Trajectory linearization based output tracking control of an unmanned tandem helicopter with variance constraints

An output tracking control problem for an unmanned tandem rotor helicopter with variance constraints is investigated in this paper. A modified Trajectory Linearization Control (TLC) is proposed to stabilize a nonlinear continuous-time flight dynamics system of the tandem helicopter. The tracking controller structure of TLC is designed by using two-time-scale nonlinear dynamic inversion. The base control law of the translational and attitude loops is designed in a pseudo-inversion feedforward controller to deal with nonlinear features of the plant and a proportional integral controller to stabilize the linear slowly time-variant error system resulted from the nonlinear flight system. Furthermore, a feasible TLC strategy is designed to meet a performance index set including steady trajectory tracking error variance and desired Parallel D-spectrum (PD-) eigenvalues to achieve good flight quality. The Variance-constrained Trajectory Linearization Control (VCTLC) is designed to realize the desired steady tracking precision and agile capability. Flight simulation results show the VCTLC method is feasible and effective in attitude and altitude tracking.     

Trajectory tracking control for a miniature fixed-wing unmanned air vehicle

This article considers the problem of trajectory tracking control for a miniature fixed-wing unmanned air vehicle (UAV). With the UAV equipped with longitudinal and lateral autopilots, we adopt a kinematic model that takes into account the fact that the heading of the UAV is controlled by its roll motion and the autopilot responses to air speed and roll control commands are first order in nature. Backstepping techniques are applied to derive air speed and roll control commands from known air speed and heading control laws that explicitly account for air speed and heading rate constraints of the UAV. Regarding inaccurately known autopilot constants, a parameter adaptation technique is used to estimate autopilot constants. High-fidelity simulation results on a six degree-of-freedom (DOF) 12-state fixed-wing UAV model are presented to show the effectiveness of our approach.     

基于DMC的微小型无人直升机航迹跟踪

微小型无人直升机的航迹跟踪需要在克服模型不确定性的同时保持良好的控制精度和动态性能。提出了航迹跟踪的动态矩阵控制（DMC）方法,通过在线优化、反馈校正抑制不确定性的影响。将系统经姿态环和速度环镇定后作为广义对象,设计了DMC控制器,并对DMC参数进行了整定。半实物仿真实验证明,采用DMC方法后,系统具有较好的动态响应,航迹跟踪效果明显改善。     

基于Dubins曲线的无人直升机轨迹规划

为提高无人直升机的控制性能,提出了一种基于Dubins曲线的轨迹规划算法,并对其各个部分的实现进行了研究和设计。该算法利用Dubins曲线原理对定点飞行任务的两点或者多点目标进行分析计算,寻找出一条最短的飞行路径,从而提高了飞行效率。根据无人直升机系统多变量、非线性和强耦合的特点,采用串级PID方法设计了飞行控制器,该控制器能够修正无人直升机的姿态和位置,从而提高了轨迹规划的稳定性和准确性。最后,以某小型无人直升机为实验平台表明了该轨迹规划算法和控制器的可行性。     

Autonomous takeoff and landing control for a prototype unmanned helicopter

In this paper, an autonomous takeoff and landing control strategy is designed and implemented for a prototype coaxial unmanned helicopter with ducted fan configuration. The control strategy is designed such that longitudinal and lateral controls use ground forces, attitude and drifting feedbacks. Vertical control employs takeoff and landing decision and vertical velocity control is based on altitude tracking. Ground forces feedback is used to balance longitudinal forces and moments during liftoff effectively cancelling all ground forces. Attitude and drifting feedbacks are used to balance the longitudinal and lateral movements of the helicopter during takeoff and landing. The flight control strategy is successfully verified during flight tests.     

微小型无人直升机协调转弯的控制和实现

针对微小型无人直升机( MUH)协调转弯的问题,提出了控制策略和实施方案。首先在MUH数学模型的基础上,建立了MUH的状态方程,灰箱辨识得到其参数;然后分析了协调转弯的工作原理,并以无人直升机的军标ADS-33E-PRF作为参考,利用Matlab sisotool工具箱设计了协调转弯控制器,反复调整参数使其满足军标的level1标准;最后基于该对象和设计的控制器,在3~6m/s的风速下,进行了实物飞行实验。实际飞行结果表明：协调转弯控制姿态稳定,速度误差在±0.5 m/s以内,高度保持相对稳定,误差在±1.2 m以内,水平曲线近似一个圆,XY位置误差在8%以内。结果验证了所设计的协调转弯控制器可靠,工程上能实现,具备良好的鲁棒性和动态性能。     

Adaptive backstepping control for electrically driven unmanned helicopter

This paper addresses the attitude control problem for a twin rotor unmanned helicopter driven by DC motors. The control objective is to have the helicopter attitude, i.e., pitch and yaw angles, track specified angles. From the considered dynamics of the plant, it is observed that the main difficulty of the control problem is due to the existing nonlinear coupling effects between the two perpendicular rotors. Hence, a novel adaptive control approach based on the backstepping concept is developed to solve the problem. In the controller design, the system parameters are assumed to be unavailable and are estimated on-line. The stability of the overall closed-loop system is proven to be asymptotically stable based on the Lyapunov theorem. In order to demonstrate the applicability of the proposed control scheme, computer simulations and experiments are shown.     

