Optimal Preview Control for Automatic Carrier Landing System of Carrier-Based Aircraft with Air Wake

Carrier-based aircraft carrier landing is a special kind of tracking control problem and not suitable for classical control methods,which may miss the desired performance or result in overdesign.Therefore,we present an optimal preview control for automatic carrier landing system(ACLS)by using state information of system,as well as future reference information,which can avoid the shortcomings of classical control methods.Since the flight performance of carrier-based aircraft is disturbed by air wake when the aircraft flies near the area of carrier stern,we design a disturbance rejection strategy to ensure that aircraft track the glide path with high precision and robustness.Further,carrier-based aircraft is a complex nonlinear system.However,the nonlinear model of carrier-based aircraft can be linearized at equilibrium landing state and decoupled into the longitudinal model and the lateral model.Therefore,an optimal preview control system is designed.The simulation results of a carrier-based aircraft show that the optimal preview control system can effectively suppress air wake.Tracking accuracy of optimal preview controller is higher than that of the proportional integral differential(PID)control system.

Guidance and Control Techniques of Carrier-Based Aircraft for Automatic Carrier Landing

We summarize the guidance and control techniques of automatic carrier landing for carrier-based aircraft.First,we analyze the carrier landing operations of the manned fixed-wing aircraft,unmanned fixed-wing aircraft and helicopters.Second,we look into the navigation and guidance system and the flight control methods for current different aircraft.Finally,we draw several conclusions of the development prospects for aircraft carrier landing,including the precision landing control techniques,precision approach and landing guidance techniques,and adaptive,reconfigurable and intelligent flight control techniques.

Automatic Carrier Landing Control for Unmanned Aerial Vehicles Based on Preview Control

For carrier-based unmanned aerial vehicles(UAVs),one of the important problems is the design of an automatic carrier landing system(ACLS)that would enable the UAVs to accomplish autolanding on the aircraft carrier.However,due to the movements of the flight deck with six degree-of-freedom,the autolanding becomes sophisticated.To solve this problem,an accurate and effective ACLS is developed,which is composed of an optimal preview control based flight control system and a Kalman filter based deck motion predictor.The preview control fuses the future information of the reference glide slope to improve landing precision.The reference glide slope is normally a straight line.However,the deck motion will change the position of the ideal landing point,and tracking the ideal straight glide slope may cause landing failure.Therefore,the predictive deck motion information from the deck motion predictor is used to correct the reference glide slope,which decreases the dispersion around the desired landing point.Finally,simulations are carried out to verify the performance of the designed ACLS based on a nonlinear UAV model.

H_∞ Preview Control for Automatic Carrier Landing

This paper focuses on the application of H_∞preview control in automatic carrier landing system(ACLS)for carrier-based aircraft.Due to the mutual movement between aircraft and carrier,the landing process becomes considerably more challenging compared to a conventional runway landing.ACLS systems mitigate this by predicting deck motion and generating ideal glide slope path for tracking.Although,this predicted glide slope information is available in advance,conventional control structures are still unable to use this future information.H_∞preview control has the ability to utilize this future information for improving tracking response and disturbance rejection.The process of incorporating preview information into ACLS framework and synthesizing the H_∞preview controller is presented.The methodology is verified using the example of F/A-18 automatic carrier landing problem and results are presented.

Iterative Model Predictive Control for Automatic Carrier Landing of Carrier-Based Aircrafts Under Complex Surroundings and Constraints

This paper considers the automatic carrier landing problem of carrier-based aircrafts subjected to constraints,deck motion,measurement noises,and unknown disturbances.The iterative model predictive control(MPC)strategy with constraints is proposed for automatic landing control of the aircraft.First,the long short-term memory(LSTM)neural network is used to calculate the adaptive reference trajectories of the aircraft.Then the Sage-Husa adaptive Kalman filter and the disturbance observer are introduced to design the composite compensator.Second,an iterative optimization algorithm is presented to fast solve the receding horizon optimal control problem of MPC based on the Lagrange’s theory.Moreover,some sufficient conditions are derived to guarantee the stability of the landing system in a closed loop with the MPC.Finally,the simulation results of F/A-18A aircraft show that compared with the conventional MPC,the presented MPC strategy improves the computational efficiency by nearly 56%and satisfies the control performance requirements of carrier landing.

