Stability control of 4WS vehicles using robust IMC techniques

A robust nonparametric approach to vehicle stability control by means of a four-wheel steer by wire system is introduced. Both yaw rate and sideslip angle feedbacks are used in order to effectively take into account safety as well as handling performances. Reference courses for yaw rate and sideslip angle are computed on the basis of the vehicle speed and the handwheel angle imposed by the driver. An output multiplicative model set is used to describe the uncertainty arising from a wide range of vehicle operating situations. The effects of saturation of the control variables (i.e. front and rear steering angles) are taken into account by adopting enhanced internal model control methodologies in the design of the feedback controller. Actuator dynamics are considered in the controller design. Improvements on understeer characteristics, stability in demanding conditions such as turning on low friction surfaces, damping properties in impulsive manoeuvres, and improved handling in closed loop (i.e. with driver feedback) manoeuvres are shown through extensive simulation results performed on an accurate 14 degrees of freedom nonlinear model, which proved to give good modelling results as compared with collected experimental data.     

Model predictive control with constraints for a nonlinear adaptive cruise control vehicle model in transition manoeuvres

A vehicle following control law, based on the model predictive control method, to perform transition manoeuvres (TMs) for a nonlinear adaptive cruise control (ACC) vehicle is presented in this paper. The TM controller ultimately establishes a steady-state following distance behind a preceding vehicle to avoid collision, keeping account of acceleration limits, safe distance, and state constraints. The vehicle dynamics model is for continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. The ACC vehicle can execute the TM successfully and achieves a steady-state in the presence of complex dynamics within the constraint boundaries.     

Comparing rear wheel steering and rear active differential approaches to vehicle yaw control

A comparison between two different approaches to vehicle stability control is carried out, employing a robust non-parametric technique in the controller design. In particular, an enhanced internal model control strategy, together with a feedforward action and a suitably generated reference map, is employed for the control of a vehicle equipped either with a rear wheel steering (RWS) system or with a rear active differential (RAD) device. The uncertainty arising from the wide range of operating conditions is described by an additive model set employed in the controller design. Extensive steady state and transient tests simulated with an accurate 14 degrees of freedom nonlinear model of the considered vehicle show that both systems are able to improve handling and safety in normal driving conditions. RAD devices can make the vehicle reach higher lateral acceleration values but they achieve only slight stability improvements against oversteer. On the other hand, 4WS systems can greatly improve both vehicle safety and manoeuvrability in all driving situations, making this device an interesting and powerful stability system.     

Vehicle dynamic stability improvements through gain-scheduled steering and braking control

This paper is concerned with the synthesis of a robust gain-scheduled ?_∞ MIMO vehicle dynamic stability controller (VDSC) involving both steering and rear braking actuators. This VDSC aims at improving automotive vehicle yaw stability and lateral performances. The aim of this work is to provide a methodology to synthesise such a controller while taking into account the braking actuator limitations and use the steering actuator only if it is necessary. These objectives are treated in an original way by the synthesis of a parameter-dependent controller built in the LPV framework and by the solution of an LMI problem. The proposed solution is coupled with a local ABS strategy to guarantee slip stability and make the solution complete. Nonlinear time and frequency domain simulations on a complex full vehicle model (which has been validated on a real car), subject to critical driving situations, show the efficiency and robustness of the proposed solution.     

Optimal roll control of an articulated vehicle: theory and model validation

This paper investigates optimal roll control of an experimental articulated vehicle. The test vehicle and the mathematical model used to design the control strategies are presented. The vehicle model is validated against experimental data from the test vehicle in passive configuration. The initial controller design, performed by Sampson (Sampson, D.J.M. and Cebon, D., 2003a, Achievable roll stability of heavy road vehicles. Proc. Instn. Mech. Engrs, Part D, J. Automobile Engineering, 217(4), 269–287), is reviewed and adapted for the experimental vehicle. The effect of not controlling all the axles on the vehicle is investigated and a variable vehicle speed controller is designed by interpolating between constant speed controllers. Substantial reduction in normalized load transfer is achieved for a range of manoeuvres, both in steady-state and transient conditions.     

