基于多模型方法的全包络鲁棒飞行控制器设计

利用新一代歼击机不同平衡点的多个非线性子模型对其机动飞行的全包络模型进行逼近。对于每一个子模型,设计相应的动态逆控制器,应用模糊神经网络产生控制器切换决策,实现不同飞行状态下不同模型控制器之间的相互切换。同时为了提高多模型飞行控制效果,对各模型控制器的输入及输出采样并作为神经网络的学习样本,形成一个全包络内的多模型统一神经网络控制器。最后通过歼击机的大迎角机动仿真来验证所设计的基于多模型的统一神经网络控制器的有效性,仿真结果表明所设计的统一神经网络控制器是有效的。     

Digital Control of High Performance Aircraft Using Adaptive Estimation Techniques

Since the early 1960's, a rapid advance in signal processing, including filtering and estimation techniques, has been evident. In contrast, applied feedback control, particularly for aircraft, is currently based on technology available prior to 1960, i. e., primarily either constant gain feedback or at most a standard gain-scheduling. In this paper, an adaptive signal processing algorithm is joined with gain-scheduling to produce an effective scheme for controlling the dynamics of high performance aircraft. A technique is presented for a reduced-order model (the longitudinal dynamics) of a high performance short-takeoff-and-landing (STOL) aircraft. The actual controller views the nonlinear behavior of the aircraft as being equivalent to a randomly switching sequence of linear models taken from a preliminary piecewise-linear fit of the system nonlinearities. The adaptive nature of the estimator is necessary to select the proper sequence of linear models along the flight trajectory. From the analysis of the reduced-order model the nonlinear behavior has been found to be well approximated by assuming an effective switching of the linear models at random times, the durations of which reflect the motion of the aircraft in response to pilot commands.     

Ground maneuver for front-wheel drive aircraft via deep reinforcement learning

The maneuvering time on the ground accounts for 10%–30% of their flight time, and it always exceeds 50% for short-haul aircraft when the ground traffic is congested. Aircraft also contribute significantly to emissions, fuel burn, and noise when taxiing on the ground at airports. There is an urgent need to reduce aircraft taxiing time on the ground. However, it is too expensive for airports and aircraft carriers to build and maintain more runways, and it is space-limited to tow the aircraft fast using tractors. Autonomous drive capability is currently the best solution for aircraft, which can save the maneuver time for aircraft. An idea is proposed that the wheels are driven by APU-powered (auxiliary power unit) motors, APU is working on its efficient point; consequently, the emissions, fuel burn, and noise will be reduced significantly. For Front-wheel drive aircraft, the front wheel must provide longitudinal force to tow the plane forward and lateral force to help the aircraft make a turn. Forward traction effects the aircraft’s maximum turning ability, which is difficult to be modeled to guide the controller design. Deep reinforcement learning provides a powerful tool to help us design controllers for black-box models; however, the models of related works are always simplified, fixed, or not easily modified, but that is what we care about most. Only with complex models can the trained controller be intelligent. High-fidelity models that can easily modified are necessary for aircraft ground maneuver controller design. This paper focuses on the maneuvering problem of front-wheel drive aircraft, a high-fidelity aircraft taxiing dynamic model is established, including the 6-DOF airframe, landing gears, and nonlinear tire force model. A deep reinforcement learning based controller was designed to improve the maneuver performance of front-wheel drive aircraft. It is proved that in some conditions, the DRL based controller outperformed conventional look-ahead controllers.     

Design for aircraft engine multi-objective controllers with switching characteristics

The aircraft engine multi-loop control system is described and the switching control theory is introduced to solve the regulating and protecting control problems in this paper. The aircraft engine multi-loop control system is firstly described and the control problems are formulated. Secondly, the theory of the smooth switching control is devoted and a new extended scheme for the smooth switching of a switched control system is introduced. Then, for the key technologies of aero-engines switching control, a design algorithm is presented which can determine which candidate controller should be put in feedback with the plant to achieve a desired performance and the procedure to design the aircraft engine multi-loop control system is detailed. The switching performance objectives and the switching scheme are given and a family of PID controllers and compensators is designed. The simulation shows that using the switching control design method can not only improve the dynamic performance of the aircraft engine control system and reduce the switching times, but also guarantee the stability in some peculiar occasions.     

