TF/TA trajectory tracking using nonlinear predictive control approach

The use of a methodology of nonlinear continuous predictive control to design the guidance control law for the aircraft TF/TA² trajectory tracking problem is emplojed. For the derivation of the predictive control law, by using Taylor series expansion, and based on optimizing a performance index which is a quadratic function of both the predictive value of the state variables and the control inputs, a state variable feedback controller for nonlinear systems is obtained, and it provides a tradeoff between satisfactory tracking performance and the control magnitude requirements. Numerical simulation results for a supersonic fighter aircraft model show the viability of this approach.     

基于扰动观测器的飞行器轨迹跟踪控制器设计

针对多种扰动作用下的固定翼飞行器三维轨迹跟踪问题, 设计了一种基于改进非线性扰动观测器的非奇异快速终端滑模轨迹跟踪控制器。首先推导固定翼飞行器三维轨迹跟踪误差模型, 考虑模型误差和飞行过程中的未知扰动, 设计了一种基于状态估计误差反馈的非线性扰动观测器对扰动进行观测。基于非奇异快速终端滑模控制方法, 采用双幂次趋近律设计轨迹跟踪控制器, 并证明了闭环控制系统的稳定性。仿真结果表明, 在多种扰动的作用下, 所设计的轨迹跟踪控制器能够对三维机动轨迹进行准确、稳定的跟踪。     

基于NDO的飞机轨迹跟踪抗干扰控制律设计

针对飞机纵向欠驱动耦合动力学模型设计鲁棒轨迹跟踪滑模控制律。首先,通过引入虚拟状态变量进行状态变换实现模型控制解耦。其次,考虑由系统建模误差和大气干扰组成的复合不确定性,设计非线性干扰观测器(nonlinear disturbance observer, NDO)进行观测补偿。然后,建立飞机极短距起降中攻角变化轨迹曲线,设计滑模控制律实现对虚拟状态变量和攻角轨迹指令的稳定跟踪。仿真结果表明,NDO可以实现对系统不确定性的精确观测和补偿,滑模控制律具有对系统建模误差和大气风切变的鲁棒性和抗干扰性。     

飞行器栖落机动切换控制设计及其吸引域计算

针对固定翼无人机栖落过程的纵向运动,研究栖落轨迹跟踪控制问题及其相应的吸引域计算方法。首先将飞行器栖落机动过程的动力学模型沿参考轨迹线性化,并建立分段线性切换系统模型。在此基础上,结合最优控制理论与切换系统全局稳定分析方法,设计了栖落轨迹跟踪切换控制律。然后,为确定局部稳定区域从而保证飞行器能在预期时间内准确地栖落在目标区域,设计相应的平方和优化算法,计算了切换控制下的栖落轨迹吸引域。最后,对固定翼飞行器的栖落过程进行了仿真,仿真结果验证了所设计的跟踪控制器的有效性与所计算的吸引域的正确性。     

机器人轨迹跟踪连续预测控制

针对能够描述机械手动态特性的一类特殊仿射非线性系统 ,提出了一种非线性连续预测控制器。其预测模型通过对系统状态泰勒级数展开并做适当的截尾处理获得。此外 ,证明了非线性连续预测控制器的渐近跟踪特性 ,并给出了一种改进的预测控制方案。将非线性连续预测控制器应用于二自由度机械手轨迹跟踪控制。仿真结果证明了该控制器的有效性     

Study on robust terrain following control

1.INTRODUCTION Terrainfollowing(TF)isanimportanttechnology formodernaircraftsuperlowaltitudepenetration flights.Iteffectivelymakesuseofinterferenceand deadzonesinenemydefensesystemscreatedbystray groundwavesandterrainundulations,raisingaircraft survivalcapabilities.Manymethodsareusedinair craftsuchasadaptiveanglemethodinF 111andB 1, templatemethodin“Tornado”and“Mirage2000” etc.TFtechnologyisalsousedincruisemissilessuch as“Tomahawk”.Aerodynamicnonlinearitiesandthe uncertaintiesof…     

飞机拦阻系统非线性控制仿真分析

针对飞机拦阻系统采用非线性控制进行了机构实现分析,利用状态反馈线性化及线性系统二次性能指标最优控制设计方法设计了非线性控制规律。建立了跟踪控制飞机位移及速度的非线性控制仿真模型,针对系统参数变化及飞机撞网速度测量值有偏差状况,进行了鲁棒性仿真分析,仿真结果表明:采用非线性控制,系统动态响应快,跟踪特性好,鲁棒性强,拦阻指标容易满足。     

