舰尾流随高扰动模型对直升机着舰悬停控制的影响研究

大海况下存在的复杂舰尾流严重影响直升机着舰时的飞行姿态,针对常规舰尾流模型仅适用于研究直升机纵向运动受干扰的问题,本文在美军标 MIL-F-8785C 描述的舰尾流模型基础上,提出增加随高度变化的垂向扰动分量,建立舰尾流随高扰动模型,以便切合实际地反映垂向干扰的作用强度。将该模型引入直升机着舰悬停系统后,针对传统 PID 控制对高度保持和位置控制效果不佳的问题,提出基于前馈补偿的改进 PID 控制,对比仿真结果表明,所提控制方法具有较高的跟踪精度和良好的鲁棒性,能够满足实际舰尾流扰动下的直升机着舰悬停的控制要求。     

平流层卫星建模与基于分级模型的轨道控制

为实现平流层卫星在平流层大气环流作用下环某一纬度飞行,需对平流层卫星经度方向轨迹进行控制.根据Lagrange方程建立了其六自由度的动力学模型,在基于模型的直接输入输出反馈线性化无法实现的情况下,按"舵控制帆、帆控制绳和绳控制球"的工作原理将系统分为3个级联子系统,并对3个子系统分别设计控制器来实现"舵控制球"的轨迹控制.仿真结果表明所设计的控制器性能良好.     

Flight control of a rotary wing UAV using backstepping

This paper presents a novel application of backstepping controller for autonomous landing of a rotary wing UAV (RUAV). This application, which holds good for the full flight envelope control, is an extension of a backstepping algorithm for general rigid body velocity control. The nonlinear RUAV model used in this paper includes the flapping and servo dynamics. The backstepping‐based controller takes advantage of the ‘decoupling’ of the translation and rotation dynamics of the rigid body, resulting in a two‐step procedure to obtain the RUAV control inputs. The first step is to compute desired thrusts and flapping angles to achieve the commanded position and the second step is to compute control inputs, which achieve the desired thrusts and flapping angles. This paper presents a detailed analysis of the inclusion of a flapping angle correction term in control. The performance of the proposed algorithm is tested using a high‐fidelity RUAV simulation model. The RUAV simulation model is based on miniature rotorcraft parameters. The closed‐loop response of the rotorcraft indicates that the desired position is achieved after a short transient. The Eagle RUAV control inputs, obtained using high‐fidelity simulation results, clearly demonstrate that this algorithm can be implemented on practical RUAVs. Copyright © 2009 John Wiley & Sons, Ltd.     

Direct product quality control for energy efficient climate controlled transport of agro-material

A (model-based) Product Quality Controller is presented for climate controlled operations involving agro-material, such as storage and transport. This controller belongs to the class of Model Predictive Controllers and fits in a previously developed hierarchical control structure. The new Product Quality Controller rejects disturbances and tracks the product quality by means of the product responses respiration and fermentation. To achieve an energy efficient operation the presented controller is closely linked with the (existing) local controllers. Local optimisation on the level of these local controllers allows (controlled) high-frequent climate fluctuations. This results in significant energy savings. The Product Quality Controller and the energy efficient local controllers are implemented in small-scale and full-scale industrial case studies on controlled atmosphere-container transport of apples. This yields direct control of product quality and a significant reduction in energy consumption.     

无人直升机基于视觉的静止点目标跟踪*

针对带有摄像机的直升机进行静止点目标跟踪的情况,提出了一种层级控制器。该控制器共有三个回路：内回路采用四个独立的PD控制器控制直升机的高度和姿态;中间回路利用两个Mamdani型模糊控制器控制直升机的位置;外回路利用视觉反馈获得直升机下一步的期望位置,其不需要已知摄像机的内参数和平移外参数以及目标点的坐标,只需已知粗略标定的旋转外参数。仿真结果表明了该控制器的可行性。     

Design and implementation of a hybrid fuzzy logic controller for a quadrotor VTOL vehicle

