高超声速飞行器最优PIF-LQR控制器设计

以一类通用高超声速飞行器的非线性纵向模型为研究对象,对其线性化后,应用LQR理论设计了一种多输人多输出的最优控制器.通过引入比例积分滤波器(PIF),有效地抑制模型参数变化所引起的扰动,实现飞行器对速度和高度变化指令精确跟踪.将所设计控制器应用于具有不确定参数的高超声速飞行器扰动模型,通过仿真对控制器的鲁棒性进行评估.仿真结果表明,尽管存在参数不确定性,所设计控制器能够满足高超声速飞行器在复杂飞行条件下的控制要求,具有较强的鲁棒性.     

基于Backstepping的高超声速飞行器模糊自适应控制

提出了高超声速飞行器的模糊自适应控制方法.根据飞行器纵向模型的特点,分别设计了基于动态逆的速度控制器和基于Backstepping的高度控制器,模糊自适应系统用来在线辨识飞行器模型由于气动参数的变化而引起的不确定性,采用Lyapunov理论设计的自适应律保证了系统的稳定性与指令跟踪的精确性.仿真使用了高超声速飞行器的纵向模型对算法进行了验证,得到了较满意的控制效果.     

基于模糊控制的高超声速飞行器二阶滑模姿态控制

考虑高超声速飞行器飞行过程中气动参数变动导致的不确定,将模糊控制与二阶滑模控制相结合,形成自适应模糊二阶滑模控制器,用于控制高超声速飞行器姿态的飞行系统中.依据奇异摄动理论,设计快速和慢速双闭环系统控制角速率和姿态角.设计二阶滑模控制器用于有效地衰减抖振,同时对姿态角指令实现准确和快速跟踪.采用自适应模糊逻辑逼近高超声速飞行器动力学和运动学模型中的不确定部分,以对控制器进行有效补偿,基于Lyapunov稳定性理论,推导模糊规则参数的自适应律,确保整个闭环控制系统的稳定.仿真结果表明,所提出的高超声速飞行器的自适应模糊滑模控制系统能够有效抑制气动参数摄动的影响,对姿态角指令有较好的跟踪性能.     

带有干扰观测器的高超声速飞行器滑模控制

针对高超声速飞行器非线性和易受干扰影响的特点,提出了带有扩张状态干扰观测器的连续滑模控制方法.在对飞行器非线性模型做线性化处理的基础上,设计了一种连续时间滑模控制器.该控制器在对不确定性和未知动态保持鲁棒性的基础上,消除了传统滑模中存在的抖振现象.对系统中存在的外加干扰,设计了扩张状态干扰观测器.将外加干扰作为系统的一个状态变量被估计出来,再将估计值用作滑模控制器的补偿量,进而达到消除外干扰的目的.在高超声速飞行器巡航飞行状态的基础上进行了仿真.仿真结果表明,所提出的方案能够满足控制要求.     

基于sigmoid函数的高超声速飞行器自适应姿态控制

针对高超声速飞行器无动力再入过程中具有强耦合、气动参数摄动及不确定性的非线性姿态模型,提出了飞行器姿态控制的一种非线性设计方法。首先基于时标分离原理分内外环设计非线性动态逆控制器,并利用Sigmoid函数分通道制定控制律。针对单纯使用动态逆控制鲁棒性弱的特点,引入基于扩张状态观测器(Extended State Observer,ESO)的自适应控制器对参数摄动和不确定性进行补偿,在参数拉偏和风干扰条件下仿真结果验证了设计控制器具有较强的鲁棒性。     

微型飞行器的自抗扰控制器设计

微型飞行器具有高度的非线性特性,且气动参数具有不确定性,难以建立精确的数学模型;为实现其姿态、速度、以及高度的精确鲁棒控制,基于自抗扰控制方法设计了微型飞行器速度回路和高度回路的控制器;首先建立了微型飞行器的非线性模型,然后利用扩张状态观测器对飞行器状态和气动不确定性因素进行了估计,并通过非线性反馈对模型不确定性部分和状态耦合进行补偿,实现了纵向通道的解耦控制;通过仿真对所设计的控制器进行性能验证,结果表明自抗扰控制器能够实现对微型飞行器的快速稳定控制,且不依赖于精确的飞行器数学模型,具有良好的鲁棒性。     

高超声速飞行器鲁棒自动驾驶仪设计研究

针对高超声速飞行器姿态控制问题,设计了具有鲁棒特性的自动驾驶仪;针对带有耦合特性的面对称外形高超声速飞行器的动力学模型,在存在气动参数摄动的情形下,基于数值有界不确定性描述形式,利用鲁棒控制理论和线性矩阵不等式(LMl)求解方法,设计了三通道鲁棒的自动驾驶仪控制器;最后仿真结果表明,所设计的三通道自动驾驶仪使得高超声速飞行器获得理想的动态性能和稳态品质,并对气动参数和通道间的耦合不确定性具有较强的鲁棒性.     

