Adaptive Throttle Control for Speed Tracking

SUMMARY

Electronic throttle control is an important part of every advanced vehicle control system. In this paper we design an adaptive control scheme for electronic throttle that achieves good tracking of arbitrary constant speed commands in the presence of unknown disturbances. The design is based on a simplified linear vehicle model which is derived from a validated nonlinear one. The designed control scheme is simulated using the validated full order nonlinear vehicle model and tested on an actual vehicle. The simulation and vehicle test results are included in this paper to show the performance of the controller. Due to the learning capability of the adaptive control scheme, changes in the vehicle dynamics do not affect the performance of the controller in any significant manner.     

TECHNICAL NOTE

This paper presents an advanced control method in application of automotive systems. An adaptive fuzzy logic controller based on self tuning control methodology has been implemented and used to control the vehicle velocity. Fuzzy rules and reasoning are utilized on-line to determine the throttle angle, spark advance and braking force. Simulated results, as presented in this paper show the adaptive fuzzy control is well suited for vehicle speed control with a nonlinear dynamic behaviour of the engine.     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

车速控制系统自适应油门控制器设计

在分析非线性车辆纵向动力学模型及简化模型基础上，采用一种简化非线件模型设计自适应油门控制器，并应用李亚谱诺夫理论证明了传动系统存在动态过程时控制系统的稳定性。通过对基于简化线性和非线性模燃的自适应控制器的仿真研究，结果表明后者具有更好的收敛性。试验结果也进一步表明，基于非线性模型的自适应控制器可以通过自适应调节减小参数不确定造成的干扰，当传动系统存在动态过程时可以保证车速跟踪误差有界。     

无人驾驶机器人车辆非线性模糊滑模车速控制

为了实现不同行驶工况下车速的精确、稳定控制,提出一种基于非线性干扰观测器的无人驾驶机器人车辆模糊滑模车速控制方法。考虑模型不确定性和外部干扰对车速控制的影响,建立车辆纵向动力学模型。通过分析无人驾驶机器人油门机械腿、制动机械腿的结构、机械腿操纵自动挡车辆踏板的运动,建立油门机械腿和制动机械腿的运动学模型。在此基础上,分别设计油门/制动切换控制器、油门模糊滑模控制器以及制动模糊滑模控制器,并进行控制系统的稳定性分析。油门/制动切换控制器以目标车速的导数为输入来进行油门与制动之间的切换控制。油门模糊滑模控制器和制动模糊滑模控制器以当前车速以及车速误差为输入,分别以油门机械腿直线电机位移和制动机械腿直线电机位移为输出来实现对油门与制动的控制。模糊滑模控制器中,为了减少控制抖振,滑模控制的反馈增益系数由模糊逻辑进行在线调节。模糊滑模控制器中的非线性干扰观测器用于估计和补偿无人驾驶机器人车辆的模型不确定性与外部干扰。仿真及试验结果对比分析表明：本文方法能够精确地估计和补偿无人驾驶机器人车辆的模型不确定性和外部干扰,避免了油门控制与制动控制之间的频繁切换,并实现了精确稳定的车速控制。     

基于预测恒定车头时距策略的自适应巡航控制研究

为了进一步提高车辆跟车过程中的跟踪性、安全性、舒适性和燃油经济性，针对已有间距策略表现过于保守或反应过于激烈等不足之处，提出了一种预测恒定车头时距策略。该策略考虑了相对加速度，建立了一种预测型期望车间距模型，进而应用于模型预测控制的多目标自适应巡航控制系统中，能进一步提高模型预测控制对多个控制目标的综合协调能力。搭建上层控制器、下层PID控制器、油门制动切换、逆纵向动力学模型。在多工况下仿真，通过建立性能评判指标对多目标进行量化分析。结果表明，所提出的间距策略在保证安全性的前提下，提升了自适应巡航控制系统的综合性能。在不同驾驶风格的车头时距下，跟踪性、舒适性和燃油经济性均有良好表现。     

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.     

Design and Evaluation of Robust Cooperative Adaptive Cruise Control Systems in Parameter Space

This paper is on the design of cooperative adaptive cruise control systems for automated driving of platoons of vehicles in the longitudinal direction. Longitudinal models of vehicles with simple dynamics, an uncertain first order time constant and vehicle to vehicle communication with a communication delay are used in the vehicle modeling. A robust parameter space approach is developed and applied to the design of the cooperative adaptive cruise control system. D-stability is chosen as the robust performance goal and the feedback PD controller is designed in controller parameter space to achieve this D-stability goal for a range of possible longitudinal dynamics time constants and different values of time gap. Preceding vehicle acceleration is sent to the ego vehicle using vehicle to vehicle communication and a feedforward controller is used in this inter-vehicle loop to improve performance. Simulation results of an eight vehicle platoon of heterogeneous vehicles are presented and evaluated to demonstrate the efficiency of the proposed design method. Also, the proposed method is compared with a benchmark controller and the feedback only controller. Time gap regulation and string stability are used to assess performance and the effect of the vehicle to vehicle communication frequency on control system performance is also investigated.     

