H∞ control of novel active steering integrated with electric power steering function

Based on the traditional active steering system, a novel active steering system integrated with electric power steering function was introduced, which can achieve the functions of both active steering and electric power steering. In view of the interference from road random signal and sensor noise in the novel active steering system, the H∞ control model of the novel active steering system was built. With satisfying steering feel, good robust performance and steering stability being the control objectives, the H∞ controller for the novel active front steering (AFS) system was designed. The simulation results show that the novel AFS system with H∞ control strategy can attenuate the road interference quickly, and there is no resonance peak in the bode diagram. It can make the driver obtain more useful information in the low frequency range, and attenuate the road interference better in the high frequency range, thus the driver can get more satisfying road feeling. Therefore, the designed H∞ controller can synthesize the advantages of both robust performance and robust stability, and has certain contribution to the design of novel AFS system.

Controller Design for Electric Power Steering System Using T-S Fuzzy Model Approach

Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno （T-S） fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation （PDC） structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality （LMI） problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.

Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters.Primarily,the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed,and in which the relationship between the look-ahead time and vehicle velocity is revealed.Then,in order to overcome the external disturbances,parametric uncertainties and time-varying features of vehicles,a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles,which includes an equivalent control law and an adaptive variable structure control law.In this novel automatic steering control system of vehicles,a neural network system is utilized for approximating the switching control gain of variable structure control law,and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time.The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory.Finally,the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

Precise Compound Control of Loading Force for Electric Load Simulator of Electric Power Steering Test Bench

Electric load simulator(ELS) systems are employed for electric power steering(EPS) test benches to load rack force by precise control. Precise ELS control is strongly influenced by nonlinear factors. When the steering motor rapidly rotates, extra force is directly superimposed on the original static loading error, which becomes one of the main sources of the final error. It is key to achieve ELS precise loading control for the entire EPS test bench. Therefore, a three-part compound control algorithm is proposed to improve the loading accuracy. First, a fuzzy proportional–integral plus feedforward controller with force feedback is presented. Second, a friction compensation algorithm is established to reduce the influence of friction. Then, the relationships between each quantity and the extra force are analyzed when the steering motor rapidly rotates, and a net torque feedforward compensation algorithm is proposed to eliminate the extra force. The compound control algorithm was verified through simulations and experiments. The results show that the tracking performance of the compound control algorithm satisfies the demands of engineering practice, and the extra force in the ELS system can be suppressed by the net torque corresponding to the actuator’s acceleration.

Research on Vehicle Control Technology Using Four-Wheel Independent Steering System

The enhancement of vehicle handling stability and maneuverability through active and independent rear wheels control is presented. Firstly, the configuration of four-wheel independent steering prototype vehide is introduced briefly. Then the concrete overall design of the electronic controllers of four wheel independent steering system （4WIS） is formulated in details. Under the control strategy of zero sideslip angle at mass center, the mathematical model of 4WIS is established to deduce the equations of separated rear wheel steering angles. According to these equations, simulation analysis for 4WIS vehicle performances is finished to show that 4WIS vehicle can improve the maneuverability greatly at low speed and increase the handling stability at high speed. Finally, the road test of 4WIS vehide has performed to verify the correctness of simulation and show that compared with the conventional four wheel steering （4WS） vehicle, the 4WIS vehicle not only improves the kinematical harmony but also decreases steering resistance and lighten abrasion of tires.

Autonomous Tracking Control for Four-Wheel Independent Steering Robot Based on Improved Pure Pursuit

Autonomous tracking control is one of the fundamental challenges in the field of robotic autonomous navigation,especially for future intelligent robots.In this paper,an improved pure pursuit control method is proposed for the path tracking control problem of a four-wheel independent steering robot.Based on the analysis of the four-wheel independent steering model,the kinematic model and the steering geometry model of the robot are established.Then the path tracking control is realized by considering the correlation between the look-ahead distance and the velocity,as well as the lateral error between the robot and the reference path.The experimental results demonstrate that the improved pure pursuit control method has the advantages of small steady-state error,fast response and strong robustness,which can effectively improve the accuracy of path tracking.

Electrical power assisted steering for EVs and HEVs

Electrical power assisted steering (EPAS) is one of the key components, especially for electrical vehicle. It has attracted much attention for their advantages with respect to improved fuel economy and has been widely adopted as automotive power-steering equipment in recent years. EPS (electrical power steering) controllers contain MCU (microprocessor control unit) to implement the complex control algorithms. EPS control strategy development is the core technology of the whole system. To achieve the better performance of driving, both mechanical structures and electrical structures are totally designed as a whole. Model-based development is recommended to software design. There are several trends about EPS’ future, such as high power EPS development, high voltage EPS development and steering-by-wire technology.

