自主空中加油时变质量无人作战飞机非线性控制

针对自主空中加油中无人作战飞机(UCAV)位置保持问题, 进行了时变质量UCAV的动力学建模与非线性控制设计. 综合考虑了燃油传输对UCAV的质量、惯性矩阵和质心位置的影响, 基于相对于惯性系的状态变量, 推导了UCAV时变质量动力学方程. 通过引入谱半径, 将局部化自适应边界指令滤波反推方法应用于UCAV的位置保持控制. 使用逼近器对未知模型不确定性进行在线逼近. 对于固有逼近误差和外部扰动, 采用局部化自适应边界进行补偿. 通过指令滤波反推, 设计了相对位置、速度、姿态角和角速度四个反馈回路来保证UCAV的稳定性. 最后, 三种不同加油方案下的非线性仿真验证了非线性飞行控制律的有效性.     

基于非线性干扰观测器的高超声速飞行器滑模反演控制

针对高超声速飞行器非线性、强耦合和参数不确定弹性体模型,提出了一种基于非线性干扰观测器的滑模反演控制方法.将飞行器曲线拟合模型分解为速度子系统和高度相关子系统并表示为严格反馈形式,分别采用滑模和反演方法设计实际控制量与虚拟控制量.采用1阶低通滤波器获取虚拟控制量的导数,解决了传统反演控制方法"微分项膨胀"问题.基于改进滑模微分器设计了一种新型非线性干扰观测器,以此对模型不确定项进行估计和补偿.仿真结果表明,该控制器对模型不确定性和气动弹性影响具有鲁棒性,且实现了对速度和高度参考输入的稳定跟踪.     

基于非线性干扰观测器的翼伞鲁棒反步跟踪控制

针对干扰条件下的无人翼伞飞行器路径跟踪控制问题,提出一种基于非线性干扰观测器的反馈增益鲁棒反步控制方法.采用二阶跟踪-微分器设计干扰观测器对系统复合干扰进行估计和补偿,设计了反馈增益反步跟踪控制律,通过合理设计增益参数,消除了部分复杂非线性项,避免了虚拟量高阶导数问题,简化了控制器形式.根据Lyapunov理论设计鲁棒反馈补偿项,在保证稳定性的同时提高了系统的鲁棒性.仿真实验结果验证了所提出方法的有效性.     

逐点线性化后退区间最优控制在飞机非线性控制中的应用

常规线性飞控系统针对推力矢量飞机这样的多控制冗余、非线性MIMO系统,无法实现非线性控制．本文针对推力矢量飞机非线性系统,阐述了一种逐点线性化后退区间最优控制算法满足飞行品质要求．首先将作动器,飞行品质和逐点线性化的飞机线性模型综合实现在线建模,然后以飞行状态与预测状态之间的误差、作动器的位置限制和速率限制作为最优指标,最后以此为基础,根据最优控制原理计算当前时刻飞机最优控制指令,实现飞机非线性控制．采用国内某型号飞机气动数据验证此算法的鲁棒性和稳定性．     

基于反馈增益反步法欠驱动无人水下航行器三维路径跟踪控制

针对欠驱动无人水下航行器的三维空间路径跟踪控制问题.基于虚拟向导建立载体坐标系下的三维路径跟踪运动学误差模型,首先设计跟踪误差反馈增益形式的线性控制项镇定位置跟踪系统,避免计算虚拟控制量导数的复杂形式;然后基于反步法设计动力学控制器,通过合理的选择控制器参数消除了部分非线性项,简化了虚拟控制量的形式,同时避免了采用传统反步法设计控制器时存在的奇异值问题,基于李雅普诺夫稳定性理论设计鲁棒反馈补偿项,保证了闭环跟踪误差系统状态的一致最终有界.仿真实验表明本文设计控制器能够精确跟踪三维曲线路径,并对外界干扰具有较好的鲁棒性.     

