This paper describes an autonomous driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consisted of four parts: speed controller for following the desired speed, trajectory tracking controller to track the desired trajectory, longitudinal tire force distribution algorithm which determines the optimal desired longitudinal tire force and wheel torque controller which determines the wheel torque command at each wheel to keep the slip ratio below the limit value as well as to track the desired tire force. The longitudinal and vertical tire force estimators were designed for optimal tire force distribution and wheel slip control. The dynamic model of the RVAS is validated using vehicle test data. Simulation and vehicle tests were conducted in order to evaluate the proposed driving control algorithm. Based on the simulation and test results, the proposed driving controller was shown to produces satisfactory trajectory tracking performance.
This paper describes a drive controller designed to improve the lateral vehicle stability and maneuverability of a 6-wheel drive / 6-wheel steering (6WD/6WS) vehicle. The drive controller consists of upper and lower level controllers. The upper level controller is based on sliding control theory and determines both front and middle steering angle, additional net yaw moment, and longitudinal net force according to the reference velocity and steering angle of a manual drive, remotely controlled, autonomous controller. The lower level controller takes the desired longitudinal net force, yaw moment, and tire force information as inputs and determines the additional front steering angle and distributed longitudinal tire force on each wheel. This controller is based on optimal distribution control and takes into consideration the friction circle related to the vertical tire force and friction coefficient acting on the road and tire. Distributed longitudinal/lateral tire forces are determined as proportion to the size of the friction circle according to changes in driving conditions. The response of the 6WD/6WS vehicle implemented with this drive controller has been evaluated via computer simulations conducted using the Matlab/ Simulink dynamic model. Computer simulations of an open loop under turning conditions and a closed-loop driver model subjected to double lane change have been conducted to demonstrate the improved performance of the proposed drive controller over that of a conventional DYC. NOMENCLATURE F xi : longitudinal tire force [N] F zi : vertical(normal) tire force [N] δ : manual steering wheel angle [rad] F xi_des : desired longitudinal tire force [N] ∆M z : required yaw moment [Nm] y : lateral position [m] γ : yaw rate [rad/s] Vx : longitudinal vehicle velocity [m/s] ∆δ f : additional front steering angle [rad] ∆F yi : additional lateral tire force [N] T i_c : torque command (in-wheel-motor) [Nm] γ des : desired yaw rate [rad/s] l f,m,r : wheel base (front, middle and rear) [m] γ ss : steady-state yaw rate [rad/s] m : vehicle mass [kg] g : acceleration of gravity [m/s^2] c yi : lateral weighting factor J ω : wheel moment of inertia r i : wheel radius [m] : estimated slip ratio C x : longitudinal tire force stiffness [N] x : longitudinal position [m] ϕ : heading angle [rad] β : side slip angle [rad] µ : road friction coefficient ∆F xi : additional longitudinal tire force [N] δ i_c
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.