SWATH船纵向运动模糊自适应控制

针对SWATH船载重不同和航行过程中由升沉运动引起的水线变化对船舶运动参数的影响提出了一种模糊自适应控制策略。为保证S W A T H船纵向运动稳定性,根据李雅普诺夫稳定性定理,对纵摇控制器提出了最优控制器设计,通过选用合适的权函数,保证S W A T H船的航行性能。仿真结果表明,模糊化自适应控制系统对于不同频率下的正弦波响应和不同海况下的耐波性响应都能具有良好的控制性能,解决了船舶在不同载重、不同水线下参数变化对控制器影响的问题。     

Pilot Response in Flight and Simulated Flight

This paper describes an experiment in which an attempt was made to assess the value of two types of response, control activity and physiological activity, as indications of the effect on simulator fidelity of adding pitch motion cues. The investigation used a general-purpose research simulator and a two-seater Hunter T7 aircraft. The responses of nine experienced pilots were compared when, flying on instruments, they undertook the same flight plan under three different conditions. Namely:

flight in he Hunter T7 aircraft:

simulated flight in the simulator with pitch motion present;.

simulated flight in the same simulator without motion.     

The influence of ship motion on manual control skills

The effects of ship motion on a range of typical manual control skills were examined on the Warren Spring ship motion simulator driven in heave, pitch and roll by signals taken from the frigate H MS Avenger at 13m/s(25 knots) into a force 4 wind. The motion produced a vertical r.m.s. acceleration of 0024g, mostly between 01 and 0-3 Hz, with comparatively little pitch or roll. A task involving unsupported arm movements was seriously affected by the motion; a pursuit tracking task showed a reliable decrement although it was still performed reasonably well (pressure and free-moving tracking controls were affected equally by the motion); a digit keying task requiring ballistic hand movements was unaffected. There was no evidence that these effects were caused by sea-sickness.

The differing response to motion of the different tasks, from virtual destruction to no effect, suggests that a major benefit could come from an attempt to design the man/control interface on board ship around motion resistant tasks.     

An algorithm for trajectory prediction of flight plan based on relative motion between positions

Traditional methods for plan path prediction have low accuracy and stability. In this paper, we propose a novel approach for plan path prediction based on relative motion between positions (RMBP) by mining historical flight trajectories. A probability statistical model is introduced to model the stochastic factors during the whole flight process. The model object is the sequence of velocity vectors in the three-dimensional Earth space. First, we model the moving trend of aircraft including the speed (constant, acceleration, or deceleration), yaw (left, right, or straight), and pitch (climb, descent, or cruise) using a hidden Markov model (HMM) under the restrictions of aircraft performance parameters. Then, several Gaussian mixture models (GMMs) are used to describe the conditional distribution of each moving trend. Once the models are built, machine learning algorithms are applied to obtain the optimal parameters of the model from the historical training data. After completing the learning process, the velocity vector sequence of the flight is predicted by the proposed model under the Bayesian framework, so that we can use kinematic equations, depending on the moving patterns, to calculate the flight position at every radar acquisition cycle. To obtain higher prediction accuracy, a uniform interpolation method is used to correct the predicted position each second. Finally, a plan trajectory is concatenated by the predicted discrete points. Results of simulations with collected data demonstrate that this approach not only fulfils the goals of traditional methods, such as the prediction of fly-over time and altitude of waypoints along the planned route, but also can be used to plan a complete path for an aircraft with high accuracy. Experiments are conducted to demonstrate the superiority of this approach to some existing methods.     

Fixed‐wing attitude estimation using temporal tracking of the horizon and optical flow

A method has been developed for estimating pitch angle, roll angle, and aircraft body rates based on horizon detection and temporal tracking using a forward‐looking camera, without assistance from other sensors. Using an image processing front end, we select several lines in an image that may or may not correspond to the true horizon. The optical flow at each candidate line is calculated, which may be used to measure the body rates of the aircraft. Using an extended Kalman filter (EKF), the aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and the location of the horizon. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To test the accuracy of the algorithm, two flights were conducted, one using a highly dynamic uninhabited airborne vehicle (UAV) in clear flight conditions and the other in a human‐piloted Cessna 172 in conditions in which the horizon was partially obscured by terrain, haze, and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42 and 0.71 deg, respectively, when compared with a truth attitude source. The Cessna flight resulted in pitch and roll error standard deviations of 1.79 and 1.75 deg, respectively. The benefits of selecting and tracking the horizon using a motion model and optical flow rather than naively relying on the image processing front end are demonstrated. © 2011 Wiley Periodicals, Inc.     

