Attitude estimation and control of a 3-DOF lab helicopter only based on optical flow

This paper proposes an attitude estimation method based on optical flow to solve the attitude tracking control problem for a three degree-of-freedom (3-DOF) lab helicopter. First, the relationship between optical flow and the motion of a general unmanned aerial vehicle is derived from the transformation between the image coordinate frame and the world coordinate frame. Then, an expression for the angular velocity of the 3-DOF helicopter is deduced only based on optical flow, and the attitude information is acquired by solving nonlinear equations. Finally, using visual feedback, a linear quadratic regulation (LQR) controller is designed for hovering and tracking, which consists of a feedforward controller and a LQR state feedback controller. Closed-loop experimental results on the lab helicopter demonstrate the effectiveness of the proposed estimation and control methods.     

主旋翼升力和机身姿态受限的模型直升机非线性控制（英文）

A nonlinear control is proposed for trajectory tracking of a 6-DOF model-scaled helicopter with constraints on main rotor thrust and fuselage attitude. In the procedure of control design, the mathematical model of helicopter is simplified into three subsystems: altitude subsystem, longitudinal-lateral subsystem and attitude subsystem. The proposed control is developed by combining the sub-controls for the corresponding subsystems. The sub-controls for altitude subsystem and longitudinal-lateral subsystem are designed with hyperbolic tangent functions to satisfy the constraints; the sub-control for attitude subsystem is based on backstepping technique such that fuselage attitude tracks the virtual control for longitudinallateral subsystem. It is proved theoretically that tracking errors are ultimately bounded, and control constraints are satisfied.Performances of the proposed controller are demonstrated by simulation results.     

主旋翼升力和机身姿态受限的模型直升机非线性控制

针对主旋翼升力和机身姿态受限的6自由度模型无人直升机的轨迹跟踪控制问题设计了一种非线性控制器.在控制器设计过程中,直升机的数学模型被简化为三个子系统: 姿态子系统,纵-侧向子系统和高度子系统,所设计的控制器由针对这三个子系统的子控制器组成.纵-侧向和高度子控制器基于双曲正切函数进行设计,以保证满足受限条件; 姿态子控制器利用反步法设计,使得机身姿态能够跟踪纵-侧向和高度子系统的虚拟控制.本文在理论上证明了闭环系统跟踪误差最终有界,并且控制器满足受限条件.仿真结果证实了所设计控制器的性能.     

Switching model predictive attitude control for a quadrotor helicopter subject to atmospheric disturbances

In this article a switching model predictive attitude controller for an unmanned quadrotor helicopter subject to atmospheric disturbances is presented. The proposed control scheme is computed based on a piecewise affine (PWA) model of the quadrotor's attitude dynamics, where the effects of the atmospheric turbulence are taken into consideration as additive disturbances. The switchings among the PWA models are ruled by the rate of the rotation angles and for each PWA system a corresponding model predictive controller is computed. The suggested algorithm is verified in experimental studies in the execution of sudden maneuvers subject to forcible wind disturbances. The quadrotor rejects the induced wind disturbances while performing accurate attitude tracking.     

小型无人直升机姿态非线性鲁棒控制设计

本文针对小型无人直升机的姿态控制问题,通过系统参数辨识,获得了较为准确的无人直升机姿态动力学模型.并根据无人直升机的动态特性,设计了基于神经网络前馈与滑模控制的非线性鲁棒姿态控制律,该控制律对直升机模型的先验知识要求较低.利用基于Lyapunov的分析方法证明,设计的控制律能够实现对无人直升机姿态角的半全局指数收敛镇定控制,并能确保闭环系统的稳定性.基于姿态飞行控制实验平台的实时飞行控制实验结果表明,提出的控制设计取得了很好的姿态控制效果,并对系统不确定性和外界风扰动具有较好的鲁棒性.     

A New Nonlinear Controller for Trajectory Tracking of the Longitudinal Dynamics of a Small Scale Helicopter

A nonlinear control scheme is proposed for the trajectory tracking problem of a small scale helicopter’s longitudinal dynamics. The control scheme is based on a control design procedure that constructs static feedback regulators for nonlinear systems which are linearizable by dynamic feedback. Besides, the flatness characteristics of the helicopter’s longitudinal dynamics are used to design the desired trajectory. The controller proposed is based on the longitudinal model of the small scale helicopter including the main rotor and stabilizer bar dynamics. Sufficient conditions are given to guarantee asymptotic convergence to zero of the tracking error and to keep the main rotor thrust always negative assuming that all the helicopter’s parameters are known and that all helicopter’s states are measured. Numerical simulations are given to show the performance of the controller in the presence of the main rotor and stabilizer bar dynamics.     

