Adaptive neuro-fuzzy wheel slip control

Due to complex and nonlinear dynamics of a braking process and complexity in the tire–road interaction, the control of automotive braking systems performance simultaneously with the wheel slip represents a challenging problem. The non-optimal wheel slip level during braking, causing inability to achieve the desired tire–road friction force strongly influences the braking distance. In addition, steerability and maneuverability of the vehicle could be disturbed. In this paper, an active neuro-fuzzy approach has been developed for improving the wheel slip control in the longitudinal direction of the commercial vehicle. The dynamic neural network has been used for prediction and an adaptive control of the brake actuation pressure, during each braking cycle, according to the identified maximum adhesion coefficient between the wheel and road surface. The brake actuation pressure was dynamically adjusted on the level that provides the optimal level of the longitudinal wheel slip vs. the brake pressure selected by driver, the current vehicle speed, the brake interface temperature, vehicle load conditions, and the current value of longitudinal wheel slip. Thus the dynamic neural network model operates (learn, generalize and predict) on-line during each braking cycle, fuzzy logic has been integrated with the neural model as a support to the neural controller control actions in the case when prediction error of the dynamic neural model reached the predefined value. The hybrid control approach presented here provided intelligent dynamic model – based control of the brake actuation pressure in order to keep the longitudinal wheel slip on the optimum level during a braking cycle.     

基于车用电涡流缓速器温度场分析控制系统设计

随着车辆向大型化、高速化发展,车辆正常行驶制动能量增加,传统的摩擦制动器已经难以满足使用要求,很容易诱发一些故障;电涡流缓速器以其非接触无摩擦,响应时间短,无明显时间滞后,工作时噪声很小,能够提供车辆正常行驶85%的制动功率等优点成为新型的车辆辅助制动系统;采用ANSYS软件实现电涡流缓速器转子盘的二维温度场分析,对不同宽度的转筒式电涡流缓速器的温度分布进行数据采集,建立转筒式电涡流缓速器转筒的二维模型,采用虚拟边界法进行简化处理,然后根据系统不同的载荷和约束条件进行温度场控制系统建模;最后做了大量的仿真实验,模拟了依据不同的制动力矩,不同的磁路结构以及转子盘温升来分析对汽车制动性的影响。     

嵌入式飞机防滑刹车动态测试分析系统设计

针对飞机防滑刹车系统测试中无法进行动态跟踪而难以采取最优系统控制策略的问题,设计了一种用基于ARM嵌入式系统的飞机刹车动态测试分析系统;该系统通过对飞机刹车中的机轮及其刹车盘建立数学模型,利用ARM嵌入式技术进行算法移植,实现了刹车系统的模拟及其动态过程的测试分析,解决了飞机刹车模拟和动态测试系统的实时性管理的问题;工程试验结果表明该嵌入式动态测试系统,能有效地模拟刹车过程,并动态跟踪和分析飞机刹车参数的变化。     

Implementable strategy research of brake energy recovery based on dynamic programming algorithm for a parallel hydraulic hybrid bus

The purpose of this paper is to develop an implementable strategy of brake energy recovery for a parallel hydraulic hybrid bus. Based on brake process analysis, a dynamic programming algorithm of brake energy recovery is established. And then an implementable strategy of brake energy recovery is proposed by the constraint variable trajectories analysis of the dynamic programming algorithm in the typical urban bus cycle. The simulation results indicate the brake energy recovery efficiency of the accumulator can reach 60% in the dynamic programming algorithm. And the hydraulic hybrid system can output braking torque as much as possible.Moreover, the accumulator has almost equal efficiency of brake energy recovery between the implementable strategy and the dynamic programming algorithm. Therefore, the implementable strategy is very effective in improving the efficiency of brake energy recovery.The road tests show the fuel economy of the hydraulic hybrid bus improves by 22.6% compared with the conventional bus.     

飞机防滑刹车控制方法综述

飞机防滑刹车系统具有复杂动态特性,防滑刹车控制器的性能对飞机着陆的安全性具有重要作用。针对此问题,回顾了飞机防滑刹车系统的发展历程和主要控制方式,分析了飞机刹车系统的动态特性及影响刹车性能的主要因素。评述了基于数学模型的传统控制方法和基于模糊控制、神经网络等人工智能技术的智能控制方法在机轮防滑刹车控制中的研究与应用情况,并探索了当前防滑刹车控制方法研究中所面临和需要解决的关键问题,展望了未来控制系统的发展趋势。     

A mechatronic conception of a new intelligent braking system

This paper describes a new intelligent braking system for motor vehicles. A mechatronic approach helped to avoid some of the drawbacks found in conventional systems. The brake was designed according to the so-called “full contact disc brake” principle, which means that the classic pads are replaced by the whole discs and that—for maximum performance—the brake is controlled continuously and not cyclically as with classic ABS systems. This required a complete re-design of the regulation chain, the actuators and sensors. Indeed, to provide better control, the regulator uses feedback information not only from slip, but also from the braking torque.     