MPC-based Torque Distribution for Planar Motion of Four-wheel Independently Driven Electric Vehicles:Considering Motor Models and Iron Losses

The most critical obstacle for four-wheel independently driven electric vehicles(4WID-EVs)is the driving range.Being the actuators of 4WID-EVs,motors account for its major power consumption.In this sense,by properly distributing torques to minimize the power consumption,the driving range of 4WID-EV can be effectively improved.This paper proposes a model predictive control(MPC)-based torque distribution scheme,which minimizes the power consumption of 4WID-EVs while guaranteeing its tracking performance of planar motions.By incorporating the motor model considering iron losses,the optimal torque distribution can be achieved without an additional torque controller.Also,for this reason,the proposed control scheme is computationally efficient,since the power consumption term to be optimized,which is expressed as the product of the motor voltages and currents,is much simpler than that derived from the efficiency map.With reasonable simplification and linearization,the MPC problem is converted to a quadratic programming problem,which can be solved efficiently.The simulation results in MATLAB and CarSim co-simulation environments demonstrate that the proposed scheme effectively reduces power consumption with guaranteed tracking performance.

An Integrated Control Framework for Torque Vectoring and Active Suspension System

Four-wheel independently driven electric vehicles(FWID-EV)endow a flexible and scalable control framework to improve vehicle performance.This paper integrates the torque vectoring and active suspension system(ASS)to enhance the vehicle’s longitudinal and vertical motion control performance.While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden.To facilitate the controller design and ease the load,a half-vehicle dynamics system is built and simplified to the linear-time-varying(LTV)model.Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety,energy-saving and comfort requirements.The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption.Finally,the effectiveness of the proposed controller is verified through the rapid-control-prototype(RCP)test.The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

Control strategy of a novel electric power steering system integrated with active front steering function

A novel electric power steering system(EPS) integrated with active front steering(AFS) is developed.It has functions of both AFS system and EPS system with two actuator units:the AFS actuator unit and the EPS actuator unit.The AFS actuator unit controls the displacement transfer behavior of the steering system,and improves the handling stability under adverse road conditions by varying the steering ratio directly related to the speed and road conditions.The EPS actuator unit controls the force transfer behavior of the steering system,and improves the steering portability and road feel of the vehicle.Based on a dynamic model,the mixed H2/H∞ control strategy of the EPS actuator and the active steering intervention control strategy of the AFS actuator are designed.The simulation indicates that the novel EPS system with the designed control strategies has obvious advantages in vehicle handling stability and the driver's road feel over the traditional EPS system,and extends the vehicle's steering performance.

Lateral stability region conservativeness estimation and torque distribution for FWIA electric vehicle steering

Estimation of the lateral stability region and torque distribution on steering is very important to improve stability in lateral handling for all wheel drive electric vehicles.Based on the built-nonlinear vehicle dynamic model,the lateral stability region of the vehicle related to steering is estimated using Lyapunov function.We obtained stable equilibrium points of non-straight driving according to the estimated lateral stability region and also reconstructed the Lyapunov function matrix,which proved that the closed-loop system composed of yaw rate and lateral velocity is satisfied with negative definite property.In addition,the designed controller dynamically allocates the drive torque in terms of the vertical load and slip rate of the four wheels.The simulation results show that the estimated lateral stability region and the designed controller are satisfactory in handling stability performance against different roads and vehicle parameters.

基于电动方向盘的拖拉机自动导航转向控制方法

为提高轮式拖拉机自动导航过程中转向控制的精度与稳定性,该研究以雷沃欧豹M704-2H拖拉机作为试验平台,采用电动方向盘作为转向执行机构,分析转向机械间隙对控制精度的影响,针对转向间隙特性设计转向控制算法。首先,为了获得准确的转向角,利用GNSS(global navigation satellite system)与二轮车模型快速标定虚拟轮转角,标定结果表明:虚拟轮转角的最大误差为1.3°,平均误差为0.11°。然后,对转向系统的机械间隙进行分析,设计一种带有间隙补偿的模糊PD(proportional derivative)转向控制算法,并在Simulink中验证算法的可行性。实车试验结果表明,该算法跟踪方波转角信号的响应时间为1.1 s,最大稳态误差为0.65°,平均稳态绝对误差为0.132°。跟踪正弦波转角信号的平均延时为0.5 s,最大误差为1.91°,平均绝对误差为1.09°。与无间隙补偿算法相比,有间隙补偿算法跟踪方波信号最大稳态误差减小了0.022°,平均稳态绝对误差减少了0.112°,角度误差在±0.2°内的时间提升了71%;跟踪正弦波信号最大误差减小了0.68°,平均绝对误差减小0.23°。田间直线导航转向控制试验结果表明,转角跟踪的绝对平均误差为0.61°,最大跟踪误差为2.82°,转向控制跟踪精度较高,稳定性好,满足导航作业需求。