Quaternion-based Robust Trajectory Tracking Control of a Quadrotor Hover System

This paper presents a robust nonlinear output feedback control method that achieves three degree of freedom (3-DOF) attitude trajectory tracking of a hover system test bed. The proposed control method formally incorporates dynamic model uncertainty in addition to test bed voltage constraints. To reduce the computational requirement in the closed-loop system, constant feedforward estimates of the input-multiplicative parametric uncertainty are utilized in lieu of adaptive parameter estimates. To eliminate the need for angular rate measurements, the control design employs a bank of dynamic filters, which operates as a velocity estimator in the closed-loop system. A rigorous error system development and Lyapunov-based stability analysis are presented to prove asymptotic 3-DOF attitude trajectory tracking control. Computer simulation and experimental results are also included to illustrate the performance of the attitude control method using the Quanser 3-DOF hover system test bed.     

Nonlinear asymptotic attitude tracking control of an underactuated 3-degree-of-freedom helicopter using neural network feedforward term

This paper proposes a new asymptotic attitude tracking controller for an underactuated 3-degree-of-freedom (DOF) laboratory helicopter system by using a nonlinear robust feedback and a neural network (NN) feedforward term. The nonlinear robust control law is developed through a modified inner-outer loop approach. The application of the NN-based feedforward is to compensate for the system uncertainties. The proposed control design strategy requires very limited knowledge of the system dynamic model, and achieves good robustness with respect to system parametric uncertainties. A Lyapunov-based stability analysis shows that the proposed algorithms can ensure asymptotic tracking of the helicopter’s elevation and travel motion, while keeping the stability of the closed-loop system. Real-time experiment results demonstrate that the controller has achieved good tracking performance.     

A HIL Testbed for Initial Controller Gain Tuning of a Small Unmanned Helicopter

A Hardware-In-The-Loop (HIL) testbed design for small unmanned helicopters which provides a safe and low-cost platform to implement control algorithms and tune the control gains in a controlled environment is described. Specifically, it allows for testing the robustness of the controller to external disturbances by emulating the hover condition. A 6-DOF nonlinear mathematical model of the helicopter has been validated in real flight tests. This model is implemented in real-time to estimate the states of the helicopter which are then used to determine the actual control signals on the testbed. Experiments of the longitudinal, lateral and heading control tests are performed. To minimize the structural stress on the fuselage in case of controller failure or a subsystem malfunction, a damping system with a negligible parasitic effect on the dynamics of the helicopter around hover is incorporated. The HIL testbed is capable of testing the helicopter in hover, as well as on any smooth trajectories such as cruise flight, figure-8, etc. Experimentally tuning the controller on the HIL testbed is described and results in a controller which is robust to the external disturbances, and achieves an accuracy of ±2.5 cm in the position control on the longitudinal and lateral trajectory tracking, and ±5 deg accuracy around the yaw axis on the heading trajectory tracking.     

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.     

基于LQR直升机模糊滑模跟踪控制

研究直升机系统稳定性优化问题,由于直升机系统的强耦合和非线性特性的影响,使飞行的稳定性和实时跟踪性差。为解决上述问题,对直升机原始数学模型进行近似线性化和解耦处理,采用模糊滑模控制方法实现直升机姿态角度的跟踪控制。首先,在滑模面的设计中引入最优线性二次型调节器,构建一种积分型切换面。其次,以切换面及导数的乘积和滑模切换增益的变化量为模糊系统的变量,实时调整变结构控制项的切换增益。仿真结果表明,通过控制器设计能够实现直升机姿态角度跟踪的稳定性,对外界不确定干扰具有强鲁棒性且控制器输出抖振问题得到明显改善。     

A new smooth robust control design for uncertain nonlinear systems with non-vanishing disturbances

In this paper, we consider the control problem for a general class of nonlinear system subjected to uncertain dynamics and non-varnishing disturbances. A smooth nonlinear control algorithm is presented to tackle these uncertainties and disturbances. The proposed control design employs the integral of a nonlinear sigmoid function to compensate the uncertain dynamics, and achieve a uniformly semi-global practical asymptotic stable tracking control of the system outputs. A novel Lyapunov-based stability analysis is employed to prove the convergence of the tracking errors and the stability of the closed-loop system. Numerical simulation results on a two-link robot manipulator are presented to illustrate the performance of the proposed control algorithm comparing with the layer-boundary sliding mode controller and the robust of integration of sign of error control design. Furthermore, real-time experiment results for the attitude control of a quadrotor helicopter are also included to confirm the effectiveness of the proposed algorithm.     