Helicopters have generated considerable interest in both the control community due to their complex dynamics, and in military community because of their advantages over regular aerial vehicles. In this paper, we present the modeling and control of a four rotor vertical take-off and landing (VTOL) unmanned air vehicle known as quadrotor aircraft. This model has been generated using Newton-Euler equations. In order to control the helicopter, classical PD (proportional derivative) and Hybrid Fuzzy PD controllers have been designed. Although fuzzy control of various dynamical systems has been presented in literature, application of this technology to quadrotor helicopter control is quite new. A quadrotor helicopter has nonlinear characteristics where classical control methods are not adequate especially when there are time delays, disturbances and nonlinear vehicle dynamics. On the other hand, Fuzzy control is nonlinear and it is thus suitable for nonlinear system control. Matlab Simulink has been used to test, analyze and compare the performance of the controllers in simulations. For the evaluation of the autonomous flight controllers, some experiments were also performed. For this purpose, an experimental test stand has been designed and manufactured. This study showed that although, both of the classical PD and the Fuzzy PD controllers can control the system properly, the Fuzzy PD controllers performed slightly better than the classical PD controllers, and have benefits such as better disturbance rejection, ease of building the controllers.     

基于两时间尺度模型的直升机非线性控制器设计

提出一种基于两时间尺度模型的直升机非线性控制方法. 该方法利用直升机不同状态达到稳定的时间不同的特点, 将直升机模型分为快速和慢速两种模型. 反步控制方法和逆动力学控制方法分别被用于进行快慢两种模型控制器的设计, 并在控制过程中采用了不同的控制周期. 仿真结果表明, 利用上述方法设计的控制器, 对于阶跃变化和正弦变化的速度轨迹具有良好的跟踪效果.

     

直升机执行器故障的双时标容错控制系统设计

针对直升机的执行器故障,本文提出了一种基于双时标模型的自适应容错控制方法.根据直升机的不同状态变量响应时间不同的特点和时标分离理论,将直升机模型划分为快速(姿态动力学)和慢速(平移动力学)两种时标模型.反步控制方法和逆动力学控制方法分别被用于进行快慢两种模型控制器的设计,并在控制过程中采用了不同的控制周期.在双时标模型中,引入了执行器效率因子(actuator effectiveness factors,AEFs)用于表示执行器的健康情况.利用无色卡尔曼滤波(unscented Kalman filter,UKF)对AEFs进行了在线估计,估计结果用于快速和慢速模型控制器的自适应重构.仿真结果表明,该自适应容错控制方法,能够有效的消除执行器故障(包括常值和时变故障)对直升机飞行性能的影响,并取得良好的控制效果.     

基于开放平台和神经网络的自主飞行控制系统研究

开发了飞行控制软件的应用中间件，实现控制结构的动态变化和控制组件的动态重构. 基于模型逆技术，设计了某状态下的旋转逆和平移逆控制器，其它状态下的逆误差由在线神经网络补偿．实例仿真的结果表明：开放平台和神经网络的结合，能够很好地实现无人直升机的自主飞行，具有较大的理论意义和工程应用价值．     

Vision-Based Landing of Light Weight Unmanned Helicopters on a Smart Landing Platform

This paper presents a simple and efficient solution to vision guided autonomous landing of a light-weight (<150 Kg) unmanned helicopter on a smart landing platform, called ISLANDS??Intelligent Self-Leveling and Nodal Docking System. The advantage of ISLANDS is that it may allow the helicopter upon docking to recharge its batteries or refuel, thus, indirectly increasing endurance and flight range. In order for the helicopter to dock with ISLANDS, an on-board ??vision module?? coupled with the helicopter attitude controller is developed. This ??vision module?? detects the location and orientation of ISLANDS and feeds back information to the helicopter attitude controller, which commands the helicopter to descent onto the landing platform at a desired orientation and speed. The Scale Invariant Feature Transform (SIFT) is used for automatic detection of the landing platform based on images captured by a single camera mounted on the helicopter. The detected SIFT features are used to estimate the 3-D orientation of the platform relative to the helicopter using Homography and RANSAC techniques. The focus of this paper is on the vision-guided landing technique in a predefined orientation and not on controller details, which may be found in Shim et al. (1998).     