Model reference adaptive control with smooth switching scheme for piecewise linear systems and its application in turbofan engine control

A model reference adaptive control (MRAC) with smooth switching scheme was proposed for piecewise linear systems, and the method was utilized in turbofan engine control to avoid the discontinuity of control input. In this scheme, each sub-region of the operating envelope had its own MRAC controller, and smooth indicator function based smooth switching scheme was introduced to switch multiple controllers smoothly at the boundary of adjacent sub-regions. The Lyapunov stability analysis indicated that the proposed smooth switching scheme can guarantee the convergence of the closed-loop system during the controllers switching. The tracking error system was converted into a switched system to analyze the global stability of the closed-loop system. The advantage of the method was that the chattering of system output and instability caused by asynchronous switching can be eliminated. The simulation illustrates the effectiveness of the proposed control scheme in comparison with the existing MRAC controller with gain scheduling for turbofan engine.      

Evaluation on novel architecture for harmonizing manual and automatic flight controls under atmospheric turbulence

Pilot uncertainty in aircraft response under automatic flight control has triggered aircraft accidents/incidents in the past. This uncertainty compels a pilot to disengage autopilot and switch to manual control. However, the decision to disengage autopilot and when to do it can be difficult: especially if there is not enough time to monitor the cockpit displays, for instance while countering atmospheric turbulence. Against this background, we proposed the “human as a control module” architecture for harmonizing pilot and autopilot controls. The architecture blends pilot maneuver with autopilot control instead of switching between them when simultaneous inputs are given to the aircraft. By automatically adjusting pilot and autopilot control inputs, the architecture avoids overlaps of both control authorities and helps to circumvent the effect of conflicting actions. This paper applies the architecture to the situations of past aircraft incidents which had been caused by the transfer from autopilot control to pilot maneuver after encountering atmospheric turbulence. The effectiveness of the architecture is evaluated via simulation study for the specific incident examples. Furthermore, this paper extends the architecture with an Extended Kalman Filter (EKF) based observer and evaluates its robustness under errors in wind estimation.     

基于Kalman滤波的变体飞行器T-S模糊控制

针对变体飞行器的跟踪控制问题,提出了一种基于Kalman滤波的T-S模糊控制方法。考虑飞行器系统状态不可测,引入惯导数据作为辅助信息,利用Kalman滤波算法融合飞控信息与惯导信息实现状态估计。由于变体飞行器在不同变形结构下气动特性变化较大,为便于控制器设计,采用小扰动线性化方法得到飞行器在不同平衡点处的局部线性模型,并通过状态反馈方法设计局部控制器,局部线性模型和局部控制器通过模糊集和模糊规则聚合成一个连续光滑的全局T-S模糊模型和T-S模糊控制器。通过综合Kalman滤波器与T-S模糊控制器得到一个基于Kalman滤波的T-S模糊控制器。仿真结果表明,该控制器在变形过程中能够实现状态估计,保证飞机的跟踪性能。     

A systematic method of smooth switching LPV controllers design for a morphing aircraft

This paper is concerned with a systematic method of smooth switching linear parametervarying(LPV) controllers design for a morphing aircraft with a variable wing sweep angle. The morphing aircraft is modeled as an LPV system, whose scheduling parameter is the variation rate of the wing sweep angle. By dividing the scheduling parameter set into subsets with overlaps, output feedback controllers which consider smooth switching are designed and the controllers in overlapped subsets are interpolated from two adjacent subsets. A switching law without constraint on the average dwell time is obtained which makes the conclusion less conservative. Furthermore,a systematic algorithm is developed to improve the efficiency of the controllers design process. The parameter set is divided into the fewest subsets on the premise that the closed-loop system has a desired performance. Simulation results demonstrate the effectiveness of this approach.     

Multiobjective Target Feedback Loop / Loop Transfer Recovery (TFL/LTR) design with application to aircraft lateral control in high incidence regime

Target Feedback Loop / Loop Transfer Recovery (TFL/LTR) synthesis and multiobjective optimization are combined to design robust and well performing controllers in a most general sense. A TFL/LTR synthesis based on quadratic stabilization is used to efficiently synthesize robustly stabilizing controllers. Multiobjective optimization is used to tune synthesis parameters for which the TFL/LTR controller yields good performance in addition to robust stability. The technique is demonstrated in the design of a lateral controller for a high performance aircraft in high incidence regime.     