基于双向长短期记忆网络的DA40飞机碳刹车片剩余寿命预测

飞机刹车片在飞机制动过程中起着十分重要的作用。对刹车片进行准确的剩余使用寿命（RUL）预测对于减少制动故障以及节省人力物力资源具有重要意义。针对飞机刹车片磨损序列的非平稳和非线性等特点,提出了一种基于双向长短期记忆（BiLSTM）网络的飞机刹车片RUL预测模型——VMD-BiLSTM模型。首先,利用变分模态分解（VMD）方法将原始磨损序列分解成多个具有不同频率和带宽的子序列,从而降低序列的非平稳性;然后,对分解后的各子序列分别构造BiLSTM神经网络预测模型;最后,将每个子序列的预测值叠加来得到刹车片磨损值的最终预测结果,从而实现刹车片的寿命预测。仿真结果表明,VMD-BiLSTM模型的均方根误差（RMSE）为0.466,平均绝对百分比误差（MAPE）为0.898%,均优于对比模型,验证了VMD-BiLSTM模型的优越性。     

基于补偿神经网络的模糊飞机刹车控制系统研究

尽管飞机防滑刹车可以在保持可操纵性的同时优化刹车效率，但遇到不同路况时刹车性能却时常下降。为了在防滑的同时获得最大的刹车结合系数，该文提出了新的飞机防滑刹车控制律：基于补偿神经网络的模糊控制。控制器识别飞机和机轮的速度反馈，从而调整刹车力矩实现优化刹车。同时系统又可根据复杂的路况，通过补偿神经网络进行自优化。通过MATLAB、VC仿真得出滑移率跟踪曲线。结果表明刹车系统在适应不同路况时有很好的控制性能。     

考虑非线性因素的飞机防滑刹车系统控制

飞机的刹车过程存在较强的非线性,目前广泛应用的速度差加压力偏调式(PBM)控制律难以实现对飞机刹车的高性能控制.本文提出了一种考虑飞机刹车过程中非线性因素的滑模控制律.首先建立考虑轮胎跑道非线性和刹车盘摩擦系数非线性的的飞机防滑刹车系统非线性模型,然后设计了滑模观测器对飞机速度进行估计,并在此基础上设计了一种滑模变结构控制律,最后基于模糊理论对滑模控制律进行优化,从而抑制控制器的抖振.仿真结果表明,基于模糊指数趋近律的滑模变结构控制律控制效果优于传统“PD+PBM”控制律,抑制控制器输出抖振效果良好,能够很好的适应刹车过程中的复杂非线性因素,刹车效率高,控制方法合理有效.     

一种新型剪切阀式旋转MR制动器的开发与评估

基于磁流变（Magnetorheological,MR）液的流变特性,MR制动器具有的高转矩-体积比(Torque-to-Volume Ratio,TVR)和低功耗优点使其成为一种应用前景广泛的被动力输出装置。为了提高旋转型MR制动器在单位空间内的输出制动转矩,基于凸轮结构提出了一种在剪切阀模式下工作的旋转型MR制动器。首先,介绍了这种新型MR制动器的总体结构,并基于Bingham塑性模型和凸轮模型对MR制动器的输出制动转矩进行了理论推导。然后,利用ANSYS软件和多目标优化设计方法,对制动器的结构进行有限元分析,得到最优的几何参数。在自主搭建的实验平台上对制动器进行了性能测试实验,结果表明,该制动器具有较高的TVR、较低的初始制动转矩和良好的动态特性。该制动器在较小的体积下能够实现最大42.4 kN/m³的TVR,可以很好地满足力触觉交互、康复训练、可穿戴设备等需要小体积和大输出转矩的应用场景。     

基于LS-SVM的涡轮增压发动机性能预测

针对神经网络方法在涡轮增压发动机性能预测方面存在的缺陷,提出了一种新的基于最小二乘支持向量机的涡轮增压发动机性能智能预测方法.介绍了最小二乘支持向量机的基本算法,分析了涡轮增压发动机的性能指标,选择发动机转速、压缩比、容积效率、平均指示压力和平均制动压力作为预测模型的输入参数,输出功率、输出扭矩和有效燃油消耗率作为预测模型的输出量,进一步建立了基于最小二乘支持向量机的涡轮增压发动机性能预测模型.仿真实例的预测结果表明,所建立的智能涡轮增压发动机性能预测模型是合理有效的.     