高超声速飞行器应用保护映射的大包线控制律

针对高超声速飞行器模型具有高度非线性和易变的动态特性,应用保护映射理论提出了一种高超声速飞行器大包线控制律设计方法.首先,结合间隙度量理论建立高超声速飞行器线性变参数(linear parameter-varying,LPV)模型,然后设计控制器结构并计算初始点的控制器参数,并根据保护映射理论分析初始控制器使闭环系统稳定的参数区间,通过迭代运算自适应地获得满足性能要求的控制器参数集合.仿真结果表明,建立的LPV模型具有良好的精确度;所设计的大包线控制律能够满足高超声速飞行器的性能要求,并且保证系统在飞行域内全局稳定.     

基于非线性干扰观测器的高超声速飞行器滑模反演控制

针对高超声速飞行器非线性、强耦合和参数不确定弹性体模型,提出了一种基于非线性干扰观测器的滑模反演控制方法.将飞行器曲线拟合模型分解为速度子系统和高度相关子系统并表示为严格反馈形式,分别采用滑模和反演方法设计实际控制量与虚拟控制量.采用1阶低通滤波器获取虚拟控制量的导数,解决了传统反演控制方法"微分项膨胀"问题.基于改进滑模微分器设计了一种新型非线性干扰观测器,以此对模型不确定项进行估计和补偿.仿真结果表明,该控制器对模型不确定性和气动弹性影响具有鲁棒性,且实现了对速度和高度参考输入的稳定跟踪.     

高超声速飞行器再入姿态改进自抗扰控制

针对高超声速飞行器在无动力再入过程中具有复杂非线性、控制通道间强耦合及气动参数不确定性,增加了控制器设计的困难.通过构造连续光滑扩张状态观测器及自抗扰解耦控制技术,设计了高超声速飞行器自抗扰姿态控制器.采用构造qin函数实现了连续光滑扩展状态观测器的设计,可避免自抗扰控制器应用过程中的高频颤振现象.通过自抗扰解耦控制技术设计了姿态角及姿态角速度联合控制器,无需基于奇异摄动理论分为内外环控制,解决了设计飞行器内外环控制器时需忽略内环对外环的耦合影响问题,并且解决了难于获取精确的飞行器被控模型及精确的气动参数、摄动界限等问题.仿真结果表明了改进方法的有效性.     

Landing Auto‐Pilots for Aircraft Motion in Longitudinal Plane using Adaptive Control Laws Based on Neural Networks and Dynamic Inversion

This paper presents two new automatic landing systems (ALSs) for aircraft motion in longitudinal plane; the model of the landing geometry determines the flight trajectory and the aircraft calculated altitude; the flight trajectory during landing consists of two parts: the glide slope and the flare. Both designed ALSs have an adaptive system (ACS) for the aircraft output's control; for the first ALS, the output vector consists of the flying altitude and the longitudinal velocity, while, for the second ALS, the output variables are the pitch angle and the longitudinal velocity of aircraft. The second variant of ALS also contains an altitude controller providing the calculated pitch angle. The calculated altitude (for the first ALS), the calculated pitch angle (for the second ALS), and the desired flight velocity are provided to the ACS by means of a block consisting of two reference models. ACS is based on the dynamic inversion concept and contains an adaptive controller which includes a linear dynamic compensator, a state observer, a neural network, and a Pseudo Control Hedging block. The paper is focused both on the design of the two ALSs and on their complex software implementation and validation.     

基于动态面的高超声速飞行器模糊自适应非线性控制

针对高超声速飞行器模型非线性、多变量和参数不确定特性, 并考虑控制增益变化可能导致控制奇异值问 题, 提出一种基于动态面的模糊自适应非线性控制方法. 根据动态面和动态逆策略, 分别设计了高度和速度跟踪控制 器. 利用模糊自适应方法在线逼近不确定函数项, 并采用Nussbaum 增益技术抑制虚拟控制增益不确定影响, 以减少 在线学习量, 保证系统的半全局一致最终有界性. 仿真结果表明, 所提出的方法可实现飞行器对高度和速度的准确跟 踪控制.

     

飞机操纵面损伤的自适应容错控制设计

针对飞控系统实时控制和高可靠性的要求,提出一种飞控系统多操纵面损伤的在线容错控制算法.首先建立包含各种常见故障的操纵面参数仿真模型和故障注入仿真机制,其次由于故障的随机性,设计多个并行的在线观测器,对应于每个观测器模型建立一个基于特征结构配置的控制器.最后根据多个观测器和相应的控制器可完成系统在线故障隔离与重构.应用某型飞机横侧向控制系统进行仿真,得到了预期的效果.此方法设计简单合理,适于工程应用.     

基于多目标控制的变体飞行器切换线性变参数控制器

变体飞行器在不同的机体构型有不同的控制目标,针对变体飞行器的多目标控制问题,提出了一种切换线性变参数(linear parameter varying,LPV)控制方法.该方法根据变体飞行器的任务模式及性能指标要求把后掠角变化范围分成不同的区域,在不同的区域根据相应的控制目标求出系统满足控制性能指标的有解条件及相应的LPV控制器,并用参数依赖多Lyapunov函数和公共Lyapunov函数两种方法保证变体过程的稳定性及快速性.仿真结果表明:在飞行器参数大范围快速变化的情况下,运用本文设计的控制器具有良好的操纵性能.     

