基于非线性干扰观测器的飞机全电刹车系统滑模控制设计

飞机防滑刹车具有典型的强非线性、强耦合和参数时变等特点, 并且跑道环境的干扰容易对飞机的地面滑跑性能造成不利影响. 本文提出了一种基于非线性干扰观测器的飞机全电防滑刹车系统滑模控制设计方法. 首先, 考虑了实际刹车不确定性干扰条件下的防滑刹车动力学建模问题, 通过对高阶非线性刹车系统进行反馈线性化处理, 简化了基于严格反馈的模型. 其次, 基于对主轮打滑原因的深入分析, 设计了非线性干扰观测器对干扰进行在线估计, 并在控制律设计中引入补偿部分. 通过构造递归结构的快速终端滑模控制器来跟踪实时变化的最佳滑移率并建立稳定性条件, 实现了飞机全电防滑刹车系统的有限时间快速稳定并有效抑制了主轮锁定打滑. 通过在不同跑道状态下进行模拟仿真, 验证了本文提出的飞机防滑刹车控制策略可以有效地提高刹车效率.     

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.     

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。     

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.     

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     

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.     

求解机场终端区飞机着陆调度问题的遗传算法

空中管制员需为到达的飞机安排跑道并计算着陆时间,以飞机空中延误最小为出发点研究了多跑道的飞机着陆调度问题,约束条件为每架飞机的着陆时间应落在规定的时间窗内及相邻两架飞机应满足最小时间间隔。针对该问题设计了一种遗传算法对问题进行求解,其中染色体由飞机排序链表和跑道链表组成,相应的交叉和变异算子也做了改进设计。仿真实验用数据库OR-Library中的实例验证了该算法的有效性。     

Controller design for vehicle stability enhancement

A Vehicle Dynamics Control (VDC) system is developed for tracking desired vehicle behavior. The cascade structure of control system consists of yaw moment major controller and wheel slip minor controller. The Linear Quadratic Regulator (LQR) theory is exploited for yaw moment controller and the sliding mode theory is applied for wheel slip controller design. The use of yaw moment control was investigated by regulating the wheel slip ratio for improving handling and stability of vehicle. The performance of the control system is evaluated under various emergency maneuvers and road conditions through pure computer simulations and Hardware In-the-Loop Simulation (HILS) system. The results indicate the proposed system can significantly improve vehicle stability for active safety.     

多轮系防滑验证试验测控系统的设计与实现

在地面惯性试验台上进行刹车模拟试验,是目前国内外常用的测试机轮刹车系统功能与性能试验方法。充分地在地面对影响飞机刹车性能的问题进行验证和解决,使飞机机轮及刹车系统达到最理想的装机条件和工作状态,需要依靠先进的系统检测试验手段。针对此类问题,尤其是多起落架、多机轮配置的大型飞机刹车系统试验对于整个起落架性能及匹配性问题,开展了本系统的设计及验证工作。多轮系机轮刹车系统综合动力试验台验证及系统防滑试验具有系统监测控制、信息采集、数据解析、实时显示存储等功能,能直观地展示试验过程以及结果,进而全面验证大型飞机起降系统的综合性能。改良原来的多轮防滑刹车试验系统,完善并提供必要的试验条件,缩短了机轮试验研制周期,实现起落架、机轮、刹车系统集成的匹配性、协调性、安全性和可靠性测试,极大地降低了飞机试飞的风险和成本。     

Practical active traction control for independent-wheel-drive electric vehicle based on slip-ratio threshold determination

The traditional traction control system (TCS) based on hydraulic braking only works when the wheels are slipping, which will cause the problem of slow response to extreme slip. In addition, the TCS of four-wheel-independent-drive electric vehicle (4WIDEV) is often based on road adhesion characteristics identification or optimal slip ratio identification to implement active control, which is difficult to achieve in engineering. Aiming at this problem, a practical active TCS is proposed in this paper. Firstly, according to the wheel slip state of the front and rear axles, the dynamic transfer of torque between axles is realized to maintain the vehicle propulsion power. Second, the adhesion conditions between road and tire are classified, and two sets of target slip ratio thresholds are formulated for high and low adhesion pavement, respectively. Then the current road adhesion coefficient is estimated by using the advantage that the in-wheel motor torque can be obtained in real-time. Thirdly, the overall framework of the control strategy is established, the logic threshold control algorithm is adopted for tracking the wheel target slip ratio. Finally, the simulation results show that the proposed active TCS can improve the vehicle power and avoid excessive wheel slipping.     

