Optimal trajectory design accounting for the stabilization of linear time-varying error dynamics

This study is dedicated to the development of a direct optimal control-based algorithm for trajectory optimization problems that accounts for the closed-loop stability of the trajectory tracking error dynamics already during the optimization. Consequently, the trajectory is designed such that the Linear Time-Varying(LTV) dynamic system, describing the controller’s error dynamics, is stable, while additionally the desired optimality criterion is optimized and all enforced constraints on the traje...     

Modeling and parameter identification of linear time-varying systems based on adaptive chirplet transform under random excitation

In this paper, a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying (LTV) systems under random excitation is presented. It is assumed that the solution of responses of LTV structures is expressed as the sum of multicomponent Linear Frequency Modulated (LFM) signals in a short-time. Then the measured acceleration response is used to perform the adaptive chirplet transform, in which an integral algorithm is employed to reconstruct the velocity and displacement responses. The vibration differential equation with time-varying coefficients is transformed into a simple linear equation. Furthermore, for systems under random excitation, the input–output relation based on correlation function is also derived to estimate the parameters including physicals parameters and instantaneous modal parameters. The full procedure of the method is presented and validated by using simulated responses. The results show that the presented method is accurate and robust for various LTV systems under random excitation.     

Indirect Radau pseudospectral method for the receding horizon control problem

To solve the receding horizon control (RHC) problem in an online manner, a novel numerical method called the indirect Radau pseudospectral method (IRPM) is proposed in this paper. Based on calculus of variations and the first-order necessary optimality condition, the RHC problem for linear time-varying (LTV) system is transformed into the two-point boundary value problem (TPBVP). The Radau pseudospectral approximation is employed to discretize the TPBVP into well-posed linear algebraic equations. The resulting linear algebraic equations are solved via a matrix partitioning approach afterwards to obtain the optimal feedback control law. For the nonlinear system, the linearization method or the quasi linearization method is employed to approximate the RHC problem with successive linear approximations. Subsequently, each linear problem is solved via the similar method which is used to solve the RHC problem for LTV system. Simulation results of three examples show that the IRPM is of high accuracy and of high compu-tation efficiency to solve the RHC problem and the stability of closed-loop systems is guaranteed.     

2-D奇异系统鲁棒稳定性的状态空间测度

考虑具有非结构摄动的2-D奇异系统Roesser模型(简称2-DSRM)鲁棒稳定性的状态空间测度问题.利用其容许、稳定的充要条件及矩阵的奇值分解,分析其鲁棒稳定性,给出了不破坏2-D奇异系统稳定的摄动的最大上界.     

A Discrete Method for Parameter Identification in Linear Systems with Transport Lags

Linear dynamical systems with transport lags are characterized by linear differential-difference equations. The task of identifying unknown parameters in such systems from the input-output data is difficult due to mathematical complications associated with differentialdifference equations. This paper presents a method which solves the identification problem. The method is digitally oriented and shows how a continuous-time system can be identified by discrete techniques. The solution is based on Kalman's least square method. The identification procedure essentially involves two steps: 1) discretizing the continuous system via finite difference approximation, and 2) estimating the parameters through the identification of the resulting discrete model. Experimental results have verified the validity of the proposed method.     

Optimal filtering for systems with finite-step autocorrelated noises and multiple packet dropouts

This paper addresses the optimal filtering problem for a class of uncertain dynamical systems with multiple packet dropouts and finite-step correlated observation noises. By rearranging the stochastic terms in the transmission and measurement matrices of the dynamical system into the noises directly, the process noises and observation noises in resulted system depend on the state as well as the stochastic uncertain perturbations, and are not only autocorrelated respectively but also cross-correlated. For this complicated dynamical system, instead of designing a Kalman-type filter, a globally optimal filtering in the minimum mean square error sense is developed by exploiting sufficiently the statistical properties of correlated noises. Numerical simulation is provided to demonstrate the performance of the proposed filter.     