Adaptive finite-time backstepping control for attitude tracking of spacecraft based on rotation matrix

This paper investigates two finite-time controllers for attitude control of spacecraft based on rotation matrix by an adaptive backstepping method. Rotation matrix can overcome the draw- backs of unwinding which makes a spacecraft perform a large-angle maneuver when a small-angle maneuver in the opposite rotational direction is sufficient to achieve the objective, With the use of adaptive control, the first robust finite-time controller is continuous without a chattering phenom- enon. The second robust finite-time controller can compensate external disturbances with unknown bounds. Theoretical analysis shows that both controllers can make a spacecraft following a time-varying reference attitude signal in finite time and guarantee the stability of the overall closed-loop system. Numerical simulations are presented to demonstrate the effectiveness of the proposed control schemes.     

Reconfigurable flight control via multiple model adaptive controlmethods

An aircraft flight control system with reconfigurable capabilities is considered. A multiple model adaptive controller (MMAC) is shown to provide effective reconfigurability when subjected to single and double failures of sensors and/or actuators. A command generator tracker/proportional-plus-integral/Kalman filter (CGT/PI/KF) form of controller was chosen for each of the elemental controllers within the MMAC algorithm and each was designed via LQG synthesis to provide desirable vehicle behavior for a particular failure status of sensors and actuators. The MMAC performance is enhanced by an alternate computation of the MMAC hypothesis probabilities, use of maximum a posteriori probability (MAP) versus Bayesian form of the MAC (or a modified combination of both), and reduction of identification ambiguities through scalar residual monitoring for the case of sensor failures     

Reduced-dimensional MPC controller for direct thrust control

With the development of the aircraft gas turbine engine, a control system should be able to achieve effective thrust control to gain better operability. The main contribution of this paper is to develop a novel direct thrust control approach based on an improved model predictive control method through a strategy that reduces the dimension of control sequence. It can not only achieve normal direct thrust control tasks but also maximize the thrust level within the safe operation boundaries. Only t...     

三轴式无人旋翼飞行器及自适应飞行控制系统设计

设计了一种操控简便的三轴式无人旋翼飞行器,由三组共轴双旋翼组成,各旋翼由直流电机直接驱动,只需调节各电机转速就能控制旋翼飞行器运动姿态和轨迹。为使三轴式无人旋翼飞行器飞行控制系统设计得到有效验证,研究了旋翼飞行器的飞行动力学非线性建模,运用叶素动量理论建立了共轴双旋翼变转速旋翼载荷计算方法,分析了旋翼入流分布对共轴双旋翼气动载荷模型的影响,通过试验验证了共轴双旋翼气动载荷计算模型的正确性。由于旋翼飞行器飞行动力学模型的非线性及未建模动力学的影响,难于建立非常精确的数学模型,给飞行控制系统设计带来了挑战。本文根据旋翼飞行器飞行动力学非线性模型推导出了旋转动力学模型逆和平移动力学模型逆控制器,利用神经网络在线自适应修正模型逆误差,采用线性PD或PI控制器调节指令跟踪误差,应用由向心回转和垂直上升组合的机动科目进行了仿真验证,给出了具有外界阵风干扰模拟的仿真结果,表明所设计的飞行控制系统具有自适应性和鲁棒性,能实现精确的轨迹跟踪控制。     

多模型切换控制及其在BTT导弹设计中的应用

研究了一类可以抑制切换时刻输出跳跃的多模型切换控制器的设计问题。基于参数化特征结构配置结果及模型跟踪方法,设计了满足输出跟踪性能并使多模型系统中各闭环子系统渐近稳定的多模型切换控制律集合。充分利用参数化特征结构配置方法提供的全部自由度,协调选取各子系统控制律中的参数来抑制切换时刻的输出跳跃。将本文提出的方法应用到某型倾斜转弯导弹自动驾驶仪设计中,仿真结果表明导弹的输出过载迅速准确跟踪制导指令,并且切换抖动得到有效抑制。     