Optimal roll control of an articulated vehicle: theory and model validation

This paper investigates optimal roll control of an experimental articulated vehicle. The test vehicle and the mathematical model used to design the control strategies are presented. The vehicle model is validated against experimental data from the test vehicle in passive configuration. The initial controller design, performed by Sampson (Sampson, D.J.M. and Cebon, D., 2003a, Achievable roll stability of heavy road vehicles. Proc. Instn. Mech. Engrs, Part D, J. Automobile Engineering, 217(4), 269-287), is reviewed and adapted for the experimental vehicle. The effect of not controlling all the axles on the vehicle is investigated and a variable vehicle speed controller is designed by interpolating between constant speed controllers. Substantial reduction in normalized load transfer is achieved for a range of manoeuvres, both in steady-state and transient conditions.     

Vehicle dynamic control of a passenger car applying flexible body model

Modern software tools have enhanced modelling, analysis and simulation capabilities pertaining to control of dynamic systems. In this regard, in this paper a full vehicle model with flexible body is exposed by using MSC. ADAMS and MSC. NASTRAN. Indeed, one of the most significant vehicle dynamic controls is directional stability control. In this case, the vehicle dynamic control system (VDC) is used to improving the vehicle lateral and yaw motions in critical manoeuvres. In this paper, for design the VDC system, an optimal control strategy has been used for tracking the intended path with optimal energy. For better performance of VDC system, an anti-lock brake system (ABS) is designed as a lower layer of the control system for maintaining the tyre longitudinal slip in proper value. The performances of the controller on rigid and flexible models are illustrated, and the results show the differences between the control efforts for these models, which are related to the differences of dynamic behaviours of rigid and flexible vehicle dynamic models.     

Real-time weighted multi-objective model predictive controller for adaptive cruise control systems

In this paper, a novel spacing control law is developed for vehicles with adaptive cruise control (ACC) systems to perform spacing control mode. Rather than establishing a steady-state following distance behind a newly encountered vehicle to avoid collision, the proposed spacing control law based on model predictive control (MPC) further considers fuel economy and ride comfort. Firstly, a hierarchical control architecture is utilized in which a lower controller compensates for nonlinear longitudinal vehicle dynamics and enables to track the desired acceleration. The upper controller based on the proposed spacing control law is designed to compute the desired acceleration to maintain the control objectives. Moreover, the control objectives are then formulated into the model predictive control problem using acceleration and jerk limits as constrains. Furthermore, due to the complex driving conditions during in the transitional state, the traditional model predictive control algorithm with constant weight matrix cannot meet the requirement of improvement in the fuel economy and ride comfort. Therefore, a real-time weight tuning strategy is proposed to solve time-varying multi-objective control problems, where the weight of each objective can be adjusted with respect to different operating conditions. In addition, simulation results demonstrate that the ACC system with the proposed real-time weighted MPC (RW-MPC) can provide better performance than that using constant weight MPC (CW-MPC) in terms of fuel economy and ride comfort.     

A tube-based robust nonlinear predictive control approach to semiautonomous ground vehicles

This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents a systematic way of enforcing robustness during the MPC design stage. A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre line. A force-input nonlinear bicycle vehicle model is developed and used in the RNMPC control design. A robust invariant set is used in the RNMPC design to guarantee that state and input constraints are satisfied in the presence of disturbances and model error. Simulations and experiments on a vehicle show the effectiveness of the proposed framework.     