一类高超声速飞行器自适应容错控制器设计

高超声速飞行器控制系统具有非常突出的强耦合、强非线性、时变的力学特性,在其研究与设计过程中,需要处理高速飞行带来的弹性形变、多输入多输出、气动参数不确定以及高温高热等原因导致的各种传感器故障和部分作动器故障等一系列问题,因此该类飞行器控制系统的研究与设计面临着传统飞行器控制系统研究所未有的困难和挑战.针对高超声速飞行器飞行过程中遇到的部分作动器故障问题,本文提出了非线性观测器与控制器一体化设计的高超声速飞行器自适应反演容错控制方法.首先将飞行器作动器故障模型转换为一类状态不能完全测量,且具有未知参数和未知控制增益的SISO输出反馈非线性最小相位系统,然后,基于改进的K-滤波器理论对状态向量进行重构,在系统只有输出可以测量的情况下,设计了一种新型观测器,确定出收敛的状态向量,设计出强自适应能力的控制器,保证了系统所有信号的有界性.在自适应反演设计时,采用动态面设计方法,引入一阶滤波器,得到虚拟控制量的微分,消除传统反演设计中的"项数膨胀"问题,用Lyapunov稳定性定理保证误差一致有界.仿真实验验证了该算法的有效性.最后以高超声速飞行器纵向通道为例,验证了上述理论.     

基于滤波反步法的欠驱动AUV三维路径跟踪控制

研究了欠驱动自主水下航行器 (Autonomous underwater vehicle, AUV)的三维空间路径跟踪控制问题.针对基于虚拟向导建立的三维路径跟踪误差模型, 采用滤波反步法设计跟踪控制器,通过二阶滤波过程获得虚拟控制量的导数, 避免了直接对虚拟控制量解析求导的复杂过程, 同时滤除了高频测量噪声, 增加了系统对噪声的鲁棒性.通过设计滤波误差补偿回路, 保证了滤波信号对虚拟控制量的逼近精度.基于李雅普诺夫稳定性理论设计鲁棒项, 保证了闭环跟踪误差系统状态的渐近稳定.仿真结果表明了该控制器对噪声干扰具有一定的鲁棒性, 能够实现对三维路径的精确跟踪.     

基于径向基神经网络的压电作动器建模与控制

针对压电作动器(piezoelectric actuator,PEA)的率相关迟滞非线性特性,构建了Hammerstein模型对压电作动器建模.采用径向基(radial basis function,RBF)神经网络模型表征迟滞非线性,利用自回归历遍模型(auto-regressive exogenous,ARX)表征频率的影响,并对模型参数进行了辨识.此模型可以在信号频率在1～300 Hz范围内时,较好地描述压电作动器的迟滞特性,建模相对误差为1.99%～4.08%.采用RBF神经网络前馈逆补偿控制,结合PI反馈的复合控制策略实现跟踪控制,控制误差小于2.98%,证明了控制策略的有效性.     

模块化反步自适应大机动飞行控制

针对飞机大机动飞行时模型非线性和参数不确定性的特点,提出一种输入状态稳定反步自适应控制的模块化设计方法.基于模块化设计思想,设计一个输入状态稳定的反步控制器,保证在输入有界情况下系统状态的有界特性.基于最小二乘算法设计参数自适应律和滤波器的辨识器模块,保证独立于输入状态稳定控制器之外的参数误差及其导数有界,并利用一种基于免疫克隆原理的改进粒了群算法优化固定参数,改善动态性能.仿真结果表明了所提出算法的有效性.     

襟翼机电作动器的非线性跟踪控制器设计

针对存在未知扰动的民机襟翼机电作动器,为了实现位置跟踪控制,提出了一种新型的非线性连续鲁棒控制器.利用反向递推理论对非线性连续鲁棒控制器进行了设计.首先通过设计电流虚拟控制量,对未知机械扰动进行了补偿;其次,利用电流虚拟控制量,设计了控制电压,实现了对未知扰动信号的抑制.根据李雅普诺夫稳定性分析方法,论证了在所设计的控制器作用下,受控机电作动器能够实现对参考轨迹的全局渐进跟踪.仿真结果表明,改进控制器能够有效提高机电作动器的位置跟踪控制性能,控制效果优于PID控制.     