An experimental study of pilots' control characteristics for flight of an STOL aircraft in backside of drag curve at approach and landing.

In general, most vehicles can be modelled by a multi-variable system which has interactive variables. It can be clearly shown that there is an interactive response in an aircraft's velocity and altitude obtained by stick control and/or throttle control. In particular, if the flight conditions fall to backside of drag curve in the flight of an STOL aircraft at approach and landing then the ratio of drag variation to velocity change has a negative value (delta D/delta u less than 0) and the system of motion presents a non-minimum phase. Therefore, the interaction between velocity and altitude response becomes so complicated that it affects to pilot's control actions and it may be difficult to control the STOL aircraft at approach and landing. In this paper, experimental results of a pilot's ability to control the STOL aircraft are presented for a multi-variable manual control system using a fixed ground base simulator and the pilot's control ability is discussed for the flight of an STOL aircraft at backside of drag curve at approach and landing.     

Combining fuzzy, PID and regulation control for an autonomous mini-helicopter

This paper reports on the synthesis of different flight controllers for an X-Cell mini-helicopter. They are developed on the basis of the most realistic mathematical model currently available. Two hybrid intelligent control systems, combining computational intelligence methodologies with other control techniques, are investigated. For both systems, Mamdani-type fuzzy controllers determine the set points for altitude/attitude control. These fuzzy controllers are designed using a simple rule base. The first scheme consists of conventional SISO PID controllers for z-position and roll, pitch and yaw angles. In the second scheme, two of the previous PID controllers are used for roll and pitch, and a linear regulator is added to control altitude and yaw angle. These control schemes mimic the action of an expert pilot. The designed controllers are tested via simulations. It is shown that the designed controllers exhibit good performance for hover flight and control positioning at slow speed.     

An experimental study of pilots' control characteristics for flight of an STOL aircraft in backside of drag curve at approach and landing

Abstract

In general, most vehicles can be modelled by a multi-variable system which has interactive variables. It can be clearly shown that there is an interactive response in an aircraft's velocity and altitude obtained by stick control and/or throttle control. In particular, if the flight conditions fall to backside of drag curve in the flight of an STOL aircraft at approach and landing then the ratio of drag variation to velocity change has a negative value (ΔD/Δu<0) and the system of motion presents a non-minimum phase. Therefore, the interaction between velocity and altitude response becomes so complicated that it affects to pilot's control actions and it may be difficult to control the STOL aircraft at approach and landing.

In this paper, experimental results of a pilot's ability to control the STOL aircraft are presented for a multi-variable manual control system using a fixed ground base simulator and the pilot's control ability is discussed for the flight of an STOL aircraft at backside of drag curve at approach and landing.     

Neural-fuzzy scheduling of H robust controllers for a high performance fighter aircraft under a Herbst-like manoeuvre

This paper presents a flight control system design method witha neural-fuzzy gain-scheduling algorithm with learning capability for a high performance fighter aircraft undergoing a high angle of attack velocity vector roll manoeuvre. This manoeuvre is similar to the Herbst manoeuvre, hence also called a Herbst-like manoeuvre. Two linear H robust controllers are designed by using the mu -synthesis method at two trim conditions that cover the whole dynamic range of this manoeuvre. Then a scheduling technique is proposed, using the neural-fuzzy concept, together witha dynamic back propagation algorithm for its training. Simulation results, using a recently developed non-linear six-degree-of-freedom aircraft simulation package, demonstrate that the neural-fuzzy scheduler can be trained by using the dynamic back propagation algorithm to achieve better closed-loop tracking performance, and the proposed neural-fuzzy scheduled flight control system gives satisfactory performance inexecuting this Herbst-like manoeuvre.     

低空导航吊舱地形跟随算法设计与仿真

导航吊舱是战斗机超低空突袭作战时的必备外挂设备,可保证飞机超低空飞行的安全;为了提供一种适应作战环境的方法,提高飞机有效低空突防能力,设计了低空导航吊舱地形跟随算法;通过建立雷达工作模型与无线电工作模型分别得到飞行控制角指令,然后对角指令进行数据融合得到最终适合飞机进行地形跟随飞行的指令;在随机地图上利用MATLAB对该算法进行了仿真,结果表明该算法很好地实现了飞机飞行高度为150 m的地形跟随和突防任务。     

最优控制L1自适应在重装空投纵向控制器设计中的应用

为保证空投过程中载机的姿态和高度稳定,采用结合最优控制的L_1自适应控制方法设计了飞机纵向控制器.利用最优控制产生线性控制信号并确定匹配参考模型,在此基础上将系统非线性转化为L_1自适应控制结构中的匹配和非匹配不确定性实现姿态保持,结合外环PID高度控制器完成整个飞控系统的设计.仿真验证了控制器的强鲁棒性,可以抑制高自适应增益下输入信号中的高频抖振.