鲁棒递推阻尼最小二乘算法

递推最小二乘法是工程上自校正控制中常用的参数辨识方法,收敛速度快,但是存在着长期运行协方差矩阵容易爆发的问题。工业上通常采用死区等保护手段,但是会对精度产生一定的影响,并且参数调试困难。本文根据目前计算机的处理能力,提出了阻尼最小二乘法的有限时间窗口批处理递推算法,解决了传统递推最小二乘算法存在的难以克服的参数爆发现象,仿真结果验证了这个算法的有效性。     

磁悬浮电励磁三相直线同步电机离线参数辨识

建立磁悬浮电励磁三相直线同步电机(MSEETPLSM)的连续时间参数型状态空间方程数学模型,利用前向一阶差分方法将连续时间数学模型离散化成离散时间参数型状态空间方程数学模型,再利用z变换写成递推最小二乘算法标准形式的数学模型。利用递推最小二乘算法在初级转子静止状态下辨识出MSEETPLSM的电阻及自感参数。利用计算机数值仿真软件仿真MSEETPLSM参数的离线辨识算法,得到MSEETPLSM的初级与次级电阻与电感时域辨识曲线,仿真曲线收敛速度较快且辨识精度较高。仿真结果验证了该参数离线辨识算法的有效性。     

基于递推平方根法的神经网络模型辨识

提出一种基于递推平方根法的神经网络模型辨识方法,对Davidon最小二乘法和阻尼最小二乘法进行了改进,既保持了二者简单易行、收敛性的优点,又能提高精度,减少计算量,适合于应用在非线性系统的辨识和自适应控制中。与常规的Davidon最小二乘法和阻尼最小二乘法进行仿真比较,体现出了这种方法的有效性,尤其是在输入及隐含节点个数较多的情况,其优点比较明显。     

一种系统辨识的递阶算法及其在飞机颤振试飞中的应用

在研究协方差矩阵特性的基础上 ,给出一种最小二乘辨识系统的递阶算法。该算法与自回归模型参数辨识的Levinson方法相似 ,利用协方差矩阵的特性,由低阶模型参数递阶算出高一阶的参数,用阶次辨识方法确定模型阶次。避免了最小二乘系统辨识批处理方法中的高阶矩阵求逆及最小二乘系统辨识递推算法中的循环修正,提高了计算的效率。该辨识方法成功地应用于飞机颤振特性的辨识。     

基于自适应PID的异步电机电流控制

在异步电机矢量控制电流环中采用参数自适应PID算法。该算法采用带遗忘因子的递推最小二乘算法对PID参数进行在线估计,能够根据不同情况实时调整PID参数。试验结果表明,该算法鲁棒性强、稳定性好、自适应性强、计算量小,能够满足对电流控制的要求,并且提高了速度的抗干扰能力。     

石英加速度计误差模型系数的递推最小二乘辨识方法研究

为探索在线辨识的测试方法,满足实时辨识的需要,本文提出采用递推最小二乘法辨识石英加速度计模型系数,并对其在重力场测试中的应用进行了研究.介绍了递推最小二乘系数估计法原理,为便于实际应用,根据测试领域的习惯,对递推最小二乘方法进行了梳理.以加速度计分度头试验为例,将该方法应用于加速度计重力场试验的误差模型系数辨识.仿真分...     

基于最小二乘法的飞航导弹速度信息融合研究

提出了利用最小二乘法融合北斗双星定位系统和平台惯导系统的数据,估计飞航导弹的速度误差参数,用以修正惯导长时问运行产生的速度漂移,也提出了利用雷达给出的视线角和视线距信息修正惯导的速度信息.数据融合采用了线性、非线性、无限时间域递推、有限时间域递推等多种最小二乘算法,分别对它们进行了数学仿真,结果显示了该算法的有效性.     