Estimation and coordinated control for distributed parameter processes with a moving radiant actuator

This paper presents an estimation and control scheme for a class of industrial processes described by distributed parameter models with a moving radiant actuator. To overcome the lack of direct sensing alternatives for process state, a dual extended Kalman filter is established for estimating process status online based on a reduced process model and available output measurements. A distinct challenge that is addressed is the selection and construction of a suitable feedback signal from the distributed state estimate following the moving radiant actuator. The estimated status is then integrated into a rule-based feedback controller, which coordinates two manipulated variables of the moving radiant actuator to achieve the control objective. The two manipulated variables are the velocity and the radiant flux or power of the moving actuator. Both the estimation and feedback control strategies are demonstrated using computer simulations of one-dimensional distributed parameter models for an ultraviolet (UV) coating curing process involving a moving UV source. The results show that the proposed estimation and control schemes can significantly improve process quality and compensate for unknown disturbances on the target.     

基于生物启发模型的欠驱动水平TORA系统的有界输入镇定控制

针对欠驱动水平TORA(translational oscillators with rotating actuator)系统,提出一种基于生物启发模型的有界输入控制方法,实现系统在执行器存在饱和约束情况下的镇定控制.首先,根据水平TORA系统的动力学模型分析系统的无源特性,进而给出系统的控制目标;接着,基于无源特性构造一种新颖的Lyapunov函数,在此基础上设计一种结构简单的非线性状态反馈控制器;然后,考虑执行器的饱和约束条件,引入受生物启发建立的神经动力学模型,利用该模型的有界平滑输出特性,设计一种改进的状态反馈控制器;最后,根据LaSalle不变性原理对系统的稳定性进行严格的数学分析和证明.与其他方法相比,所提方法不仅考虑了执行器的饱和约束问题,而且设计的控制算法简单高效,易于工程实现.仿真与对比结果表明,所提方法具有更好的控制性能.     

Fuzzy Control for Nonlinear Uncertain Electrohydraulic Active Suspensions With Input Constraint

This paper presents a Takagi-Sugeno (T-S) model-based fuzzy control design approach for electrohydraulic active vehicle suspensions considering nonlinear dynamics of the actuator, sprung mass variation, and constraints on the control input. The T-S fuzzy model is first applied to represent the nonlinear uncertain electrohydraulic suspension. Then, a fuzzy state feedback controller is designed for the obtained T-S fuzzy model with optimized H _infin performance for ride comfort by using the parallel-distributed compensation (PDC) scheme. The sufficient conditions for the existence of such a controller are derived in terms of linear matrix inequalities (LMIs). Numerical simulations on a full-car suspension model are performed to validate the effectiveness of the proposed approach. The obtained results show that the designed controller can achieve good suspension performance despite the existence of nonlinear actuator dynamics, sprung mass variation, and control input constraints.     

线性离散时滞系统的D稳定容错控制

采用状态反馈和带时滞的状态反馈控制律,基于Lyapunov稳定性理论和Riccati方程,针对线性离散一步时滞系统,研究了执行器失效后有一定性能保证的D稳定容错控制问题。在给出对执行器失效具有完整性的D稳定容错控制系统需满足的一个充分条件的基础上,给出了控制器的设计方法和步骤,并推广至传感器失效情况。仿真结果证实了这种方法的有效性,与仅引入状态反馈控制律相比,此方法有更好的动态响应性能。最后指出了时滞状态反馈增益矩阵的选取原则。     

Control of discrete-time systems with actuator non-linearities: An LMI approach

This paper considers the problem of stabilization of discrete-time systems with actuator non-linearities. Specifically, full-state feedback and dynamic, output feedback control designs for discrete-time systems with time-varying, sector-bounded, input non-linearities are addressed. The proposed framework is based on a linear matrix inequality approach and directly accounts for robust stability and robust performance over the class of actuator non-linearities. Furthermore, it is directly applicable to actuator saturation control and provides state feedback and dynamic, output feedback controllers with guaranteed domains of attraction. The effectiveness of the approach is illustrated by two numerical examples.     