基于卡尔曼滤波理论的甲板运动预估技术研究

航母在航行过程中，海浪运动将会导致舰体产生俯仰、横滚、偏航、上下起伏等运动，这将严重威胁舰载机的着舰安全。为了确保飞机在航母上成功降落，必须在着舰前使飞机运动轨迹与甲板运动同步，因此，本文研究了甲板运动预估技术，运用卡尔曼最优波波理论开发了甲板运动预估器，并提出首先对引入着舰导引系统的甲板运动信息进行预估，然后再进行超前补偿的策略。经仿真验证，甲板运动预估与补偿的结合，可以明显减小舰载机着舰误差，提高着舰精度。     

A ship motion simulation system

In this article, efficient computational models for ship motions are presented. These models are used to simulate ship movements in real time. Compared with traditional approaches, our method possesses the ability to cope with different ship shapes, engines, and sea conditions without the loss of efficiency. Based on our models, we create a ship motion simulation system for both entertainment and educational applications. Our system assists users to learn the motions of a ship encountering waves, currents, and winds. Users can adjust engine powers, rudders, and other ship facilities via a graphical user interface to create their own ship models. They can also change the environment by altering wave frequencies, wave amplitudes, wave directions, currents, and winds. Therefore, numerous combinations of ships and the environment are generated and the learning becomes more amusing. In our system, a ship is treated as a rigid body floating on the sea surface. Its motions compose of 6 degrees of freedom: pitch, heave, roll, surge, sway, and yaw. These motions are divided into two categories. The first three movements are induced by sea waves, and the last three ones are caused by propellers, rudders, currents, and winds. Based on Newton’s laws and other basic physics motion models, we deduce algorithms to compute the magnitudes of the motions. Our methods can be carried out in real time and possess high fidelity. According to ship theory, the net effects of external forces on the ship hull depend on the ship shape. Therefore, the behaviors of the ship are influenced by its shape. To enhance our physics models, we classify ships into three basic types. They are flat ships, thin ships, and slender ships. Each type of ship is associated with some predefined parameters to specify their characteristics. Users can tune ship behaviors by varying the parameters even though they have only a little knowledge of ship theory.     

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.     

基于干扰观测器的SWATH船运动非线性预测控制

针对带有海浪干扰和参数不确定的SWATH船运动控制问题, 提出基于干扰观测器的SWATH船运动非线性预测控制. 首先对SWATH船运动进行建模、参数求解和海浪干扰仿真; 然后根据运动模型设计非线性预测控制律, 对SWATH 船升沉和纵摇进行控制, 同时利用干扰观测器对海浪干扰进行观测, 并从理论上证明了所设计的控制器可以保证SWATH 船运动的稳定性. 仿真结果表明, 所设计的控制器提高了SWATH船运动控制效果, 且能对海浪干扰进行抑制.

     

基于微分几何反馈线性化的高超声速飞行器控制系统实现

为实现对高超声速飞行器横滚角度数值、纵滚角度数值的同步控制,使飞行器元件呈现出相对平稳的运动状态,设计基于微分几何反馈线性化的高超声速飞行器控制系统;利用电源管理模块电路,更改电机驱动器元件的连接形式,根据螺旋桨转动速率,调试IMU惯性传感器、GPS定位、PID控制器三类下级硬件设备的实时运行状态,完成高超声速飞行器控制系统的主体应用结构设计;按照飞行器运动轨迹的微分处理结果,计算控制向量反馈指标的具体数值水平,再通过解析几何信号的处理方式,确定线性化姿态解算表达式,实现基于微分几何反馈线性化的飞行器控制程序设计,结合相关硬件应用设备,完成对高超声速飞行器控制系统的研究;实验结果显示,当实验时间为14 s时,实验组横滚角度数值与理想角度数值之间的差值最大为3°;当实验时间为6 s时,实验组纵滚角度数值与理想角度数值之间的差值最大为4°,微分几何反馈线性化原则能够有效控制横滚角度数值、纵滚角度数值与理想角度数值之间的差值水平,在促进高超声速飞行器平稳运动方面具有较强的可行性价值。     