对系统辨识误差鲁棒的自适应复合控制方法研究

对基于系统辨识的自校正控制方法来说,其控制性能极大程度受制于辨识精度。针对这一缺点,提出了将变结构模型参考自适应控制与自校正控制相结合的自适应复合控制方法。以二阶线性对象为例,首先给出了极点配置理论下的自校正控制方法,并分析了辨识误差对控制性能的影响,对这一问题,引入变结构自适应控制,并给出了自适应控制律,最后通过仿真证明了这种复合控制方法既能抑制辨识误差的影响,同时也保留了自校正控制参数调整迅速准确的优点。     

基于TD-RLS算法的四旋翼飞行器系统参数辨识

在对飞行器气动参数进行辨识的过程中,常需要对获得的数据求微分或二次微分,而利用差分法求微分会放大噪声的影响,引入滤波器抑制噪声又会产生相位延迟.针对这一问题,提出了一种跟踪微分器-递推最小二乘(TD-RLS)辨识算法.首先,建立了悬停条件下四旋翼飞行器的系统模型;然后,基于实验室四旋翼平台飞行试验实测数据,将TD-RLS算法应用于飞行器参数辨识.最终的辨识结果表明,在四旋翼飞行器悬停或者小角度飞行条件下,该方法可以实时获得比较精确的系统模型.     

多操纵面飞机气动参数在线辨识新方法研究

以多操纵面布局飞机为对象,针对其操纵面冗余造成的激励信号线性相关及控制过程中存在的信号激励不足问题,对最小二乘辨识算法进行了改进。新方法将先验经验引入在线辨识过程,可以克服弱信号输入造成的辨识不准确;采用激励-补偿机制,增加激励信号,改善了辨识结果的精度。以六自由度非线性飞机模型为对象进行的姿态控制系统仿真验证表明,当操纵面完好时,该方法能够在线修正建模误差;当飞机操纵面损伤时,该方法能够迅速反映操纵面气动参数的变化,提高了控制系统的适应性和鲁棒性。     

基于T-S模糊模型的非线性分布参数系统极点配置P-sD控制CSCD

采用Lyapunov直接法讨论分布参数系统的稳定性,建立分布参数系统的Lyapunov函数。为保证分布参数系统稳定,应使Lyapunov函数对时间的微分小于0。由于分布参数系统中存在空间一次微分项与二次微分项,Lyapunov函数对时间的微分中将出现常数项与积分项,针对常数项,引入空间一次微分项来抵消;针对积分项,引入对应的状态反馈来使系统稳定。利用边界条件量化Lyapunov函数对时间的微分中的各项,从而设计控制器,这是一种新的设计P-sD状态控制的方式。其中状态反馈的部分采用极点配置的方法来设计,当分布参数系统中出现状态变量的非线性函数时,采用T-S模糊模型表达,可以通过状态变量的线性组合精确描述非线性项,以便极点配置设计状态反馈。针对两个非线性分布参数数学模型进行仿真,结果证明设计的P-sD状态控制器可以使分布参数系统稳定,并达到期望的效果。     

Modified robust optimal adaptive control for flight environment simulation system with heat transfer uncertainty

To solve the rapid transient control problem of Flight Environment Simulation System (FESS) of Altitude Ground Test Facilities (AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structure of modified robust optimal adaptive control is presented. The mathematic modeling of FESS is given and the influence of heat transfer is analyzed through energy view. To consider the influence of heat transfer in controller design, we introduce a matched uncertainty that represents heat transfer influence in the linearized system of FESS. Based on this linear system, we deduce the design of modified robust optimal adaptive control law in a general way. Meanwhile, the robust stability of the modified robust optimal adaptive control law is proved through using Lyapunov stability theory. Then, a typical aero-engine test condition with Mach Dash and Zoom-Climb is used to verify the effectiveness of the devised adaptive controller. The simulation results show that the designed controller has servo tracking and disturbance rejection performance under heat transfer uncertainty and disturbance; the relative steady-state and dynamic errors of pressure and temperature are both smaller than 1% and 0.2% respectively. Furthermore, the influence of the modification parameter γ is analyzed through simulation. Finally, comparing with the standard ideal model reference adaptive controller, the modified robust optimal adaptive controller obviously provides better control performance than the ideal model reference adaptive controller does.     

