describes the hysteretic nature and effect of the applied current is presented. Given the unfeasibility of installing sensors for all vehicle states, an MR damper current controller that only considers the suspension deflection and deflection rate is proposed. A linear matrix inequality problem is formulated to design the current controller, with the objective of enhancing ride safety and comfort while guaranteeing vehicle stability and robustness against any road disturbance. A series of experiments demonstrates the enhanced performance of the proposed MR damper model, which exhibits greater accuracy than other state-of-the-art damper models, such as Bingham or bi-viscous. An evaluation of the vehicle behavior under two simulated road scenarios has been conducted to demonstrate the performance of the proposed output feedback MR damper-based semi-active suspension system. [ABSTRACT FROM AUTHOR]

An heterogeneous vehicle platoon controller for autonomous vehicles is proposed in this paper. The traction force of each vehicle is controlled according to the state of the predecessor vehicle, which can be known by LiDAR/RADAR, and the state of the leader vehicle, which is received by vehicle-to-vehicle (V2V) communication. Platoon string stability is evaluated under Lyapunov and H∞ conditions. An iterative procedure is proposed in order to deal with the non-convexity of the static output feedback control design problem. Simulation results demonstrate that the proposed heterogeneous vehicle platoon controller achieves a good overall performance without compromising the safety of any vehicle. The separation between each follower and its predecessor is kept in appropriate ranges, always close to the desired reference. Furthermore, the transient errors are not amplificated when propagated downstream the platoon, therefore string stability is assured. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant integration of advanced technology into the automotive industry, aimed primarily at enhancing safety and ride comfort. While a notable proportion of these driver-assist systems focuses on skid prevention, insufficient attention has been paid to addressing other crucial scenarios, such as rollovers. The accurate estimation of slip and roll angles plays a vital role in ensuring vehicle control and safety, making these parameters essential, especially with the rise of modern technologies that incorporate networked communication and distributed computing. Furthermore, there exists a lag in the transmission of information between the various vehicle systems, including sensors, actuators, and controllers. This paper outlines the design of an IoT architecture that accurately estimates the sideslip angle and roll angle of a vehicle, while addressing network transmission delays with a networked control system and an event-triggered communication scheme. Experimental results are presented to validate the performance of the IoT architecture proposed. The event-triggered scheme of the IoT solution is used to decrease data transmission and prevent network overload. [ABSTRACT FROM AUTHOR]

Tire slip control is one of the most critical topics in vehicle dynamics control, being the basis of systems such the Anti-lock Braking System (ABS), Traction Control System (TCS) or Electronic Stability Program (ESP). The highly nonlinear behavior of tire–road contact makes it challenging to design robust controllers able to find a dynamic stable solution in different working conditions. Furthermore, road conditions greatly affect the braking performance of vehicles, being lower on slippery roads than on roads with a high tire friction coefficient. For this reason, by knowing the value of this coefficient, it is possible to change the slip ratio tracking reference of the tires in order to obtain the optimal braking performance. In this paper, an H ∞ controller is proposed to deal with the tire slip control problem and maximize the braking forces depending on the road condition. Simulations are carried out in the vehicular dynamics simulator software CarSim. The proposed controller is able to make the tire slip follow a given reference based on the friction coefficient for the different tested road conditions, resulting in a small reference error and good transient response. [ABSTRACT FROM AUTHOR]