Automatic landing system using neural networks and radio-technical subsystems

The paper focuses on the design of a new automatic landing system（ALS） in longitudinal plane; the new ALS controls the aircraft trajectory and longitudinal velocity. Aircraft control is achieved by means of a proportional-integral（PI） controller and the instrumental landing system– the first phase of landing（the glide slope） and a proportional-integral-derivative（PID） controller together with a radio-altimeter – the second phase of landing（the flare）; both controllers modify the reference model associated with aircraft pitch angle. The control of the pitch angle and longitudinal velocity is performed by a neural network adaptive control system, based on the dynamic inversion concept, having the following as components： a linear dynamic compensator, a linear observer, reference models, and a Pseudo control hedging（PCH） block. The theoretical results are software implemented and validated by complex numerical simulations; compared with other ALSs having the same radio-technical subsystems but with conventional or fuzzy controllers for the control of aircraft pitch angle and longitudinal velocity, the architecture designed in this paper is characterized by much smaller overshoots and stationary errors.

不同海况条件下舰载无人机着舰安全分析

针对无人机上舰的使用需求,本文对舰载无人机着舰开展了系统的研究。建立了机-舰-环境综合模型和舰载无人机全自动着舰引导控制系统;基于建立的舰载无人机着舰综合模型对不同海况下的着舰过程进行仿真分析,研究不同海况条件以及航母不同航速和遭遇角对着舰安全的影响。仿真研究表明:在复杂海况下,航母可通过适当提高航速以获得更高的着舰成功率,但过高的航速会导致舰尾流扰动加剧,使得着舰成功率显著下降;通过对仿真结果进行统计分析,给出了不同海况下的着舰安全范围,为无人机着舰辅助决策提供参考。

航母舰载无人机全自动着舰技术特点分析

全自动着舰技术是无人机上舰必须解决的“使能”技术。2013年,美军已完成X-47B无人机验证机在航母上的全自动着舰试验验证,为其发展MQ-25A“黄貂鱼”航母舰载无人机装备奠定了良好的技术基础。在梳理飞机着陆与着舰差异的基础上,给出航母舰载无人机全自动着舰的通用流程;从地位作用、工作范围、系统构架、系统要求、实现手段以及关键技术支撑等角度,对比有人机重点分析了航母舰载无人机全自动着舰的特点,为后续关键技术研究和武器装备建设发展提供参考。

基于神经核网络高斯过程回归的甲板运动预测

甲板运动预测与补偿是舰载机自动着舰的关键技术之一。传统甲板运动预测方法依赖于运动建模的准确性和参数调整,面临复杂海况、不同舰型、航态变化时具有适应性差、预测时长短、结果可靠性低等问题。提出一种基于神经核网络高斯过程回归(NKN-GPR)的甲板运动预测模型,使用神经核网络(NKN)实现高斯过程回归(GPR)模型自动复合核构造,有效改善基于规则库自动核搜索(ACKS)算法依赖人工先验知识的不足。以正弦波组合模型和功率谱模型构造仿真数据,对NKN-GPR模型和基于最小二乘法的自回归(AR)模型进行对比仿真验证,仿真结果表明,NKN-GPR模型在运动预测精度、平滑性、预测时长等方面具有显著优势,证明了所提算法的有效性,可为舰载机自动安全着舰提供理论支撑。

MAGIC CARPET着舰控制的稳定性

魔毯(MAGIC CARPET)是美国最近几年非常成功的舰载机着舰控制技术,是未来主要的着舰方式。研究了MAGIC CARPET控制的稳定性。首先,分析MAGIC CARPET着舰和常规着舰的控制结构。然后,进行人在环实时仿真实验,实验有MAGIC CARPET控制和常规控制两组,每组中又分油门不动和自动油门接通两种情况。实验显示稳定能力(轨迹稳定性、轨迹可控性、速度稳定性、迎角稳定性),从高到低的排序是:MAGIC CARPET控制(正常有自动油门情况)?MAGIC CARPET控制(油门不动情况)?常规控制(正常有自动油门)?常规控制(油门不动情况),可见MAGIC CARPET的稳定性能非常优秀。最后,从D-V曲线、信号流图、复域等多角度,综合分析了MAGIC CARPET控制和常规控制的稳定性机理。研究结果可为飞机着舰和直接力控制等方面提供参考。