Active Roll Control of Articulated Vehicles

This paper describes an investigation into active roll control of articulated vehicles. The objective is to minimise lateral load transfer using anti-roll bars incorporating low bandwidth hydraulic actuators. Results from handling tests performed on an articulated vehicle are used to validate a nonlinear yaw/roll model of the vehicle. The methodology used to design lateral acceleration controllers for vehicles equipped with active anti-roll bars is developed using a simplified linear articulated vehicle model. The hardware limitations and power consumption requirements of the active elements are studied. The controller is then implemented in the validated articulated vehicle model to evaluate the performance of an articulated lorry with active anti-roll bars. The simulation results demonstrate the possibility of a significant improvement in transient roll performance of the vehicle, using a relatively low power system (10 kW), with low bandwidth actuators (5 Hz).     

Fuzzy adaptive sliding mode controller for an air spring active suspension

A fuzzy adaptive sliding mode controller for an air spring active suspension system is developed. Due to nonlinearity, preload-dependent spring force and parameter uncertainty in the air spring, it is difficult to control the suspension system. To achieve the desired performance, a fuzzy adaptive sliding mode controller (FASMC) is designed to improve the passenger comfort and the manipulability of the vehicle. The fuzzy adaptive system handles the nonlinearity and uncertainty of the air suspension. A normal linear suspension model with an optimal state feedback control is designed as the reference model. The simulation results show that this control scheme more effectively and robustly isolates vibrations of the vehicle body than the conventional sliding mode controller (CSMC).     

Cooperative lateral vehicle control for autonomous valet parking

This paper presents a lateral vehicle control algorithm for autonomous valet parking (AVP). Under the assumption that the position and heading angle are provided via vehicle-to-infrastructure (V2I) communication, the lateral controller aims to conduct two different driving maneuvers, i.e., forward driving and backward parking, and to control various types of vehicles in a unified approach. Therefore, it is necessary for the lateral controller to be robust enough to track the desired trajectories for different driving maneuvers, as well as to compensate for the uncertainty caused by the need to consider various vehicle types. With the assumption of operating conditions such as a low speed and small slip angle, a nonlinear kinematic model with kinematic constraints is used for the design of the lateral control. Based on this nonlinear model, a nonlinear control technique called dynamic surface control (DSC) is applied to design the lateral controller, and its stability is analyzed in the framework of linear differential inclusion. Finally, the proposed lateral control algorithm is validated through vehicle simulations and field tests.     

Design of a feedback-feedforward steering controller for accurate path tracking and stability at the limits of handling

This paper presents a feedback-feedforward steering controller that simultaneously maintains vehicle stability at the limits of handling while minimising lateral path tracking deviation. The design begins by considering the performance of a baseline controller with a lookahead feedback scheme and a feedforward algorithm based on a nonlinear vehicle handling diagram. While this initial design exhibits desirable stability properties at the limits of handling, the steady-state path deviation increases significantly at highway speeds. Results from both linear and nonlinear analyses indicate that lateral path tracking deviations are minimised when vehicle sideslip is held tangent to the desired path at all times. Analytical results show that directly incorporating this sideslip tangency condition into the steering feedback dramatically improves lateral path tracking, but at the expense of poor closed-loop stability margins. However, incorporating the desired sideslip behaviour into the feedforward loop creates a robust steering controller capable of accurate path tracking and oversteer correction at the physical limits of tyre friction. Experimental data collected from an Audi TTS test vehicle driving at the handling limits on a full length race circuit demonstrates the improved performance of the final controller design.     

Development of a new traction control system for vehicles with automatic transmissions

A traction control system (TCS) is used to improve the acceleration performance on slippery roads by preventing excessive wheel slip. In this paper, a new traction control system using the integrated control of gear shifting and throttle actuation is developed for vehicles with automatic transmissions. In the design of the slip controller, by means of a differential manifold transformation, a slip control system with nonlinearities and uncertainties is transformed into a linear system, and a sliding mode controller is applied for the purpose of increasing the robustness of the system. Next, to achieve the required driving torque, the optimal throttle and gear position, maps are constructed based on dynamic programming. The simulation results indicate that the present traction control system can improve the acceleration performance of an automatic transmission vehicle for various types of road conditions.     

Second-order sliding mode controller with model reference adaptation for automatic train operation

In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.     