A fuzzy logic controller for an ABS braking system

Anti-blocking system (ABS) brake controllers pose unique challenges to the designer: a) For optimal performance, the controller must operate at an unstable equilibrium point, b) Depending on road conditions, the maximum braking torque may vary over a wide range, c) The tire slippage measurement signal, crucial for controller performance, is both highly uncertain and noisy, d) On rough roads, the tire slip ratio varies widely and rapidly due to tire bouncing, and e) The braking system contains transportation delays which limit the control system bandwidth. A digital controller design was chosen which combines a fuzzy logic element and a decision logic network. The controller identifies the current road condition and generates a command braking pressure signal, based on current and past readings of the slip ratio and brake pressure. The controller detects wheel blockage immediately and avoids excessive slipping. The ABS system performance is examined on a quarter vehicle model with nonlinear elastic suspension. The parallelity of the fuzzy logic evaluation process ensures rapid computation of the controller output signal, requiring less time and fewer computation steps than controllers with adaptive identification. The robustness of the braking system is investigated on rough roads and in the presence of large measurement noise. This paper describes design criteria, and the decision and rule structure of the control system. The simulation results present the system's performance on various road types and under rapidly changing road conditions     

Evaluation of antilock braking system with an integrated model of full vehicle system dynamics

Antilock braking system (ABS), traction control system, etc. are used in modern automobiles for enhanced safety and reliability. Autonomous ABS system can take over the traction control of the vehicle either completely or partially. An antilock braking system using an on–off control strategy to maintain the wheel slip within a predefined range is studied here. The controller design needs integration with the vehicle dynamics model. A single wheel or a bicycle vehicle model considers only constant normal loading on the wheels. On the other hand, a four wheel vehicle model that accounts for dynamic normal loading on the wheels and generates correct lateral forces is suitable for reliable brake system design. This paper describes an integrated vehicle braking system dynamics and control modeling procedure for a four wheel vehicle. The vehicle system comprises several energy domains. The interdisciplinary modeling technique called bond graph is used to integrate models in different energy domains and control systems. The bond graph model of the integrated vehicle dynamic system is developed in a modular and hierarchical modeling environment and is simulated to evaluate the performance of the ABS system under various operating conditions.     

基于模糊控制的汽车防抱制动系统仿真

汽车防抱制动系统(ABS)通过在制动过程中自动控制车轮的制动力矩从而防止了车轮抱死。这对于提高汽车制动时的方向稳定性和转向操纵性，改善汽车的制动效能，保证驾驶员和乘客的安全是十分重要的。文中通过对某轻型客车的防抱制动过程进行动力学分析，建立了该轻型客车ABS模糊控制系统的数学模型，并且在Matlab／simullnk仿真软件下进行了计算机仿真。仿真结果表明，模糊控制的防抱制动系统能取得较好的控制效果，具有一定的自适应能力。     

Evaluation of antilock braking system with an integrated model of full vehicle system dynamics

Antilock braking system (ABS), traction control system, etc. are used in modern automobiles for enhanced safety and reliability. Autonomous ABS system can take over the traction control of the vehicle either completely or partially. An antilock braking system using an on–off control strategy to maintain the wheel slip within a predefined range is studied here. The controller design needs integration with the vehicle dynamics model. A single wheel or a bicycle vehicle model considers only constant normal loading on the wheels. On the other hand, a four wheel vehicle model that accounts for dynamic normal loading on the wheels and generates correct lateral forces is suitable for reliable brake system design. This paper describes an integrated vehicle braking system dynamics and control modeling procedure for a four wheel vehicle. The vehicle system comprises several energy domains. The interdisciplinary modeling technique called bond graph is used to integrate models in different energy domains and control systems. The bond graph model of the integrated vehicle dynamic system is developed in a modular and hierarchical modeling environment and is simulated to evaluate the performance of the ABS system under various operating conditions.     