乘用车双电机冗余电动助力转向系统研究

为了提高电动助力转向系统的安全性以及可靠性,基于乘用车提出一种双电机冗余电动助力转向技术,采用转向执行双助力电机,可以从硬件上实现冗余,避免任意单电机发生故障时导致转向系统的失效,不仅可以满足转向系统对于轻便型、助力跟随性的要求,还可以减轻单个助力电机的负载提高电机的使用寿命。针对提出的问题,介绍了对双电机阻力转向系统整体结构及工作原理,并对其关键零部件进行分析论述。搭建双电机冗余系统仿真模型,双电机电流分配采用“一主一辅”的控制方式,并进行方向盘多种工况仿真验证。针对助力转向出现抖动问题,结合“扫频试验”,设计输出转矩超前滞后补偿方式进行相位校正补偿。通过实车试验验证了该算法的准确性和有效性。实验结果表明双冗余电动助力转向系统极大提高了转向力矩的稳定性,抑制其扰动性,有较好的助力效果,极大提高系统的可靠性和安全性。

混合动力汽车转向稳定性多传感器融合控制技术

为了满足汽车行驶稳定性要求,当前依托于单一传感信息进行转向控制,容易忽略很多影响因素,使得控制后汽车转向质心侧偏角依旧较大。因此,混合动力汽车提出转向稳定性多传感器融合控制技术。考虑混合动力汽车转向过程中的动态特性,构建转向动力学模型,并计算出车辆理想横摆角速度。深入分析横摆角速度、滑移率对车辆转向稳定性的影响,得出期望的横摆力矩和滑移率调整力矩。将汽车转向稳定性控制问题看作二次规划问题,结合BP神经网络和常规PID控制器,设计转向稳定性控制算法,利用车辆转向参数的理想值、实际值和偏差值推算出稳定性控制参数。结合融合多传感器实时采集信息,推算出汽车转向姿态误差代入控制结构中,给出优化后的控制参数。实验结果表明:新提出的控制技术应用后,车辆转向的质心侧偏角不超过±0.012 rad/s,满足了混合动力汽车转向行驶要求。

基于粒子群优化算法PID参数优化的双电机耦合驱动履带车辆转向控制

针对电驱动履带车辆转向灵敏度不高、控制精度难的问题进行转向控制策略研究,对双电机耦合驱动履带车辆开展动力学分析,利用数学仿真软件建立转向动力学模型。设计一种基于粒子群优化算法对比例-微分-积分控制器(Proportional-Integral-Differential controller,PID)参数优化的转向控制策略,以改进型时间乘绝对误差积分指标为粒子群优化算法目标函数,对PID转向控制策略中的控制参数进行实时优化,动态调节控制参数,实现车辆转向控制系统优化输出。利用硬件在环仿真平台和实车试验,对控制策略进行仿真和实车试验验证,试验结果验证了控制策略的有效性。

分布式驱动电动汽车执行器失效容错控制研究

为了提高单电机故障状态下分布式驱动电动汽车的稳定性,提出了一种驱动力重构和主动前轮转向(AFS)结合的容错控制方法。首先,设计滑模控制器,控制输入量为横摆角速度和质心侧偏角,进而对所需横摆力矩和前轮附加转角进行控制。其次,建立电机故障状态下的整车驱动力优化分配模型。当车辆电机出现故障时,运用二次规划算法对各电机转矩进行重构分配。同时,当某一电机发生故障且同侧电机出现输出饱和而无法提供足够的横摆力矩时,通过主动前轮转向提供附加横摆力矩。最终搭建CarSim/Simulink联合仿真模型进行验证,结果显示,所采用的容错控制方法可有效提高车辆稳定性和动力性。