模糊复合控制在飞机除冰车加热系统中的应用研究

针对新型飞机除冰车加热系统的大惯性、纯滞后、非线性和模型不确定性等特点，提出了一种新的模糊复合控制方法。该方法将基于模糊规则切换的Fuzzy—PID双模控制与参数自整定模糊控制相结合，一方面利用基于模糊规则切换的Fuzzy—PID双模控制器增强系统的鲁棒性和抗干扰性，另一方面利用参数自整定模糊控制器加快系统的响应速度。理论分析和仿真结果表明，所设计的模糊复合控制方法能很好地适应飞机除冰车加热系统数学模型的大幅度变化，具有很大的实用价值。     

基于混合灵敏度的航空发动机切换控制系统设计

针对航空发动机工作安全边界,提出了一种基于切换控制的航空发动机控制系统设计方法.给出了切换控制策略的设计思路及切换稳定性的条件.给出基于混合灵敏度的航空发动机多回路切换鲁棒控制器设计方法,并构造了线性矩阵不等式.通过基于计算得到的控制器参数仿真表明,采用该切换方式相比于Min/Max切换方式消除了积分饱和在切换中延迟影响,提高发动机的动态响应能力及鲁棒性,同时可以保证切换的稳定性.      

基于动态嵌套网格的飞行器外挂物投放的数值模拟

运用Euler方程和六自由度动力学方程数值模拟了外挂物投放的气动特性与运行姿态和轨迹。为了模拟外挂物从飞行器分离后的绕流特性和相对运动，采用了动态嵌套网格技术，并发展了一种洞边界建立和外边点的插值单元搜寻蛇行法，提高了计算效率。通过算例，证明了本文方法的有效性和合理性。     

基于矫正广义走廊的电动倾转旋翼机模态转换

研究了基于矫正广义走廊和在线增益调度方法的电动倾转旋翼机模态转换控制问题。针对传统配平方法导致模态转换过程中时变动态特征被忽略的不足,提出一种新的两步法配平策略,即矫正配平工作点,并获得矫正广义走廊,以减小系统实际运行状态与配平工作点的偏离程度,进而改善增益调度方法的控制效果。传统增益调度方法控制器设计工作量较大,针对该问题设计了在线增益调度算法,有效避免了拟合过程。对某小型电动倾转旋翼无人机（UAV）的仿真表明,基于所提方法使得倾转旋翼机平稳、快速地完成模态转换过程;实验数据进一步表明,矫正后广义走廊相比于矫正前可将对过渡走廊的平均跟踪误差显著减小。     

高超声速飞行器大包线切换LPV控制方法

高超声速飞行器飞行包线和参数变化范围大,气动参数存在较强不确定性,要求控制器能够适应大的飞行包线并具有较好的鲁棒性。针对上述问题,提出一种基于间隙度量的大包线滞后切换线性变参数(LPV)控制方法。依照时变参数将设计包线划分为若干子区域,将多胞理论和间隙度量引入控制器求解,提出了基于最优间隙度量的LPV控制方法,并利用此方法独立设计各子区域的LPV控制器,以改善控制器控制性能和鲁棒性能;利用基于重叠区域的滞后切换策略实现大包线内各子区域控制器的切换,以抑制切换面附近控制器的切换抖动,并证明了切换闭环系统的稳定性;最后以某型高超声速飞行器为对象设计了大包线滞后切换LPV控制器。仿真结果表明该方法可实现控制指令的精确跟踪,提高设计包线内LPV控制器的控制性能和鲁棒性能,并能保证切换系统的稳定性。     

Non-fragile switched control for morphing aircraft with asynchronous switching

This paper deals with the problem of non-fragile linear parameter-varying (LPV) H∞ control for morphing aircraft with asynchronous switching.The switched LPV model of morphing aircraft is established by Jacobian linearization approach according to the nonlinear model.The data missing is taken into account in the link from sensors to controllers and the link from controllers to actuators,which satisfies Bernoulli distribution.The non-fragile switched LPV controllers are con structed with consideration of the uncertainties of controllers and asynchronous switching phenomenon.The parameter-dependent Lyapunov functional method and mode-dependent average dwell time (MDADT) method are combined to guarantee the stability and prescribed performance of the system.The sufficient conditions on the solvability of the problem are derived in the form of linear matrix inequalities (LMI).In order to achieve higher efficiency of the designing process,an algo rithm is applied to divide the whole set into subsets automatically.Simulation results are provided to verify the effectiveness and superiority of the method in the paper.