基于分布式模型的动车组预测控制方法

针对动车组由若干动车/拖车组成的动力单元固定编组耦 合构成,难以用集中式模型进行有效描述的问题,提出一种动车组运 行过程的分布式描述与建模方法. 基于动车组牵引/制动特性曲线和实际运 行数据,采用子空间模型辨识方法建立了动车组各动力单元的分布式状态空间模型;提出基于分布式模型的动车组预测控制方法,给出了各动力单元牵引/制动力和运 行速度同步跟踪控制算法.基于CRH380AL型动车组运行过程数据的对比仿真结果验证了本文方法的有效性.     

Comparative nonlinear modeling of renal autoregulation in rats:Volterra approach versus artificial neural networks

In this paper, feedforward neural networks with two types of activation functions (sigmoidal and polynomial) are utilized for modeling the nonlinear dynamic relation between renal blood pressure and flow data, and their performance is compared to Volterra models obtained by use of the leading kernel estimation method based on Laguerre expansions. The results for the two types of artificial neural networks and the Volterra models are comparable in terms of normalized mean square error (NMSE) of the respective output prediction for independent testing data. However, the Volterra models obtained via the Laguerre expansion technique achieve this prediction NMSE with approximately half the number of free parameters relative to either neural-network model. However, both approaches are deemed effective in modeling nonlinear dynamic systems and their cooperative use is recommended in general     

Optimal Learning Slip Ratio Control for Tractor-semitrailer Braking in a Turn based on Fuzzy Logic

The research on braking performance a of tractor-semitrailer is a hard and difficult point in the field of vehicle reliability and safety technology. In this paper, the tire braking model and the dynamic characteristic model of the brake torque with the variable of the controlling air pressure were established. We also established a nonlinear kinematic model of the tractor-semitrailer when it brakes on a curve. The parameters and variables of the model were measured and determined by the road experiment test. The optimal control strategy for the tractor-semitrailer based on the optimal slipping ratio was proposed. Then the PID controller and the fuzzy controller were designed respectively. Simulation results show that the reasonable control strategy can significantly improve the braking directional stability when a tractor-semitrailer runs on a curving road. The research results provide technical references for improving the lateral stability when a tractor-semitrailer brakes on a curve, and it also provides a technical reference for the road traffic safety.     

Iterative learning control of a fully flexible valve actuation system for non-throttled engine load control

This paper presents the application of a fully flexible valve actuation system for non-throttled load control of an internal combustion engine. A novel camless valve actuation system with a unique hydro-mechanical internal feedback mechanism which simplifies the external control design is first introduced. All the critical parameters describing the engine valve event, i.e., lift, timing, duration and seating velocity, can be continuously varied by controlling the triggering timings of three two-state valves. Initial testing of a prototype experimental setup reveals that the performance of the system (transient tracking and steady-state variability) is influenced purely by the state of the system when the internal feedback mechanism is activated. This feature motivates the development of a cycle-to-cycle learning-based external control for activating the internal feedback mechanism based on the desired valve profile characteristics and the system state. To verify the proposed control methodology, it is implemented on the experimental system to track reference trajectories for the various valve event parameters corresponding to the non-throttled load control of an engine during the U.S. Federal Test Procedure (FTP) urban driving cycle. Vehicle load demand analysis is used to compute the desired engine speed and torque requirements. Detailed dynamic valve flow simulations assuming full flexibility of the engine valve event parameters help to calculate the required trajectory of all these parameters to satisfy the speed and torque requirements without the use of a throttle. The experimental results show that the proposed framework, i.e., the valve actuation system and the external control methodology, is able to provide excellent performance even during the most aggressive transient operating conditions.     

插电式混合动力汽车车速预测及整车控制策略

本文针对插电式混合动力汽车(plug-in hybrid electric vehicle,PHEV)这一典型混杂系统,提出了一种基于车速预测的混合逻辑动态(mixed logical dynamical,MLD)模型预测控制策略.首先,通过对发动机和电动机能量消耗模型进行线性化,建立双轴并联插电式混合动力城市公交车的动力传动系统数学模型;其次,运用模糊推理进行驾驶意图分析,提出基于驾驶意图识别和历史车速数据相结合的非线性自回归(nonlinear auto-regressive models,NAR)神经网络车速预测方法进行未来行驶工况预测.然后,以最小等效燃油消耗为目标建立PHEV的混合逻辑动态模型,运用预测控制思想对车速预测时域内最优电机转矩控制序列进行求解.最后,通过仿真实验验证了本文所提出控制策略在特定的循环工况下与电动助力策略相比,能够提高燃油经济性.