无人直升机嵌入式控制系统的实现

基于AT91RM9200(ARM)微型控制器,结合适当的外围设备,构建了一个高集成度的嵌入式系统,实现微型无人直升机的飞行控制.在μC/OS-Ⅱ操作系统环境下,详细介绍了软件系统的总体结构和任务之间的切换过程.最后,针对直升机的姿态和位置控制,分别给出了适当的控制策略.     

Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects. Recommended by Editorial Board member Hyo-Choong Bang under the direction of Editor Hyun Seok Yang. This work was supported by the Korea Research Foundation Grant (MOEHRD) KRF-2005-204-D00002, the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government(MOST) R0A-2007-000-10017-0 and Engineering Research Institute at Seoul National University. Daewon Lee received the B.S. degree in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical and Aerospace Engineering. He has been a member of the UAV research team at SNU since 2005. His research interests include applications of nonlinear control and vision-based control of UAV. H. Jin Kim received the B.S. degree from Korea Advanced Institute of Technology (KAIST) in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from University of California, Berkeley in 1999 and 2001, respectively. From 2002–2004, she was a Postdoctoral Researcher and Lecturer in Electrical Engineering and Computer Science (EECS), University of California, Berkeley (UC Berkeley). From 2004–2009, she was an Assistant Professor in the School of in Mechanical and Aerospace Engineering at Seoul National University (SNU), Seoul, Korea, where she is currently an Associate Professor. Her research interests include applications of nonlinear control theory and artificial intelligence for robotics, motion planning algorithms. Shankar Sastry received the B.Tech. degree from the Indian Institute of Technology, Bombay, in 1977, and the M.S. degree in EECS, the M.A. degree in mathematics, and the Ph.D. degree in EECS from UC Berkeley, in 1979, 1980, and 1981, respectively. He is currently Dean of the College of Engineering at UC Berkeley. He was formerly the Director of the Center for Information Technology Research in the Interest of Society (CITRIS). He served as Chair of the EECS Department from January, 2001 through June 2004. In 2000, he served as Director of the Information Technology Office at DARPA. From 1996 to 1999, he was the Director of the Electronics Research Laboratory at Berkeley (an organized research unit on the Berkeley campus conducting research in computer sciences and all aspects of electrical engineering). He is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences and holds faculty appointments in the Departments of Bioengineering, EECS and Mechanical Engineering. Prior to joining the EECS faculty in 1983 he was a Professor with the Massachusetts Institute of Technology (MIT), Cambridge. He is a member of the National Academy of Engineering and Fellow of the IEEE.     

状态受限的小型无人直升机轨迹跟踪控制

无人直升机模型阶数比较高,设计常规反步控制器面临繁琐的对虚拟控制输入信号求导过程.针对此问题,设计了一种基于滤波器的反步控制方法.该方法通过滤波器而非直接解析地对虚拟控制量进行求导,从而显著简化了反步控制律的计算过程.在滤波器设计过程中,通过限制中间虚拟控制信号的幅值,变化速率以及带宽,以满足系统对状态变量及控制输入信号的约束要求.李雅普诺夫稳定性分析证明了直升机补偿跟踪误差全局指数稳定.仿真研究验证了该方法的有效性.     

小型无人直升机反步自适应控制

针对具有强非线性、高度耦合以及参数不确定性特点的小型无人直升机系统,提出一种基于小脑模型关节控制器（Cerebellar Model Articulation Control,CMAC）神经网络的自适应反步控制方法,该方法采用小脑模型关节控制器神经网络在线学习系统不确定性以及反步控制中各阶虚拟控制量的导数信息,设计鲁棒控制项克服CMAC神经网络在线学习系统不确定性的误差,控制律由反步法回归递推得到。仿真结果表明,在模型参数不确定和存在较大误差的情况下,所设计的控制律具有理想的姿态跟踪性能以及良好的鲁棒性。     

Robust attitude tracking control of small-scale unmanned helicopter

Robust attitude control problem for small-scale unmanned helicopters is investigated to improve attitude control performances of roll and pitch channels under both small and large amplitude manoeuvre flight conditions. The model of the roll or pitch angular dynamics is regarded as a nominal single-input single-output linear system with equivalent disturbances which contain nonlinear uncertainties, coupling-effects, parameter perturbations, and external disturbances. Based on the signal compensation method, a robust controller is designed with two parts: a proportional-derivative controller and a robust compensator. The designed controller is linear and time-invariant, so it can be easily realised. The robust properties of the closed-loop system are proven. According to the ADS-33E-PRF military rotorcraft standard, the controller can achieve top control performances. Experimental results demonstrate the effectiveness of the proposed control strategy.     