Identification of the state-space model and payload mass parameter of a flexible space manipulator using a recursive subspace tracking method

The on-orbit parameter identification of a space structure can be used for the modification of a system dynamics model and controller coefficients. This study focuses on the estimation of a system state-space model for a two-link space manipulator in the procedure of capturing an unknown object, and a recursive tracking approach based on the recursive predictor-based subspace identification (RPBSID) algorithm is proposed to identify the manipulator payload mass parameter. Structural rigid motion and elastic vibration are separated, and the dynamics model of the space manipulator is linearized at an arbitrary working point (i.e., a certain manipulator configuration). The state-space model is determined by using the RPBSID algorithm and matrix transformation. In addition, utilizing the identified system state-space model, the manipulator payload mass parameter is estimated by extracting the corresponding block matrix. In numerical simulations, the presented parameter identification method is implemented and compared with the classical algebraic algorithm and the recursive least squares method for different payload masses and manipulator configurations. Numerical results illustrate that the system state-space model and payload mass parameter of the two-link flexible space manipulator are effectively identified by the recursive subspace tracking method.     

Adaptive Control of a Flexible Beam Using Least Square Lattice Filters

An indirect adaptive control scheme for the control of flexible structures using least square lattice filters for on-line identification of the number of modes, mode shapes, and modal amplitudes is presented. The control law is based on modal pole placement. The system requires on-line validation of the results of the identification scheme before allowing changes in control law parameters. Successful adaptive control is demonstrated using the simulations for the 12 ft free-free beam apparatus at NASA Langley Research Center.     

涡轴发动机自适应非线性预测控制

为了实现当直升机旋翼负载变化时,尽量保持功率涡轮转速恒定,并提高系统动态品质,研究了一种针对涡轴发动机的自适应非线性预测控制(ANMPC)算法.基于涡轴发动机稳态数据和动态特性,采用递归最小二乘法(RLS)进行模型参数辨识,建立了具有在线自适应能力的涡轴发动机数值-ARX(auto regressive with external input)并联预测模型.在此基础上,通过多步输出预测和反馈校正,利用序列二次型优化(SQP)算法,进行在线滚动优化,从而获得了涡轴发动机ANMPC控制器.仿真结果表明:当旋翼负载变化时,相比于传统的串联PID(比例-积分-控制)控制器,ANMPC控制器能够使得功率涡轮转速收敛更快,超调量/下垂量更小.      

一种适用于飞行器控制系统的快速时变参数辨识方法

 在自适应控制中,特别在飞行器控制系统中,经常会遇到快速时变参数的辨识问题,这是一个比较困难的问题。本文利用折线段近似时变参数,根据最小二乘原理导出了一种计算比较简单、辨识精度较高的快速时交参数辨识方法。文中对反坦克导弹和地空导弹等快速时变系统进行了数学模拟.其结果表明,这种辨识方法不仅适用于连续快速时变系统,而且在参数变化存在第二类间断点时,仍有较好的辨识结果。     

Application of neural networks for the design of flight control algorithms. II Adaptive tuning of neural network control law

In this paper, we consider different approaches for the neural network controller tuning in the flight control system. Two of the most common tuning approaches in the adaptive control theory are applied. The first one uses parameter identification technique and consists in solving a real-time regression problem for the control law. The second approach is based on the Lyapunov direct method, which utilizes a tracking error as an absolute measure of tuning performance. The neural network control law are designed for the three-axis flight control problem and tested on the full nonlinear model of a fighter aircraft. Closed loop simulation results are presented and two adaptation algorithms are compared in the case of abrupt change of aircraft dynamics.