Nonlinear robust control of integrated vehicle dynamics

A new methodology to design the vehicle GCC (global chassis control) nonlinear controller is developed in this paper. Firstly, to handle the nonlinear coupling between sprung and unsprung masses, the vehicle is treated as a mechanical system of two-rigid-bodies which has 6 DOF (degree of freedom), including longitudinal, lateral, yaw, vertical, roll and pitch dynamics. The system equation is built in the yaw frame based on Lagrange's method, and it has been proved that the derived system remains the important physical properties of the general mechanical system. Then the GCC design problem is formulated as the trajectory tracking problem for a cascade system, with a Lagrange's system interconnecting with a linear system. The nonlinear robust control design problem of this cascade interconnected system is divided into two H _∞ control problems with respect to the two sub-systems. The parameter uncertainties in the system are tackled by adaptive theory, while the external uncertainties and disturbances are dealt with the H _∞ control theory. And the passivity of the mechanical system is applied to construct the solution of nonlinear H _∞ control problem. Finally, the effectiveness of the proposed controller is validated by simulation results even during the emergency manoeuvre.     

Application of Analytic Hierarchy Process to Stochastic Robustness Synthesis of Integrated Vehicle Controllers

This paper deals with the robust design procedure of integrated vehicle dynamics controller based on Stochastic Robustness Synthesis with use of a rational decision making process of the controller parameters. The basic control structure that integrates four-wheel steering and four-wheel torque control is determined using a nonlinear predictive control theory. The Analytic Hierarchy Process, a basic approach to decision making, is applied to determine the weight coefficients of robustness evaluation function of the controller. The desired vehicle dynamic performance is described as four-layer hierarchy structure and the design priority is determined with respect to several design criteria. The proposed design process produced a control system with excellent stability and performance robustness to vehicle parameter variations.     

Slip regulation for anti-lock braking systems using multiple surface sliding controller combined with inertial delay control

In this paper, a multiple surface sliding controller is designed for an anti-lock braking system to maintain the slip ratio at a desired level. Various types of uncertainties coming from unknown road surface conditions, the variations in normal force and the mass of the vehicle are estimated using an uncertainty estimation technique called the inertial delay control and then the estimate is used in the design of the multiple surface sliding controller. The proposed scheme does not require the bounds of uncertainties. The ultimate boundedness of the overall system is proved. The proposed scheme is validated by simulation under various scenarios of road friction, road gradient and vehicle loading followed by experimentation on a laboratory anti-lock braking set-up for different friction conditions.     

基于Simulink的电子节气门控制策略开发

针对车用电子节气门的非线性特征,提出了带复位弹簧和摩擦补偿器的PID控制策略.先分析电子节气门的物理特性,根据此特性使用Simulink建立了物理模型和控制策略模型,并进行模型仿真和参数初步整定,然后使用Simulink的Embedded-Coder工具将控制策略模型自动生成C代码,集成到自主开发的ECU中,最后在硬件...     

A Comparison of Alternative Intervention Strategies for Unintended Roadway Departure (URD) Control

This paper investigates the use of several different inputs for the control of a vehicle, in the context of URD. In this investigation, the goal of the URD controller is to provide an intervention in the event of the vehicle leaving the road. The types of inputs that will be considered are (i) Four Wheel Steering, (ii) Front Wheel Steering, (iii) Four Wheel Brake Steering, (iv) Front Wheel Brake Steering, and (v) Rear Wheel Brake Steering. The controller design is an LQ controller based on the simplified dynamics of a 2 degree of freedom bicycle model. However, the analysis of the different strategies are performed on a 7 degree-of-freedom nonlinear vehicle model. The key contribution of this paper is the quantitative evaluation of the relative efficiencies of each of these input strategies being examined. Unlike most control schemes, the performance measure to be used will not be the output tracking error of the system. Instead, the metric of performance is the ratio of peak tire force used versus available tire force or, in other words, the actuator response relative to the maximum available actuator capability.     

Application of Analytic Hierarchy Process to Stochastic Robustness Synthesis of Integrated Vehicle Controllers

This paper deals with the robust design procedure of integrated vehicle dynamics controller based on Stochastic Robustness Synthesis with use of a rational decision making process of the controller parameters. The basic control structure that integrates four-wheel steering and four-wheel torque control is determined using a nonlinear predictive control theory. The Analytic Hierarchy Process, a basic approach to decision making, is applied to determine the weight coefficients of robustness evaluation function of the controller. The desired vehicle dynamic performance is described as four-layer hierarchy structure and the design priority is determined with respect to several design criteria. The proposed design process produced a control system with excellent stability and performance robustness to vehicle parameter variations.