水上无人机自主着水控制系统设计

针对水上无人机在高海况下的着水问题,本文在分析了不同着水阶段特性的基础上,提出了一种自主着水控制系统设计方案.该方案将整个系统分为速度控制子系统和姿态控制子系统.速度控制子系统包含速度动态逆控制器和油门切换模块,姿态控制子系统包含海浪滤波器俯仰角反步控制器、高度PID控制器、俯仰角切换模块和T-S模糊推理模块.其中,海浪滤波器能有效滤除受扰姿态角中的海浪高频扰动,避免了着水之后舵面的频繁抖动;俯仰角反步控制器采用指令滤波的反步法设计,有效缓解了高海况下的舵面饱和问题.最后,在不同海况条件下进行了仿真.仿真结果表明所设计的控制系统具有良好的控制性能.     

飞行试验机翼变形测量的一种方法

飞机飞行过程中的机翼变形会引起武器在俯仰、滚转和偏航3个方向的姿态变化,三维姿态变化的大小将直接影响武器对目标的命中性能,需要对不同飞行状态下武器的三雏运动姿态进行测量,修正真实飞行状态下机翼变形引起的对准误差.在吊舱中安装两台高速摄像机同时拍摄机载武器,对采集到的序列图像进行处理,就能获得机载武器空中挂飞过程中的三维运动姿态参数.     

Active Heave Compensation Control of ROVS

To keep the remotely operated vehicles (ROVs) motion unaffected by the ship's motion in the vertical direction, a nonlinear active heave compensation controller is designed in this paper. The compensation system consists mainly of an electro‐hydraulic system driven by a double rod cylinder. Based on the external model principle, an adaptive observer is proposed to asymptotically estimate the ship's heave motion represented by a set of sinusoidal signals. The hybrid control development and stability analysis are based on the Lyapunov's direct method and backstepping technique. The proposed controller forces the tracking error to globally asymptotically converge to a small zone around zero that can be reduced arbitrarily. Simulation results illustrate and validate the effectiveness of the proposed control scheme.     

Real-time prediction of unsteady aerodynamics: Application foraircraft control and manoeuvrability enhancement

The capability to control unsteady separated flow fields could dramatically enhance aircraft agility. To enable control, however, real-time prediction of these flow fields over a broad parameter range must be realized. The present work describes real-time predictions of three-dimensional unsteady separated flow fields and aerodynamic coefficients using neural networks. Unsteady surface-pressure readings were obtained from an airfoil pitched at a constant rate through the static stall angle. All data sets were comprised of 15 simultaneously acquired pressure records and one pitch angle record. Five such records and the associated pitch angle histories were used to train the neural network using a time-series algorithm. Post-training, the input to the network was the pitch angle (alpha), the angular velocity (dalpha/dt), and the initial 15 recorded surface pressures at time (t (0)). Subsequently, the time (t+Deltat) network predictions, for each of the surface pressures, were fed back as the input to the network throughout the pitch history. The results indicated that the neural network accurately predicted the unsteady separated flow fields as well as the aerodynamic coefficients to within 5% of the experimental data. Consistent results were obtained both for the training set as well as for generalization to both other constant pitch rates and to sinusoidal pitch motions. The results clearly indicated that the neural-network model could predict the unsteady surface-pressure distributions and aerodynamic coefficients based solely on angle of attack information. The capability for real-time prediction of both unsteady separated flow fields and aerodynamic coefficients across a wide range of parameters in turn provides a critical step towards the development of control systems targeted at exploiting unsteady aerodynamics for aircraft manoeuvrability enhancement.     