无人直升机的姿态增强学习控制设计与验证

针对小型无人直升机的姿态控制问题,考虑到现有基于模型的控制方法对直升机动力学模型的先验信息依赖较大,以及未建模动态系统的影响等问题,设计了一种基于增强学习(RL)的飞行控制算法.仅利用直升机的在线飞行数据,补偿了未建模不确定性的影响.同时为了抑制外界扰动,提高系统的鲁棒性,设计了一种基于误差符号函数积分的鲁棒(RISE)控制算法.将两种算法结合,并利用基于Lyapunov分析的方法,证明了无人机姿态控制误差的半全局渐近收敛.最后在无人直升机飞行控制实验平台上,进行了姿态控制的实时实验验证.实验结果表明,本文提出的控制方法具有良好的控制效果,对系统不确定性和外界风扰具有良好鲁棒性.     

A desired landing points walking method enablinga planner quadruped robot to walk on rough terrain

It is necessary for legged robots to walk stably and smoothly on rough terrain.In this paper,a desired landing points(DLP) walking method based on preview control was proposed in which an off-line foot motion trace and an on-line modification of the trace were used to enable the robot to walk on rough terrain.The on-line modification was composed of speed modification,foot lifting-off height modification,step length modification,and identification and avoidance of unsuitable landing terrain.A planner quadruped robot simulator was used to apply the DLP walking method.The correctness of the method was proven by a series of simulations using the Adams and Simulink.     

基于计算机视觉的无人直升机位姿估计方法研究

无人直升机与着陆点的相对位置和姿态估计是其实现自主着陆的前提条件，采用计算机视觉技术完成该任务是当前的发展趋势。介绍了基于计算机视觉技术的位姿估计方法的特点，对目前直升机自主着陆研究中采用的各种位姿估计方法做了分类并进行了评述，为类似的视觉系统的设计和相关问题的研究提供了参考。     

作业型飞行机器人抓取后重心偏移的轨迹跟踪控制

作业型飞行机器人是指能够对环境施加主动影响的飞行机器人, 它通常由旋翼飞行器与机械臂组合而成. 本文针对作业型飞行机器人在动态飞行抓取后, 重心位置变化产生的系统控制难题, 设计了有效的跟踪控制策略. 首先, 在系统建模时引入重心偏移系统参数和重心偏移控制参数, 并考虑惯性张量不为常数, 提高了系统建模的精度. 然后, 在姿态解算时, 考虑重心偏移对系统性能的影响, 构建包含重心偏移系统参数的解算方法, 得到更高精度的期望翻滚角和期望俯仰角. 接着, 设计了基于滑模控制的重心偏移补偿位置控制器, 实现了有效的位置跟踪控制. 同时, 在姿态反演控制器的基础上, 加入自适应律估计重心偏移控制参数和变化的惯性张量, 再通过小脑神经网络逼近惯性张量的真实值, 提高姿态控制器的精度. 最后, 给出了所设计控制器的稳定性证明, 并在仿真环境下验证了所提出的方法的有效性和优越性.     

Small Helicopter Control Design Based on Model Reduction and Decoupling

In this paper a complete nonlinear mathematical model of a small scale helicopter is derived. A coupling between input and output variables, revealed by the model, is investigated. The influences that particular inputs have on particular outputs are examined, and their dependence on flying conditions is shown. In order to demonstrate this dependence, the model is linearized in various operating points, and linear, direct and decoupling, controllers are determined. Simulation results, presented at the end of the paper, confirm that the proposed control structure could be successfully used for gain scheduling or switching control of a small scale helicopter in order to provide acrobatic flight by using simple linear controllers.     