基于广义卡尔曼滤波的飞机防滑刹车变结构控制

飞机防滑刹车控制的关键是控制机轮的滑移率，为了使机轮工作在最佳滑移率，得到最大结合系数，提出了一种基于滑移率控制的防滑刹车变结构控制律。由于飞机滑跑时的真实速度很难测量，为此采用广义卡尔曼滤波器得到飞机刊车系统非线性模型的状态估计，状态估计值作为防滑刹车控制器的输入。计算机仿真结果显示该控制律改善了飞机的防滑刹车性能，具有较强的鲁棒性。     

临近空间高超声速飞行器机动模型及弹道预测

讨论了临近空间轴对称高超声速机动飞行器的跟踪及弹道预测问题。通过引入3个与气动力参数相关的状态变量,建立起一种非线性机动模型,并证明了基于该模型的非线性跟踪系统的可观性。针对此非线性跟踪系统,设计了扩展卡尔曼滤波器以及状态预报器,实现弹道跟踪和预测。仿真结果表明,对于临近空间飞行器在巡航末段的运动状态,采用所提出的机动模型,可以取得优良的跟踪和预测效果。     

Transient Performance Improvement in Tracking Control for a Class of Nonlinear Systems with Input Saturation

This paper addresses the composite nonlinear feedback (CNF) control for a class of singleinput single-output nonlinear systems with input saturation to track a time varying reference target with good transient performance. The CNF control law consists of a tracking control law and a performance compensator. The tracking control law is designed to drive the output of the system to track the time varying reference target rapidly, while the performance compensator is used to reduce the overshoot caused by the tracking control law. The stability of the closed-loop system is established. The design procedure and the improvement of transient performance of the closed-loop system are illustrated with a numerical example and the controlled Van del Pol oscillator.     

欠驱动VTOL空间飞行器系统的非线性跟踪控制

研究了欠驱动VTOL(垂直上升和垂直着陆)空间飞行器在各种输入耦合时的非线性跟踪控制问题。VTOL空间飞行器是具有三个自由度,两个控制输入的欠驱动系统。首先,通过控制输入和坐标变换,系统的动力学方程被变换成二阶链式形式。其次,利用后推法(backstepping)的思想推导出保证系统渐近收敛于给定轨迹的时变反馈控制规律。该方法将系统分解为低阶子系统来处理,利用中间虚拟控制变量和部分Lyapunov函数简化了控制器的设计。仿真结果证明了所设计控制器的有效性。     

考虑舵面饱和的鲁棒可重构控制律设计及仿真

针对常规显式非线性动态逆控制鲁棒性差的问题,综合隐式动态逆和奇异摄动分层设计,引入状态速率(导数)和操纵面的当前位置信号的反馈,设计鲁棒动态逆控制律,不需要完整的飞机气动力模型,敏感度降低.利用过栽测量信号采用几何的方法,构建角加速度信号,其它状态速率信号,基于飞机动力学方程求解得到.同时采用自适应权矩阵和多级舵面操纵分配策略,降低舵面速率/位置饱和.控制律结构简单,当飞机存在外形损伤、舵面或传感器失效时,能够迅速实现测量信号的隔离、反馈信号的重建和控制的重新分配和控制律重构.针对某型飞机建立高准确度的仿真模型,计算结果表明在存在气动力摄动、测量偏差干扰,噪声和舵面限制等的情况下,控制律具有良好的鲁棒性.     

Nonlinear Model Predictive Control-Based Guidance Algorithm for Quadrotor Trajectory Tracking with Obstacle Avoidance

This paper studies a novel trajectory tracking guidance law for a quadrotor unmanned aerial vehicle(UAV) with obstacle avoidance based on nonlinear model predictive control(NMPC)scheme. By augmenting a reference position trajectory to a reference dynamical system, the authors formulate the tracking problem as a standard NMPC design problem to generate constrained reference velocity commands for autopilots. However, concerning the closed-loop stability, it is difficult to find a local static state feedback to construct the terminal constraint in the design of NMPC-based guidance law. In order to circumvent this issue, the authors introduce a contraction constraint as a stability constraint, which borrows the ideas from the Lyapunov's direct method and the backstepping technique. To achieve the obstacle avoidance extension, the authors impose a well-designed potential field function-based penalty term on the performance index. Considering the practical application, the heavy computational burden caused by solving the NMPC optimization problem online is alleviated by using the dynamical adjustment of the prediction horizon for the real-time control. Finally, extensive simulations and the real experiment are given to demonstrate the effectiveness of the proposed NMPC scheme.     