Linear matrix inequality based control of vehicle active suspension system

Linear matrix inequality (LMI) methods, novel techniques in solving optimisation problems, were introduced as a unified approach for vehicle's active suspension system controller design. LMI methods were used to provide improved and computationally efficient controller design techniques. The active suspension problem was formulated as a standard convex optimisation problem involving LMI constraints that can be solved efficiently using recently developed interior point optimisation methods. An LMI based controller for a vehicle system was developed. The controller design process involved setting up an optimisation problem with matrix inequality constraints. These LMI constraints were derived for a vehicle suspension system. The resulting LMI controller was then tested on a quarter-car model using computer simulations. The LMI controller results were compared with an optimal PID controller design solution. The LMI controller was further tested by incorporating a nonlinear term in the vehicle's suspension model; the LMI's controller degraded response was enhanced by using gain-scheduling techniques. The LMI controller with gain-scheduling gave good results in spite of the unmodelled dynamics in the suspension system, which was triggered by large deflections due to off-road driving.     

基于模糊解耦控制的车辆转向制动系统研究

车辆转向系统和制动系统之间存在着很强的速度耦合关系,造成两个系统之间的性能相互影响,使得车辆在转向制动这一工况成了汽车最危险的工况之一。本文结合实际车辆参数建立转向系统的二自由度模型和制动系统的单车轮模型,针对车辆转向制动工况设计了模糊解耦控制器,实现了车辆的转向与制动同时控制。经验证含有模糊解耦控制的车辆转向制动系统具有很好的动态控制效果,并且有很强的鲁棒性和自适应性。     

Inverse neuro-fuzzy MR damper model and its application in vibration control of vehicle suspension system

In this paper, a magneto-rheological (MR) damper-based semi-active controller for vehicle suspension is developed. This system consists of a linear quadratic Gauss (LQG) controller as the system controller and an adaptive neuro-fuzzy inference system (ANFIS) inverse model as the damper controller. First, a modified Bouc–Wen model is proposed to characterise the forward dynamic characteristics of the MR damper based on the experimental data. Then, an inverse MR damper model is built using ANFIS technique to determine the input current so as to gain the desired damping force. Finally, a quarter-car suspension model together with the MR damper is set up, and a semi-active controller composed of the LQG controller and the ANFIS inverse model is designed. Simulation results demonstrate that the desired force can be accurately tracked using the ANFIS technique and the semi-active controller can achieve competitive performance as that of active suspension.     

A combined-slip predictive control of vehicle stability with experimental verification

In this paper, a model predictive vehicle stability controller is designed based on a combined-slip LuGre tyre model. Variations in the lateral tyre forces due to changes in tyre slip ratios are considered in the prediction model of the controller. It is observed that the proposed combined-slip controller takes advantage of the more accurate tyre model and can adjust tyre slip ratios based on lateral forces of the front axle. This results in an interesting closed-loop response that challenges the notion of braking only the wheels on one side of the vehicle in differential braking. The performance of the proposed controller is evaluated in software simulations and is compared to a similar pure-slip controller. Furthermore, experimental tests are conducted on a rear-wheel drive electric Chevrolet Equinox equipped with differential brakes to evaluate the closed-loop response of the model predictive control controller.     

Optimal motion control for collision avoidance at Left Turn Across Path/Opposite Direction intersection scenarios using electric propulsion

Collision avoidance at intersections involving a host vehicle turning left across the path of an oncoming vehicle (Left Turn Across Path/Opposite Direction) have been studied in the past, but mostly using simplified interventions and rarely considering the possibility of crossing the intersection ahead of a bullet vehicle. Such a scenario where the driver preference is to avoid a collision by crossing the intersection ahead of a bullet vehicle is considered in this work. The optimal vehicle motion for collision avoidance in this scenario is determined analytically using a particle model within an optimal control framework. The optimal manoeuvres are then verified through numerical optimisations using a two-track vehicle model, where it was seen that the wheel forces followed the analytical global force angle result independently of the other wheels. A Modified Hamiltonian Algorithm controller for collision avoidance that uses the analytical optimal control solution is then implemented and tested in CarMaker simulations using a validated Volvo XC90 vehicle model. Simulation results showed that collision risk can be significantly reduced in this scenario using the proposed controller, and that more benefit can be expected in scenarios that require larger speed changes.     

