基于滑模变结构的飞机防滑刹车控制器设计

以飞机全电刹车为研究背景,采用滑模变结构控制策略,设计刹车防滑控制策略,解决传统刹车效率低、机轮深度打滑、低速刹车性能差等问题.在控制策略中,以最佳滑移率为目标函数,设计滑模面,实现刹车防滑控制.由于滑模控制的强鲁棒性,可有效提高系统的抗干扰能力.仿真结果可知,滑移率控制在最佳滑移率附近,刹车效率高,可消除机轮深度打滑现象,防滑效果优良.     

基于干扰估计的非对称运动下飞机刹车系统模型预测控制

针对飞机在非对称运动下的双侧机轮协调控制问题, 提出一种基于滑模干扰估计的模型预测控制方法. 首先, 通过对飞机制动过程横纵方向力矩机理分析并分别考虑左右机轮对刹车性能的影响, 建立全面刻画系统动态的地面滑跑动力学模型. 在此基础上, 设计滑模观测器对侧风干扰进行实时估计, 利用补偿机制实现对侧风扰动的有效抑制. 此外, 提出基于前轮荷载状态门限特征和结合系数阈值范围特征的分析方法, 解决切换跑道环境辨识问题. 设计非线性模型预测算法, 实现飞机纵向防滑刹车和横向跑道纠偏的协调控制. 最后, 在侧风干扰、跑道切换以及不对称着陆等情况下进行仿真实验, 验证了所提出的控制策略能够有效提升刹车系统的防滑效率及纠偏性能.     

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.     

基于自适应线性自抗扰控制的飞机防滑刹车系统重构控制

飞机防滑刹车系统是确保飞机安全起飞、着陆和滑跑的重要航空机电系统. 除了其动力学中的强非线 性、强耦合以及参数时变外, 潜在的执行器等组件故障也会严重降低防滑刹车系统的安全性与可靠性. 为满足故障 及扰动状态下系统的性能需求, 本文提出了一种基于自适应线性自抗扰控制的飞机防滑刹车系统重构控制方法. 根据飞机防滑刹车系统的组成结构及工作原理对其进行数学建模, 并对执行器注入故障因子. 设计了自适应线性 自抗扰重构控制器, 同时分析了整个闭环系统的稳定性. 该控制器将组件故障、外部干扰以及测量噪声等视为总扰 动, 根据状态误差反馈和系统输出信息, 利用BP神经网络在线优化更新扩张状态观测器和状态误差反馈律参数, 从 而更精确地观测与补偿总扰动带来的不利影响. 最后, 在不同跑道环境下的仿真结果验证了所提出重构控制器的适 应性和鲁棒性.     

基于T-S模糊神经网络的飞机防滑刹车系统研究

航空业的发展对飞机防滑刹车系统提出了更高的要求,而传统PID+PBM控制器存在着低速打滑、刹车效率较低等问题;针对刹车过程中的不确定性和非线性问题,提出采用T-S模糊神经网络来进行防滑刹车控制器设计;在MATLAB/SIMULINK平台建立飞机刹车总体仿真模型,将设计的控制器与传统控制器进行对比仿真试验;仿真结果表明,基于T-S模糊神经网络的控制器解决了传统PID+PBM系统存在的问题,具有良好的控制效果,系统具有鲁棒性,能够适应变化的跑道情况,为飞机防滑刹车控制提供了一种新的方法。     

飞机防滑刹车系统模糊滑模控制研究北大核心

针对现在飞机广泛应用的“PD+PBM”控制律难以对具有强非线性和不确定性的飞机防滑刹车系统进行高性能控制的问题,提出飞机防滑刹车系统基于模糊指数趋近律的滑模变结构控制律。先建立具有不确定扰动的飞机防滑刹车系统的地面动力学模型以消除模型误差所带来的不利影响,然后设计了基于指数趋近律的滑模变结构控制律以改善控制性能,并利用李雅普诺夫定理证明了系统的稳定性,最后基于模糊理论对滑模控制律进行优化以抑制抖振。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“PD+PBM”控制律和传统的滑模控制律,抑制控制器输出抖振效果良好,刹车效率高,控制方法合理有效。     

无人机全电式自主刹车系统滑模极值搜索控制

常规主动刹车系统采用在线辨识跑道特征的算法,但仍需依赖摩擦模型先验知识,难以应对复杂跑道工况.为克服上述问题,提出一种滑模极值搜索控制策略并应用于无人机全电式自主刹车系统.考虑电动作动机构非线性特性,建立系统的状态空间模型并合理简化为严格反馈形式,采用超扭曲算法估计结合系数的梯度,结合反馈线性化控制律得到刹车压力参考值,证明此控制作用下可实现对未知最优滑移率的渐近跟踪.采用反演控制的思想设计无抖振滑模控制器实现对参考刹车压力的跟踪.利用Lyapunov方法获得系统的渐近稳定性条件并分析控制参数对系统的影响.半实物仿真试验结果表明控制策略的有效性.     