Adaptive stabilization for ODE systems via boundary measurement of uncertain diffusion‐dominated actuator dynamics

This paper is concerned with the adaptive stabilization for the ODE systems via boundary measurement of uncertain diffusion‐dominated actuator dynamics. It is worth pointing out that, in the related works, all the states of the diffusion‐dominated actuator are required to be measurable, and this means that an infinite number of sensors are needed to implement the controllers, which is impossible in practice. Quite differently in this paper, only one boundary state of the diffusion‐dominated actuator is measurable and available for feedback design. Moreover, the actuator dynamics contains parameter unknown. Motivated by the existing results, a state observer is first designed to estimate the unmeasurable actuator states, which consists of an input filter and an output filter. Then, by introducing an infinite‐dimensional backstepping transformation, a pivotal target system is obtained from which it is more convenient to design controller and analyze the performance of the original system. Finally, an adaptive controller is constructed by adaptive technique and Lyapunov method, which guarantees that the states of the original system converge to zero, whereas the other states of the closed‐loop system keeping bounded. A simulation example is provided to illustrate the effectiveness of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

预测增量动态逆无人机姿态控制

针对小型无人机模型参数精度不高的问题,提出一种预测增量动态逆姿态控制方法。该方法以角加速度作为姿态控制的反馈,从而降低了控制系统对模型参数的敏感性。根据无人机力矩方程,先将角加速度计算式写成增量形式;再根据非线性动态逆方法构建出角加速度为隐式输入、舵面偏转量增量为输出的直接关系式;在控制器中引入预测滤波器,对角加速度进行滤波和预测,提高反馈信号的精度和实时性。飞行实验表明方法是有效性的。     

State feedback design for nonlinear quadratic systems with randomly occurring actuator saturation

This paper is concerned with the problem of state feedback control for nonlinear quadratic systems with randomly occurring actuator saturation. The considered actuator saturation is assumed to occur in a random way, and the randomly occurring rates of the saturation are time-varying with known upper and lower bounds. By using the Lyapunov approach, a sufficient condition is given to guarantee that the closed-loop system is locally asymptotically stable in mean-square sense. The desired controller gain can be obtained in terms of the solutions to certain linear matrix inequalities. Finally, a simulation example is provided to show the effectiveness of the proposed control scheme.     

Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults

In this paper, a distributed output feedback consensus tracking control scheme is proposed for second-order multi-agent systems in the presence of uncertain nonlinear dynamics, external disturbances, input constraints, and partial loss of control effectiveness. The proposed controllers incorporate reduced-order filters to account for the unmeasured states, and the neural networks technique is implemented to approximate the uncertain nonlinear dynamics in the synthesis of control algorithms. In order to compensate the partial loss of actuator effectiveness faults, fault-tolerant parts are included in controllers. Using the Lyapunov approach and graph theory, it is proved that the controllers guarantee a group of agents that simultaneously track a common time-varying state of leader, even when the state of leader is available only to a subset of the members of a group. Simulation results are provided to demonstrate the effectiveness of the proposed consensus tracking method.     

基于时滞状态反馈的鲁棒容错控制

研究了一类线性不确定时滞系统的鲁棒容错控制问题。针对具有状态滞后,且假定状态和控制输入的不确定项均是范数有界的线性系统,基于Lyapunov稳定性理论和线性矩阵不等式方法,通过引入状态反馈和带时滞的状态反馈,得出了一个此类系统在对执行器失效或传感器失效两种情况下具有鲁棒容错性能的充分条件,并通过求解线性矩阵不等式组得到容错控制器设计结果。数值算例验证了这种控制器的设计方法的有效性和可行性。