Integration of vehicle yaw stabilisation and rollover prevention through nonlinear hierarchical control allocation

This work presents an approach to rollover prevention that takes advantage of the modular structure and optimisation properties of the control allocation paradigm. It eliminates the need for a stabilising roll controller by introducing rollover prevention as a constraint on the control allocation problem. The major advantage of this approach is the control authority margin that remains with a high-level controller even during interventions for rollover prevention. In this work, the high-level control is assigned to a yaw stabilising controller. It could be replaced by any other controller. The constraint for rollover prevention could be replaced by or extended to different control objectives. This work uses differential braking for actuation. The use of additional or different actuators is possible. The developed control algorithm is computationally efficient and suitable for low-cost automotive electronic control units. The predictive design of the rollover prevention constraint does not require any sensor equipment in addition to the yaw controller. The method is validated using an industrial multi-body vehicle simulation environment.     

Automatic guidance control of an articulated all-wheel-steered vehicle

This paper presents automatic guidance control of a single-articulated all-wheel-steered vehicle being developed by the Korea Railroad Research Institute. The vehicle has an independent drive motor on each wheel except for the front axle. The guidance controller is designed so that the vehicle follows the given reference path within permissible lateral deviations. We use a three-input/three-output linearised model derived from the nonlinear dynamic model of the vehicle. For the purpose of simplifying the controller and making it tunable, we consider a decentralised control configuration. We first design a second-order decoupling compensator for the two-input/two-output system that is strongly coupled and then design a first-order controller for each decoupled feedback loop by using the characteristic ratio assignment method. The simulation results for the nonlinear dynamic model indicate that the proposed control configuration successfully achieves the design objectives.     

Robust yaw stability control for electric vehicles based on active front steering control through a steer-by-wire system

A robust yaw stability control design based on active front steering control is proposed for in-wheel-motored electric vehicles with a Steer-by-Wire (SbW) system. The proposed control system consists of an inner-loop controller (referred to in this paper as the steering angle-disturbance observer (SA-DOB), which rejects an input steering disturbance by feeding a compensation steering angle) and an outer-loop tracking controller (i.e., a PI-type tracking controller) to achieve control performance and stability. Because the model uncertainties, which include unmodeled high frequency dynamics and parameter variations, occur in a wide range of driving situations, a robust control design method is applied to the control system to simultaneously guarantee robust stability and robust performance of the control system. The proposed control algorithm was implemented in a CaSim model, which was designed to describe actual in-wheel-motored electric vehicles. The control performances of the proposed yaw stability control system are verified through computer simulations and experimental results using an experimental electric vehicle.     

Predictive control of a vehicle trajectory using a coupled vector with vehicle velocity and sideslip angle

In this paper, a predictive algorithm for vehicle trajectory control using the vehicle velocity and sideslip angle is proposed. Since the driving state of a vehicle generates nonholonomic constraint equations, it is difficult to control the trajectory with a conventional control algorithm. Furthermore, control vectors such as vehicle velocity and sideslip angle are coupled together; hence, a separate control for each variable is not suitable. In this study, a coupled control vector that combines the velocity and sideslip angle is proposed for the predictive control of vehicle trajectory. Since the coupled control vector is derived from the status of the vehicle’s motion, it is easy to generate a feedback control vector for the predictive controller. The coupled vector cannot be directly used as input to the vehicle systems; therefore, the vehicle input vector should be calculated from the control vector using a nonlinear function. Since nonlinear functions are not inserted in the control loop, they are calculated by the controller. Therefore, this method does not require a linearization process in the control logic, which enhances the stability and accuracy of the predictive controller.     

Rule-based control of a semi-active suspension for minimal sprung mass acceleration: design and measurement

In this paper, a rule-based controller is developed for the control of a semi-active suspension to achieve minimal vertical acceleration. The rules are derived from the results obtained with a model predictive controller. It is shown that a rule-based controller can be derived that mimics the results of the model predictive controller and minimises vertical acceleration. Besides this, measurements on a test vehicle show that the developed rule-based controller achieves a real-world reduction of the vertical acceleration, which is in agreement with the simulations.