设施园艺移动平台分布式驱动自适应防滑控制

针对设施园艺特殊作业场景对电驱移动平台灵活作业与高操纵稳定性需求,该研究设计了一种四轮轮毂电机独立驱动的分布式设施园艺电驱移动平台,并提出了一种可提高转向灵活性与稳定性的自适应防滑控制策略。在该控制策略中,首先构建电驱移动平台动力学模型与Ackermann差速转向模型,结合速度瞬心原理及轮胎侧偏角确定各车轮转向目标转速;其次,为提高电驱移动平台对时变附着系数的适应能力,采用改进的强跟踪自适应无迹卡尔曼滤波算法设计复杂路面识别器,实现对路面附着系数准确估计;最后,设计基于自适应滑模算法的防滑控制器,根据路面附着系数估计值确定车轮相对最佳滑转率并实时控制滑转率。为验证所提控制策略的有效性,开展了Carsim-MATLAB/Simulink联合仿真与分布式设施园艺电驱移动平台实车试验。试验结果表明,所提控制策略可准确估计复杂道路下路面附着系数,降低车轮滑转率误差;在不变路面、对接路面与对开路面3种工况下,左侧车轮滑转率误差分别为0.031、0.015和0.038,右侧车轮滑转率误差分别为0.026、0.005和0.028;在不变路面与随机路面实测路况下,电驱移动平台路面附着系分别数约为0.44和0.47,最大滑转率分别约为0.69和0.68,有效抑制了轮胎转向时的过度滑转,提高了电驱移动平台的行驶稳定性。研究可为设施园艺车辆驱动防滑控制提供具体理论依据和实施方案。

轮毂电机驱动电动汽车4WS和DYC协调控制

为了提高轮毂电机驱动电动汽车的路径跟踪能力和操纵稳定性,本文针对主动四轮转向系统(4WS)和直接横摆力矩控制系统(DYC)提出一种新型的协调控制策略。首先,综合考虑车辆的路径跟踪性能和操纵稳定性,建立一种共享转向控制模型,并在此基础上提出基于非合作Nash博弈的4WS控制策略。其次,为了提高危险行驶工况下的车辆侧向稳定性,基于质心侧偏角相平面将车辆状态划分为稳定区域、过渡区域和失稳区域,并分区域建立DYC控制器。再次,为了实现后轮转向与直接横摆力矩的协同控制,建立基于模糊神经网络的ARS/DYC协调控制器。最后,利用CarSim/Simulink联合仿真平台和硬件在环平台,分别进行双移线工况下的试验验证。研究结果表明,所提出的控制策略能够有效地提高车辆在极端行驶工况下的路径跟踪精度和操纵稳定性能。

机械弹性电动轮驱动车辆横摆稳定性协调控制

针对匹配机械弹性电动轮(MEEW)车辆的横摆稳定性控制问题,提出一种基于主动前轮转向(AFS)与直接横摆力矩控制(DYC)的稳定性协调控制策略。为修正车辆行驶过程中的前轮转角输入,设计了基于微分平坦与RBF神经网络的AFS控制器,从而提高车辆的转向能力。针对AFS控制器在极限工况下易失效的缺陷,引入基于线性二次型调节器(LQR)的直接横摆力矩控制算法,并依照轴荷比分配四轮力矩。最后,依据机械弹性电动轮的质心侧偏角-质心侧偏角速度相平面图划分稳定域,实现AFS与DYC的协调控制。通过Matlab/Simulink和Carsim进行联合仿真,结果表明:所提出的AFS控制算法在高速高附着工况下有良好的稳定控制性能,但在高速、低附着极限工况下控制效果受到影响。而AFS/DYC协调控制策略效果较好,跟踪精度优于单一控制器,质心侧偏角和横摆角速度的最大跟踪误差仅为3.03°和1.82(°)/s,可保证汽车在极限工况下转向时的横摆稳定性。

基于FPGA的电动舵机滑模控制系统

电动舵机是现代无人机飞控系统的关键组成部分。针对传统电动舵机系统抑制干扰能力差、跟踪精度低、响应速度慢的问题,提出一种改进优化的自适应滑模控制(SMC)算法。首先,在进行系统建模和实验平台搭建时考虑了外界扰动和摩擦间隙等非线性问题,以此为基础设计了新的滑模面函数;其次,通过重新设计切换控制函数,使舵面偏转角度更加准确,有效的提高了系统的跟踪精度;最后,在系统中引入一阶低通滤波器,有效的消除了控制量抖振问题。并通过FPGA芯片实现了该算法,设计实验加以验证。实验结果表明,与传统PID算法相比,改进的滑模控制算法具有较强的抑制干扰能力和较快的动态响应速度,跟踪误差也有明显的下降。由此可见该算法在解决电动舵机的非线性问题方面具有较强的优势,基本满足舵面偏转的精准控制需求,在无人机产品的生产实践中具有较强的实际应用价值。