共轴式无人直升机建模与鲁棒跟踪控制

针对共轴式无人直升机非线性、强耦合的动力学特性,本文提出了一种基于动态反馈线性化方法的鲁棒跟踪控制策略.首先根据叶素理论、Pitt-Peters动态入流模型、上下旋翼气动干扰分析建立了共轴式无人直升机的数学模型.然后对于高度-姿态子系统,通过扩展状态变量对其进行了动态反馈线性化,分析了零动态特性.根据内环期望跟踪特性对解耦后的子系统进行极点配置.通过设计鲁棒补偿器实现了对高度与姿态指令的鲁棒跟踪.在此基础上,针对水平面内的位置子系统设计了外环比例微分(proportional-derivative,PD)控制器以实现位置跟踪.最后,通过内环跟踪仿真验证了反馈线性化方法良好的解耦特性,通过干扰条件下的轨迹跟踪仿真验证了所设计控制器具有较好的控制性能与鲁棒性.     

Robust distributed attitude synchronization of multiple three-DOF experimental helicopters

Multiple experimental three-degrees-of-freedom (three-DOF) helicopters that are equipped with active disturbance systems constitute an attractive platform to validate robust control strategies. In this paper, a distributed synchronization controller is developed for such a platform, where each helicopter is subjected to unknown model uncertainties and external disturbances, and the desired trajectories are generated online, communicated through a network and not accessible by all helicopters. The controller is composed of a continuous tracker and a continuous uncertainty and disturbance estimator (UDE). The tracker makes the nominal closed-loop system globally asymptotically stable, and the UDE output is used to reject total uncertainties. The conditions that ensure zero-error tracking for each helicopter are identified; for the case with nonzero error, explicit relationship inequalities between the involved design parameters and the ultimate bound of error are revealed. Experimental results of four cases demonstrate improved tracking and synchronization accuracy of using the UDE with small parameters.     

卫星姿态直接自适应模糊预测控制

对具有模型不确定性和未知外干扰的卫星姿态系统提出了多输入多输出直接自适应模糊预测跟踪控制设计方法. 此方法先基于卫星姿态动力学模型设计出非线性广义预测控制律, 再构造直接自适应模糊控制器逼近预测控制律中因模型不确定性引起的未知项. 文中证明了所设计的控制律能使卫星跟踪给定的期望姿态轨迹, 跟踪误差收敛到原点的小邻域内. 仿真结果验证了此方法的有效性.     

Nonlinear adaptive model following control for a 3-DOF tandem-rotor model helicopter

This paper considers two-input, two-output nonlinear adaptive model following control of a 3-DOF (degree-of-freedom) tandem rotor model helicopter. The control performance is studied by real time implementation of the control algorithms in an actual helicopter testbed. Since the decoupling matrix of the model helicopter is singular, the system is not decouplable by static state feedback, and it is challenging to design a feedback control system. Dynamic state feedback is applied. The controller is designed using a nonlinear structure algorithm. Furthermore, a parameter identification scheme is introduced in the closed-loop system to improve the control performance. Three identification methods are discussed.     

Adaptive neural network sliding mode control of a nonlinear two-degrees-of-freedom helicopter system

The helicopter can play an important role in military and civil applications owing to its super maneuvering ability, which is closely related to its control system. To improve control performance, this study presents an adaptive sliding mode control strategy merging an adaptive neural network for a nonlinear two-degrees-of-freedom (2-DOF) helicopter system. By setting up the Lyapunov function, the asymptotic stability of the closed-loop system is guaranteed, the astringency of the neural network weight renewal course is pledged, and the asymptotic attitude adjustment and trajectory tracking for the desired set point are realized. The availability of the adaptive radial basis function sliding mode control is finally verified via the simulation and real implementation on a nonlinear 2-DOF helicopter platform.     

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.     

Adaptive Control Based on Neural Networks for an Uncertain 2-DOF Helicopter System With Input Deadzone and Output Constraints

In this paper, a study of control for an uncertain 2-degree of freedom (DOF) helicopter system is given. The 2-DOF helicopter is subject to input deadzone and output constraints. In order to cope with system uncertainties and input deadzone, the neural network technique is introduced because of its capability in approximation. In order to update the weights of the neural network, an adaptive control method is utilized to improve the system adaptability. Furthermore, the integral barrier Lyapunov function (IBLF) is adopt in control design to guarantee the condition of output constraints and boundedness of the corresponding tracking errors. The Lyapunov direct method is applied in the control design to analyze system stability and convergence. Finally, numerical simulations are conducted to prove the feasibility and effectiveness of the proposed control based on the model of Quanser's 2-DOF helicopter.      

基于H∞控制理论的2-DOF内模控制器设计及其在电力系统中的应用

给出一种基于H_∞控制理论的二自由度内模控制器设计方法.考虑了标称模型与实际模型之间存在乘性摄动时的失配性,利用适当的状态变换,将跟踪问题的控制器设计转化成一个调节问题的标准H_∞控制器设计问题,再利用H_∞输出动态反馈完成了控制器设计.以电力系统模型为例设计了一个二自由度H_∞励磁控制器,仿真结果表明了此控制器的有效性.