A neuro-fuzzy approach to fast ferry vertical motion modelling

In order to stabilise the motion of a high speed craft, and so to improve the comfort of the passengers and the crew while maintaining the speed, control-oriented model are needed. For this purpose, neuro-fuzzy systems have been used to obtain general models of the non-linear behaviour of a fast ferry. The sources of the available knowledge are the physical laws of the vertical dynamics of the craft, and some experimental and simulated data of the ship performance. Two non-linear models focused on the vertical motion of the craft, both heave and pitch, are proposed: an academic one and a predictive one. The modelling task is complex and the results are original as the problem has not been previously solved in a general way neither by applying artificial intelligence techniques. The models have been proved satisfactory with regular and also irregular waves, and they have been used for ship control purposes.     

飞行模拟器的结构设计与仿真研究

飞行模拟器具有真实飞行训练无法比拟的优势,其结构设计是优化飞机设计,改善飞行性能的关键问题,故飞行模拟器的建模与仿真研究工作是飞行器设计的难点。通过与液压缸驱动的六自由度飞行模拟器对比分析,以3-RPS机构为基础,以在UG环境下建立的电动缸驱动的三自由度飞行模拟器运动平台模型为研究对象,在ADAMS/View模块下,对其添加约束和驱动后,进行了运动学特性仿真。对于给定的运动学特性曲线,运用ADAMS/Post Processor模块,对测量结果进行后处理,得到各种飞行姿态下的运动学曲线。仿真实验结果验证了该设计可实现升降、横滚、俯仰三种姿态的运动,且符合民航飞行模拟器的技术指标要求。上述分析过程为飞行模拟器的设计提供了一套有效的研究方法。     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

Dynamic instability of thermal-flying-height-control sliders at touchdown

With the wide application of thermal flying-height control (TFC) technology in the hard disk drive industry, the head-disk clearance can be controlled to as low as ~1?nm. At this ultra-low clearance, the air bearing slider is subject to relatively large interfacial forces, and it experiences more complicated dynamics, compared with the flying case. In this study we conduct a numerical analysis to investigate the dynamics of TFC sliders during touchdown. The general trend of the slider’s motion predicted by the numerical simulation qualitatively agrees with experimental findings. The touchdown process begins with a slight intermittent contact between the slider’s trailing edge and the disk, followed by a partial slider-disk contact at the trailing edge accompanied by a large pitch motion at the 1st air bearing mode; this pitch motion gets suppressed and the slider comes into stable sliding on the disk as the protrusion is further increased.     

Interactive computer-aided control design using quantitative feedback theory: the problem of vertical movement stabilization on a high-speed ferry

In a first approximation, the vertical acceleration associated with pitch motion can be considered as the main cause of motion sickness, which is without a doubt one of the most unpleasant disadvantages of maritime transport. The reduction of motion sickness can be stated as a monovariable regulation problem of a highly perturbed system. This work presents the design of a monovariable robust controller with quantitative feedback theory (QFT) for reducing the vertical movement on a high-speed ferry. The different stages of QFT methodology have been done with the help of the software tool QFTIT (Quantitative Feedback Theory Interactive Tool). This is a free software tool that is characterized by its ease of use and interactive nature. The designed regulator is validated experimentally in sea behaviour trials with a scaled down replica 1/25 the size of a high-speed ferry. The designed regulator is also compared with a gain-scheduling scheme using a proportional and derivative controller (PD).     

An advanced cargo handling system operating at sea

Mobile Harbor (MH) was recently proposed by KAIST as a novel maritime cargo transfer system that can go out to a container ship anchored in deep water and handle containers at sea. Since the system operates in at-sea conditions with waves and wind, the MH crane should be designed to suppress the swing motion of a spreader and compensate the relative motion between the MH and a container ship. For that purpose, we devised a state-of-the-art crane system equipped with a dual stage trolley, tension controller, and intelligent spreader with 3 degrees of freedom. We also integrated a robust sensing system to measure remote motions in harsh open-sea condition. With these advanced systems, we achieved swing free, position, tilting, and heave control systems for precise and safe cargo transfer. Experimental results with a 1/20 scale MH crane show the feasibility of the proposed system for at-sea cargo transfer.