综合直接侧力控制着舰

提出了一种新的着舰控制方法,即综合直接侧力控制着舰。首次将直接侧力应用到着舰研究上,并将美军MAGIC CARPET着舰控制的纵向控制理念拓展到侧向控制上,对侧向直接力舵面和侧向常规舵面进行综合控制设计,实现侧向三通道解耦。在直接侧力通道上设计了横向轨迹增量控制,让横向杆位移直接正比于横向对中漂移速率。对HUD显示符号进行改进,使飞行员更直观地观察着舰态势。设计着舰飞行模拟环境,实时模拟飞行员操纵。模拟结果显示:飞行员能如MAGIC CARPET纵向控制一样,以“一杆操纵”策略很简便地完成对中修正,同时能很好地跟踪侧向甲板运动和抵抗侧风干扰,且整个过程航向角和滚转角基本不变。相对于常规着舰,该方法大大降低了飞行员操纵负担,且提高了着舰性能。

基于线性自抗扰控制的纵向舰载机直接升力全自动着舰控制

舰载机的最终着舰过程受到强烈的舰尾流的干扰,为了抑制舰尾流扰动,本文提出一种基于径向基函数神经网络(radial basis functions neural network,RBFNN)结合线性自抗扰控制(liner active disturbance rejection control,LADRC)的创新设计方法,确保舰载机直接升力控制自动着舰系统的鲁棒性。LADRC将阵风扰动和系统不确定项作为总扰动,通过线性扩展状态观测器(liner extended state observer,LESO)对总扰动进行估计,并通过线性反馈控制律进行补偿,然后根据系统状态利用RBFNN在线调整LADRC控制器的参数,并构建Lyapunov函数以证明闭环系统的稳定性。舰载机跟踪理想下滑道的仿真结果表明,RBF-LADRC的抗干扰性、鲁棒性和跟踪精度均优于与之对比的控制方法。

基于改进灰狼优化算法的舰载机着舰调度

针对第一类着舰模式下的舰载机着舰调度问题进行了研究,建立着舰调度模型,以最小化加权着舰延误时间和、着舰完成时间为优化目标,考虑舰载机战损程度、剩余燃油量的影响。为减轻人工调度的负担,提出一种改进灰狼优化(IGWO)算法对调度模型进行优化求解,在灰狼优化(GWO)算法的基础上,改进算法选择历史最优解灰狼个体为α狼,引入混沌算子,设置算法参数更新控制变量,以应对GWO算法后期收敛速度慢、可能陷入局部最优解的缺点。通过不同规模着舰调度案例仿真和算法对比,验证了IGWO算法的有效性,所提算法在30、60、90机规模着舰调度案例中的优化效果均优于对比算法,证明其具备一定工程应用价值。

基于模型预测控制算法的精确着舰控制方法

针对舰载机着舰过程中的航母运动、舰尾流扰动等影响,提出一种基于模型预测控制-线性二次型高斯(MPC-LQG)算法的精确着舰控制方法,开展飞机纵向通道的精确着舰控制研究。对飞机纵向动力学、舰尾流、航母运动、轨迹跟踪等,进行建模和分析。对MPC-LQG算法进行融合,以实现轨迹跟踪控制,核心思想是:模型预测控制进行航母运动补偿;设计全维状态观测,实现全状态反馈,以实现最优着舰控制。对不同的着舰情况和初始条件进行算法仿真,并与其他算法进行仿真比较。仿真结果表明,所提方法的轨迹跟踪效果很好,高度偏差0.1~0.2 m;相比传统着舰控制,所提方法动态响应快、着舰精度高。