小型无人直升机的姿态与高度自适应反步控制

针对小型无人直升机的姿态与高度控制问题, 本文提出了一种基于反步法的自适应控制策略. 具体而言, 首先对小型无人直升机的运动学模型进行了等效变换, 使系统中未知参数满足线性参数化条件, 然后应用反步法设计了包含主旋翼挥舞模型的姿态与高度自适应控制器, 并借助Lyapunov方法和芭芭拉定理对闭环系统的稳定性进行了严格的数学分析. 最后, 对该控制器的性能进行了仿真验证, 结果表明在直升机质量和惯性矩阵存在不确定性(未知)的情况下, 该控制算法依然能够取得良好的控制效果.     

A fuzzy gain-scheduler for the attitude control of an unmanned helicopter

In this paper, we address the design of an attitude controller that achieves stable, and robust aggressive maneuverability for an unmanned helicopter. The controller proposed is in the form of a fuzzy gain-scheduler, and is used for stable and robust altitude, roll, pitch, and yaw control. The controller is obtained from a realistic nonlinear multiple-input-multiple-output model of a real unmanned helicopter platform, the APID-MK3. The results of this work are illustrated by extensive simulation, showing that the objective of aggressive, and robust maneuverability has been achieved.     

Hierarchical hybrid modelling and control of an unmanned helicopter

In this paper, we propose a hybrid modelling and control design scheme for an unmanned helicopter. This control structure has a hierarchical form with three layers: the regulation layer, the motion planning layer, and the supervision layer. For each layer, a separate hybrid controller has been developed. Then, a composition operator is adopted to capture the interactions between these layers. The resulting closed-loop system can flexibly command the helicopter to perform different tasks, autonomously. The designed controller is embedded in the avionic system of an unmanned helicopter, and actual flight test results are presented to demonstrate the effectiveness of the proposed control structure.     

无人直升机路径规划算法研究

提出了一种基于已知威胁点分布的Voronoi图的无人直升机路径规划算法。利用Dijkstra算法搜索出无人直升机初始最短路径，在此基础上利用威胁加权划分威胁区域对路径进行二次规划，在无人直升机机动特性的限制条件下对路径进行平滑处理，且考虑到突发威胁体出现的条件下再次对路径进行局部重规划求解最佳路径。通过Matlab 6.5对算法进行仿真验证了算法的可行性。     

基于PIDNN的六旋翼无人机飞行控制算法研究

针对六旋翼无人机比例-积分-微分(PID)控制器参数优化困难的问题,采用了PID神经网络(PIDNN)控制方法,利用其非线性映射和自学习的特性,实现了姿态控制参数的动态调整,增加了系统的自适应性.为验证方法的有效性,通过Matlab的Simulink模块构建了六旋翼无人机数学模型;利用S函数实现了基于反向传播(BP)算法的PIDNN控制器;将仿真结果与传统PID控制效果进行对比,结果表明:在缩短姿态调整时间与减少超调量方面,PIDNN方法控制效果优于PID方法.     

Neural Network Based Feedback Linearization Control of an Unmanned Aerial Vehicle

This paper presents a flight control design for an unmanned aerial vehicle (UAV) using a nonlinear autoregressive moving average (NARMA-L2) neural network based feedback linearization and output redefinition technique.The UAV investigated is non- minimum phase.The output redefinition technique is used in such a way that the resulting system to be inverted is a minimum phase system.The NARMA-L2 neural network is trained off-line for forward dynamics of the UAV model with redefined output and is then inverted to force the real output to approximately track a command input.Simulation results show that the proposed approaches have good performance.     

Robust multi-mode flight control design for an unmanned helicopter based on multi-loop structure

In this paper, a novel multi-mode flight control strategy for unmanned helicopter, in presence of model uncertainty, atmospheric disturbances and handling qualities specification requirements (as in ADS-33E), based on multi-loop control structure combining robust H-infinity and PI control is presented. In inner loop H-infinity optimal control technique is utilized ensuring the stability of flight control system in case of change of helicopter dynamics, model uncertainties and eliminates effect of gust disturbance on helicopter states and collective/cyclic inputs. PI control in outer loop is used to improve the dynamic and static operation characteristics. Attitude control and attitude holding flight mode with satisfactory command response and decoupling characteristics is designed using the proposed control strategy. Analysis and simulation results show that Level 1 handling requirements as defined in ADS-33E are accomplished even when helicopter is under constant wind circumstance.     

基于DSP和FPGA的无人直升机飞行控制系统

为实现无人直升机的先进飞行控制算法,设计基于DSP和FPGA的无人直升机飞行控制系统。DSP数字信号处理能力强,主要实现复杂的飞行控制算法;FPGA作为DSP的协处理器,主要实现传感器信号的采集和处理、舵机驱动以及地面站监控。由于任务分配合理,该系统计算能力强、实时性好、灵活度高,为实现先进飞行控制算法提供了良好的硬件基础。通过无人直升机姿态控制实验验证了该系统的有效性。