超机动飞行的非线性鲁棒自适应控制系统研究

针对飞机模型中存在气动参数不确定性以及外界干扰等影响因素,设计了一种超机动飞行的非线性鲁棒自适应控制系统。控制系统设计过程中,模型不确定性和外界干扰由RBF神经网络在线补偿,控制律及神经网络权值自适应律由反步法得到。解决了系统中控制增益矩阵未知,同时存在外界干扰情况下的鲁棒飞行控制系统设计,并证明了闭环系统所有信号有界,系统跟踪误差和神经网络权值估计误差指数收敛到有界紧集内。对所研究的飞行控制系统进行了过失速Herbst机动仿真,结果验证了该系统在过失速机动条件下具有良好的控制性能。     

基于鲁棒模型预测的智能汽车轨迹跟踪控制研究

针对传统的基于跟踪误差模型轨迹跟踪控制器在复杂行驶环境下控制精度不高,鲁棒性差等问题,设计一种鲁棒模型预测轨迹跟踪控制策略。采用车辆凸多胞体动力学模型显式描述车辆动态特性,结合轨迹跟踪多目标约束设计鲁棒性目标函数,通过线性矩阵不等式优化方式求解状态反馈控制律;引入前馈控制消除稳态误差,提高跟踪精度。结果表明:在不同行驶工况下,该控制器在保证车辆跟踪精度基础上可有效提高行驶稳定性,具有较强的鲁棒性。     

多变量非线性系统的直接自适应模糊预测控制

对一类多变量非线性系统提出了直接自适应模糊预测控制方法,此方法首先对被控对象提出了线性时变子模型加非线性子模型的预测模型,然后直接利用模糊系统设计预测控制器,并基于时变增益自适应律对控制器中的未知向量和逼近误差估计值进行自适应调整。证明了此方法可使跟踪误差收敛到原点的一个邻域内,仿真结果验证了此方法的有效性。     

Output Tracking for One-Dimensional Wave Equation with Non-Collocated Control and Output Configuration

This paper considers output tracking for a one-dimensional wave equation with general disturbance which includes both internal nonlinear uncertainty and external disturbance. The performance output is non-collocated to the control. The disturbance is estimated by an essentially extended state observer from active disturbance rejection control and the difficulty caused by the non-collocated configuration of control and output is overcome by a proper trajectory planning. An output feedback law is proposed to make the tracking error be convergent to zero exponentially as time goes to infinity.At the same time, all states of the closed-loop system are shown to be uniformly bounded. Numerical simulation is also presented to validate the theoretical results.     

基于H∞鲁棒动态逆的飞行器轨迹跟踪方法

利用非线性动态逆方法的精确线性化功能,结合H_∞控制理论,提出了一种阻力加速度能量标准轨迹的跟踪方法。通过动态逆将非线性的高超声速飞行器系统等效为线性对象,继而考虑非结构不确定性及参数不确定性,采用H_∞控制理论设计外回路鲁棒控制器,实现了标准轨迹的精确跟踪,同时给出了闭环系统的鲁棒稳定性证明。仿真结果验证了该方法的有效性。     

基于零化视线角速率的非线性预测制导律

利用非线性预测控制理论设计了一种零化视线角速率的预测制导律. 首先, 以弹目视线角速率为反馈项, 最小化预测误差为性能指标, 基于非线性预测控制理论和最优化理论推导出非线性预测制导律, 并对闭环回路的稳定性进行了证明. 其次, 针对制导律中含有的目标机动项信息, 设计了一种基于时间延迟控制理论的滤波算法, 并应用于预测制导律, 最后仿真考虑到导弹的延迟环节, 采用三阶自动驾驶仪模型, 验证了设计的制导律能够有效拦截机动目标, 与传统比例导引相比, 视线角速率变化平稳, 克服了末端视线角速率变化过快而导致过载饱和的情况, 降低了对执行机构的要求.     

Adaptive functional link network control of near-space vehicles with dynamical uncertainties

The control law design for a near-space hypersonic vehicle (NHV) is highly challenging due to its inherent nonlinearity, plant uncertainties and sensitivity to disturbances. This paper presents a novel functional link network (FLN) control method for an NHV with dynamical thrust and parameter uncertainties. The approach devises a new partially-feedback-functional-link-network (PFFLN) adaptive law and combines it with the nonlinear generalized predictive control (NGPC) algorithm. The PFFLN is employed for approximating uncertainties in flight. Its weights are online tuned based on Lyapunov stability theorem for the first time. The learning process does not need any offline training phase. Additionally, a robust controller with an adaptive gain is designed to offset the approximation error. Finally, simulation results show a satisfactory performance for the NHV attitude tracking, and also illustrate the controller's robustness.