Vessel motion control using rope tension control strategy

In this paper, the problem of designing a Position Mooring (PM) system for a barge ship is addressed. A mathematical model of a system comprising a barge ship and mooring system is derived. Hydrodynamic coefficients of the low speed model for PM ship are identified by suitable experiments. A PID control scheme is implemented to achieve PM for the vessel by changing the tension of the mooring ropes. The proposed strategy is finally tested on station keeping, and desired positions of a 1/50 scale model ship are obtained.     

A reinforcement neuro-fuzzy combiner for multiobjective control

This paper proposes a neuro-fuzzy combiner (NFC) with reinforcement learning capability for solving multiobjective control problems. The proposed NFC can combine n existing low-level controllers in a hierarchical way to form a multiobjective fuzzy controller. It is assumed that each low-level (fuzzy or nonfuzzy) controller has been well designed to serve a particular objective. The role of the NFC is to fuse the n actions decided by the n low-level controllers and determine a proper action acting on the environment (plant) at each time step. Hence, the NFC can combine low-level controllers and achieve multiple objectives (goals) at once. The NFC acts like a switch that chooses a proper action from the actions of low-level controllers according to the feedback information from the environment. In fact, the NFC is a soft switch; it allows more than one low-level actions to be active with different degrees through fuzzy combination at each time step. An NFC can be designed by the trial-and-error approach if enough a priori knowledge is available, or it can be obtained by supervised learning if precise input/output training data are available. In the more practical cases when there is no instructive teaching information available, the NFC can learn by itself using the proposed reinforcement learning scheme. Adopted with reinforcement learning capability, the NFC can learn to achieve desired multiobjectives simultaneously through the rough reinforcement feedback from the environment, which contains only critic information such as "success (good)" or "failure (bad)" for each desired objective. Computer simulations have been conducted to illustrate the performance and applicability of the proposed architecture and learning scheme.     

A unified method for evaluating real-time computer controllers and its application

A computer-controlled system is a synergistic coupling of the controlled process and the controller computer. We have defined new performance measures for real-time controller computers based on this coupling. We present a systematic study of a typical critical controlled process in the context of new performance measures that express the performance of both controlled processes and controller computers (taken as a unit) on the basis of a single variable: controller response time. Controller response time is a function of current system state, system failure rate, electrical and/or magnetic interference, etc., and is therefore a random variable. Control overhead is expressed as monotonically nondecreasing function of the response time and the system suffers catastrophic failure, or dynamic failure, if the response time for a control task exceeds the corresponding system hard deadline, if any. The controlled-process chosen for study is an aircraft in the final stages of descent, just prior to landing. Control constraints are particularly severe during this period, and great care must be taken in the design of controllers that handle this process. First, the performance measures for the controller are presented. Second, control algorithms for solving the landing problem are discussed, and finally the impact of our performance measures on the problem is analyzed, showing that the performance measures and the associated estimation method have potential use for designing and/or evaluating real-time controllers and controlled process. In common with all other control techniques, the computational complexity involved in obtaining these measures is susceptible to the curse of dimensionality.     

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.     

Three‐time scale singular perturbation control and stability analysis for an autonomous helicopter on a platform

A three‐time scale singular perturbation control law is designed for a nonlinear helicopter model in vertical flight. The proposed control law is based on time scale decomposition and is able to achieve the desired altitude by selecting a desired angular velocity and the associated collective pitch angle of the blades. The stability of the system is performed by presenting a stability analysis for generic three‐time scale singularly perturbed systems, which allows to construct a composite Lyapunov function for the resultant closed‐loop system by using time scale separation and also providing mathematical expressions for the upper bounds of the singularly perturbed parameters that define the three‐time scale. Numerical results on both, the singular perturbation control strategy and the stability analysis, are also presented for the studied nonlinear highly coupled helicopter model. Copyright © 2012 John Wiley & Sons, Ltd.