电动汽车低速电气制动防抱死功能的研究

研究电动汽车制动防抱死功能优化问题,电动汽车在冰雪路面上进行纯再生制动时,驱动轮极有可能抱死,从而造成车辆操纵稳定性下降。为解决上述问题,根据驱动电机在基速以下的调速特性,提出了调压调速型电气ABS模型。以单轮电动汽车模型为研究对象,设计了以车轮滑移率为控制目标的滑动模式防滑控制器。在Matlab/Simulink环境下建立了电气ABS仿真模型,仿真结果表明所建模型具有良好的稳定性;同时表明制动过程由初期的反接制动、为主体的中期再生制动及后期的反接制动构成;且制动精度明显高于传统ABS。研究结果对电动汽车再生制动系统的设计具有一定的参考价值。     

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。     

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.     

基于神经网络的飞机静液刹车系统设计

针对无人机的滑跑安全问题,为有效缩短刹车距离,提高刹车效率,设计了一种新型的静液刹车系统;根据新型刹车系统的特点,并综合考虑飞机机体、机轮、跑道状况的特性,以及刹车系统的非线性和不确定性,难以精确控制的特点,设计了神经网络控制器(NNC);并将神经网络控制器,新型刹车系统和飞机滑跑模型应用于仿真环境,建立了整体的仿真模型;仿真结果表明,采用神经网络的刹车系统鲁棒性增强,刹车效率提高,明显优于采用传统控制律的刹车系统。     

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.     

An intelligent approach to the lateral forces usage in controlling the vehicle yaw rate

A direct yaw moment control system (DYC) is designed to improve the handling and stability of a four‐wheel‐drive electric vehicle. The main task of this paper is to use the lateral forces in the process of optimally controlling vehicle stability. This is performed by defining a variable optimum region for the slip ratio of each wheel. A hierarchical structure is selected to design the control system. The higher‐level control system controls the yaw rate of the vehicle based on the fuzzy logic technique. The lower‐level control system, installed in each wheel, maintains the slip ratio of the same wheel within an optimum region using the fuzzy logic technique. This optimum region for each wheel is continuously modified based on the impact of the lateral force on the generated control yaw moment and the friction coefficient of the road. Therefore, an algorithm for estimation of the friction coefficient is proposed. Computer simulations are carried out to investigate the effectiveness of the proposed method. This is accomplished by comparison of the results of control methods with a fixed slip ratio region and the results of the proposed method with a variable slip ratio region in some maneuvers. The robustness of the proposed controller against hard braking and noise contamination, as well as the effect of steering wheel angle amplitude, is verified. The simulation results show that the influence of the proposed method on enhancing vehicle performance is significant. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

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.     

Application of generalised neural network for aircraft landing control system

 It is observed that landing performance is the most typical phase of an aircraft performance. During landing operation the stability and controllability are the major considerations. To achieve a safe landing, an aircraft has to be controlled in such a way that its wheels touch the ground comfortably and gently within the paved surface of the runway. The conventional control theory found very successful in solving well defined problems, which are described precisely with definite and clearly mentioned boundaries. In real life systems the boundaries can't be defined clearly and conventional controller does not give satisfactory results. Whenever, an aircraft deviates from its glide path (gliding angle) during landing operation, it will affect the landing field, landing area as well as touch down point on the runway. To control correct gliding angle (glide path) of an aircraft while landing, various traditional controllers like PID controller or state space controller as well as maneuvering of pilots are used, but due to the presence of non-linearities of actuators and pilots these controllers do not give satisfactory results. Since artificial neural network can be used as an intelligent control technique and are able to control the correct gliding angle i.e. correct gliding path of an aircraft while landing through learning which can easily accommodate the aforesaid non-linearities. The existing neural network has various drawbacks such as large training time, large number of neurons and hidden layers required to deal with complex problems. To overcome these drawbacks and develop a non-linear controller for aircraft landing system a generalized neural network has been developed.     

基于DSP的飞机全电刹车测试系统的设计与实现

介绍了在飞机全电刹车测试系统中,应用高性能F2812 DSP,根据飞机动力学模型,模拟飞机刹车过程的真实环境,从而测试全电刹车系统的性能.实验结果表明,此系统能够准确可靠地向控制器实时传送飞机速度以及机轮角速度,较好地模拟了刹车过程的外部环境,实现了预定的测试功能.