陆基工厂化水产养殖池自动清洗机器人设计与试验

针对现阶段陆基工厂化水产养殖池人工清洗存在劳动强度大、效率低等问题,设计基于轨道移动、具有越池清洗功能的养殖池自动清洗机器人。该机器人由移动机构、清洗机构和控制系统等组成。移动机构沿养殖池上方导轨前后、左右移动,清洗机构通过旋转和上下伸缩装置完成养殖池池底和池壁清洗,控制系统通过STM32F103单片机实现对清洗机器人的精准控制。通过建立全覆盖栅格地图的方法进行路径规划,并采用最短切线、野火法等算法实现自动避障,并对机器人进行测试。结果表明:刷盘转速和驱动速度最优组合方式为刷盘转速600 r/min,驱动速度0.2 m/s。

智能集成式轻小型落地抱杆的液压绞磨自动化控制

液压绞磨在铁塔组立施工中起重要作用,为此该文提出一种智能集成式轻小型落地抱杆的液压绞磨自动化控制方法。以实际牵引速度与期望牵引速度以及两者的偏差作为输入值,通过BP神经网络运算得出PID最优组合的控制参数,以实际牵引力和目标牵引力的偏差以及偏差变化率作为模糊控制的输入,通过模糊PID的计算,得到PID精确的更新参数;将两方面输出控制结果作用于执行器,进行液压绞磨参数调节,实现牵引速度和牵引力控制。实验结果表明,该方法控制的液压绞磨性能参数与目标参数吻合性高,动态性能平稳,在平衡方面控制效果也很显著。

舰载机着舰侧向轨迹增量控制

针对舰载机着舰侧向控制难度较大的问题,借鉴美国海军的“魔毯”(MAGIC CARPET)着舰的先进理念,提出了1种新的着舰控制方法,即侧向轨迹增量控制。首先,分别从理论上分析了侧向常规控制、侧向轨迹增量控制的控制结构和着舰性能;然后,对HUD显示符号进行改进;最后,通过实时仿真,比较了这2种方法的着舰控制效果。结果显示,着舰侧向轨迹增量控制具有3个优点:1)简易,降低了飞行员的操纵频次和负担;2)直观,着舰侧向操纵更直观,侧向杆量与飞机侧偏修正速率成正比例,而且当横杆回中时飞机能自动跟踪跑道中心线的横向漂移;3)鲁棒,显著提高了对侧风和舰尾流的抑制能力,即使在飞行员不操纵的情况下,飞机也能迅速反应和抑制风干扰。因此,建议在着舰工程中采用侧向轨迹增量控制。

舰尾流下自动着舰进场动力补偿的仿真与分析

着舰过程中舰尾流影响舰载机高度和速度,造成着舰偏差,甚至会导致复飞。针对舰尾流造成舰载机自动着舰落点精度差的问题,本文首先介绍传统速度恒定动力补偿、迎角恒定动力补偿2种方案,并对迎角恒定动力补偿控制方案进行改进,减小纵向高度通道与速度通道的耦合程度,降低舰尾流对下滑道控制精度的影响。通过数学仿真对比了3种方案抑制舰尾流稳态分量的效果。仿真结果表明,改进的迎角恒定动力补偿方案能够有效抑制舰尾流垂直分量的影响,并能够改善舰尾流水平分量的影响。

基于视觉导引的自主着舰仿真系统设计与实现

针对舰载机着舰场景的仿真应用需求,设计并实现了一种基于视觉导引的自主着舰仿真系统。根据实际场景对自主着舰仿真系统进行需求分析并梳理出软件架构;研究了航母、舰载机、可见光和红外相机等模型的仿真关键技术;基于Unigine和仿真模型实现了系统的核心功能。应用结果表明,方案能够满足自主着舰仿真的视景仿真要求,达到了更加真实的视景仿真效果。

基于自适应固定时间的直接升力着舰容错控制

针对执行器效益损失故障、偏移故障和舰尾流扰动,提出了一种直接升力作用下的自适应固定时间容错控制方法。首先,建立了一种新的含襟翼的舰载机精确反馈线性化模型,并基于新的固定时间稳定性定理,对直接升力模态设计了滑模控制器,提升了系统的收敛速度和着舰精度;然后,引入非线性微分方程形式的自适应更新律,在线估计故障因子的最小值和复合扰动上界值,补偿故障和扰动的影响,基于李雅普诺夫方法证明了闭环系统的固定时间收敛特性;最后,与其他方法对比仿真的结果证明了所设计方法的有效性和优越性。