飞机防滑刹车系统新型控制策略研究

飞机防滑刹车控制系统是重要的机载设备,对飞机的安全起飞和着陆有着重要作用.NASA研究数据表明,传统的PD+ PBM控制律在混合跑道刹车性能下降,且在低速段容易出现严重的打滑现象,导致系统刹车效率降低.对飞机防滑刹车系统的工作原理进行了分析,针对传统控制律的不足,提出了一种基于免疫PID的新型刹车控制策略.在计算机建立...     

基于DSP的飞机防滑刹车控制系统设计

在分析飞机防滑刹车控制系统组成及工作原理的基础上,设计了一种基于数字信号处理器(DSP)的飞机防滑刹车控制器.控制器采用DSP作为核心处理单元,设计了故障监控模块和AD采集模块等,结合等效滑模控制作为防滑控制算法,实现数字防滑刹车控制器的硬件及软件设计.结果表明,基于DSP的防滑刹车控制器运行可靠稳定,具有较高的刹车效率,能够满足飞机防滑刹车系统的要求.     

非线性不确定系统的非奇异快速终端滑模控制

针对存在非匹配干扰的非线性系统,设计了一种基于干扰观测器和反步法的非奇异快速终端滑模控制.引入非线性干扰观测器估计系统的不确定性,利用反步的思想处理高阶非线性系统,从而可以将非线性干扰观测器估计的干扰值引入反步法的虚拟控制量中,同时设计一种新颖的非奇异快速终端滑模控制律保证系统的收敛速度和精度.利用Lyapunov函数从理论上证明了所设计的控制器可以保证闭环系统的有限时间收敛.最后通过数值仿真验证了所设计的控制方法的有效性.     

防抱制动系统滑模状态观测和控制系统仿真

该文在考虑不平路面随机激励作用下车辆垂向振动的基础上 ,首先建立了四分之一车辆制动模型 ,而后充分运用滑移模式变结构的分析和设计方法 ,提出了车轮最佳滑移率的滑模实时在线辨识滑模优化算法 ,在对系统可观测性论证的基础上 ,设计了非线性滑模状态观测器 ,给出了单通道防抱制动系统基于滑移率的滑模控制算法 ,通过计算机仿真 ,验证了该控制算法的可行性和有效性 ,为设计具有高鲁棒性的防抱制动系统做了一定的理论探索和仿真工作     

无模型自适应控制在飞机防滑刹车中的应用

针对飞机防滑刹车系统的复杂性和非线性,在分析滑移率控制式飞机防滑刹车系统的工作原理基础上,提出了一种基于无模型自适应控制的飞机防滑刹车控制算法;该算法无需精确的动力学模型,直接利用输入输出信息实现飞机防滑刹车的最佳滑移率控制;仿真结果表明:采用无模自适应防滑刹车控制算法,在5s之内就能获得稳定的滑移率,为提高飞机刹车的效率提供了一条新的思路。     

A novel method for non-linear control of wheel slip in anti-lock braking systems

Anti-lock braking system (ABS) provides active safety for vehicles during braking by regulation of the wheel slip at its optimum value. Due to the non-linear characteristics and model uncertainties in vehicle dynamics, a non-linear controller with increased robustness should be designed for ABS. In this paper, to achieve this aim, an optimization-based braking torque control law is developed for ABS using the prediction of the wheel slip response from a continuous non-linear vehicle dynamics model. To increase the robustness of the controller, the integral feedback technique is appended to the design method. The derived control law and its special cases are evaluated and discussed. At the end, the performance of the proposed controller is compared with that of a sliding mode controller, reported in the literature, through simulations of braking on dry and slippery roads. The simulation results indicate that, the wheel slip tracking error is remarkably decreased by the proposed controller. Moreover, the achieved control input is entirely smooth and suitable for implementation.     

Backstepping dynamic surface control for an anti-skid braking system

The electric aircraft landing system, as one of the important components of more electric aircraft (MEA) and all electric aircraft (AEA), has been a subject of interest in recent years. An anti-skid braking system (ABS), which is the crucial component of the electric aircraft landing system, has the function of regulating the wheel slip ratio such that the braking process operates in a stable state. In this paper, an approach that combines a nonlinear backstepping dynamic surface control (DSC) and an asymmetric barrier Lyapunov function (ABLF) is presented to not only track the reference slip ratio but also to avoid the slip ratio in the unstable region. We demonstrate that the proposed controller can guarantee the boundedness of the output constraints and the stability of the overall system. Using the ABLF allows one to relax the required initial conditions on the starting values of the wheel slip ratio and subsequently make the wheel slip constraints more flexible for various runway surfaces and runway transitions. The DSC is introduced to eliminate repeated differentiation resulting from ABLF synthesis, which can relax the restrictions on the high-order differentiability for stabilizing functions and the high power of wheel slip tracking error transformation. The proposed controller can avoid the negative effects of disturbance produced by repeated differentiation and can construct a simple controller for wheel slip control. The results of simulations with varying runway surfaces have validated the effectiveness of the proposed control scheme, in which the output constraints on the wheel slip ratio are guaranteed not to be violated and self-locking is avoided.     

Estimation of road frictional force and wheel slip for effective antilock braking system (ABS) control

The introduction of electric braking via brake‐by‐wire systems in electric vehicles) has reduced the high transportation delays usually involved in conventional friction braking systems. This has facilitated the design of more efficient and advanced control schemes for antilock braking systems (ABSs). However, accurate estimation of the tire‐road friction coefficient, which cannot be measured directly, is required. This paper presents a review of existing estimation methods, focusing on sliding‐mode techniques, followed by the development of a novel friction estimation technique, which is used to design an efficient ABS control system. This is a novel slip‐based estimation method, which accommodates the coupling between the vehicle dynamics, wheel dynamics, and suspension dynamics in a cascaded structure. A higher‐order sliding‐mode observer–based scheme is designed, considering the nonlinear relationship between friction and slip. A first‐order sliding‐mode observer is also designed based on a purely linear relationship. A key feature of the proposed estimation schemes is the inclusion of road slope and the effective radius of the tire as an estimated state. These parameters impact significantly on the accuracy of slip and friction estimation. The performance of the proposed estimation schemes are validated and benchmarked against a Kalman filter (KF) by a series of simulation tests. It is demonstrated that the sliding‐mode observer paradigm is an important tool in developing the next generation ABS systems for electric vehicles.     

基于模糊神经网络的飞机防滑刹车系统研究

以某型飞机刹车系统为研究对象,为了使该系统以最佳滑移率工作,防止陷入深度打滑和获得最大的刹车结合系数,提出了一种智能飞机防滑刹车系统的设计方案,制定出刹车控制规律并对整个刹车系统进行了仿真。改进了现有飞机刹车防滑系统的控制算法,应用神经网络BP算法实时获取最佳滑移率,利用模糊神经网络实现快速逼近给定滑移率,并采用基于数字信号处理器（DSP）的硬件电路实现了智能刹车控制。实验结果表明,飞机防滑刹车效率有了明显改进,鲁棒性增强。     

Intelligent exponential sliding-mode control with uncertainty estimator for antilock braking systems

The purpose of the antilock braking system (ABS) is to regulate the wheel longitudinal slip at its optimum point in order to generate the maximum braking force; however, the vehicle braking dynamic is highly nonlinear. To relax the requirement of detailed system dynamics, this paper proposes an intelligent exponential sliding-mode control (IESMC) system for an ABS. A functional recurrent fuzzy neural network (FRFNN) uncertainty estimator is designed to approximate the unknown nonlinear term of ABS dynamics, and the parameter adaptation laws are derived in the sense of projection algorithm and Lyapunov stability theorem to ensure the stable control performance. Since the outputs of the functional expansion unit are used as the output weights of the FRFNN uncertainty estimator, the FRFNN can effectively capture the input–output dynamic mapping. In addition, a nonlinear reaching law, which contains an exponential term of sliding surface to smoothly adapt the variations of sliding surface, is designed to reduce the level of the chattering phenomenon. Finally, the simulation results demonstrate that the proposed IESMC system can achieve robustness slip tracking performance in different road conditions.