一阶滞后对象广义预测控制下的闭环稳定性分析

 利用参数模型和非参数模型相结合的方法,给出了一阶滞后对象在广义预测控制下闭环稳定的充要条件。发现:(1)对开环稳定的一阶滞后对象,总存在一组控制器参数,使得在该控制器控制下,无论对象的开环增益K与时间常数T如何变化,闭环系统都保持稳定;(2)对于开环不稳定的一阶滞后对象,无论控制器参数如何选取,当K和T的变化超出一定范围时,闭环系统就会失去稳定性。     

挤压油膜阻尼器-滑动轴承-转子系统非线性动力特性的数值分析及实验研究

 采用非线性模型,研究挤压油膜阻尼器 -滑动轴承 -转子系统的运动稳定性和分岔特性。利用有限元离散变分不等原理和基于线性规划余原理的迭代方法,求解自由边值条件下的油膜力。采用模态综合技术中的缩减系统线性自由度的方法,并提出基于 Newmark法的预估 -校正 -局部迭代的方法,求解系统响应。采用 Poincaré映射法,将周期解的确定转化为 Poincaré截面上不动点的确定,然后分析不动点的稳定性。最后通过实验转子,从实验与数值计算进行对比分析,验证了挤压油膜阻尼器的减振特性及其提高系统运动稳定性的特性,同时也说明了上述方法可以有效地分析这类系统的局部非线性动力特性。     

非线性广义时变时滞系统鲁棒模糊控制

针对一类参数不确定模糊广义时变时滞系统,研究该系统的鲁棒稳定性控制问题。选取特殊的Lyapunov函数,给出了该系统稳定的充分条件,采用线性矩阵不等式技术,将时变时滞系统稳定性条件转化为求解一组线性矩阵不等式问题,并设计出状态反馈控制器,仿真结果说明该方法的可行性。     

Aircraft nonlinear stability analysis and multidimensional stability region estimation under icing conditions

Icing is one of the crucial factors that could pose great threat to flight safety,and thus research on stability and stability region of aircraft safety under icing conditions is significant for control and flight.Nonlinear dynamical equations and models of aerodynamic coefficients of an air craft are set up in this paper to study the stability and stability region of the aircraft under an icing condition.Firstly,the equilibrium points of the iced aircraft system are calculated and analyzed based on the theory of differential equation stability.Secondly,according to the correlation theory about equilibrium points and the stability region,this paper estimates the multidimensional stability region of the aircraft,based on which the stability regions before and after icing are compared.Finally,the results are confirmed by the time history analysis.The results can give a reference for stability analysis and envelope protection of the nonlinear system of an iced aircraft.     

高机动性飞机大迎角全局稳定性研究

为了研究高机动性飞机大迎角时的全局稳定性,建立了飞机的非线性动力学方程和气动力模型。应用微分方程定性理论,通过对算例的分析,讨论了目前飞机设计中常用的稳定性判据(如(C_(nβ))_(dyn)和LCDP等)与平衡点处线化矩阵特征值之间的关系。结果表明这些判据可以从飞机在特定状态下的线化矩阵经简化得到。因此,它们只能预测大迎角的局部稳定性。若考虑全局稳定性则必须用本文所给的方法进行。最后,指出了平衡点和周期吸引子与机翼摇晃、偏离和尾旋之间的关系,并用时间过程作了验证。     

自适应广义预测控制系统的鲁棒稳定性分析

研究当被控对象具有未建模动态、参数时变、非线性以及有界干扰时,自适应广义预测控制系统的鲁棒稳定性。提出了分析和设计鲁棒自适应广义预测控制系统的一般理论和方法。给出了一类满足弱化鲁棒稳定性条件的鲁棒参数自适应算法,并根据确定性等价原理将它和鲁棒广义预测控制律结合,建立了鲁棒间接自适应广义预测控制算法。采用统一的理论分析了已建立的自适应广义预测控制算法的全局稳定性和鲁棒性,得出了自适应控制系统具有鲁棒稳定性的新条件：自适应验后误差和对象参数估值变化的均值渐近小,从而弱化了现有自适应控制系统的鲁棒稳定性条件。     

Calculation of Output Noise Variances for Discrete Time-Invariant Filters

Certain calculations to minimize output noise variance are introduced. Many applied problems in sampled data systems require that data be smoothed in the presence of noise for the prediction of future positions, velocities, or accelerations. Smoothing coefficients in discrete time-invariant filters are computed to minimize the output noise variance, but under the constraints that the function and derivatives be predicted ahead. The output noise variance is seen to be a function of the input noise, the number of input signals (N+1) that the filter has to smooth, and the prediction time ?T. Four examples are given in the derivation of smoothing coefficients for step and ramp inputs subjected to either almost white noise or Gaussian-Markoff noise. The examples illustrate the number of constraint relations that the filter smoothing coefficients must satisfy for function and/or derivative convergence under noise-free conditions. The smoothing coefficients are also a function of the type of noise input into the system or the discrete filter. From the examples, it can be observed that as N becomes larger, the output noise variance becomes smaller, but the computation time is increased.     

多项式非线性系统的多维频率响应函数

应用多维频率响应函数进行非线性系统的谱分析,是线性系统谱分析的推广。讨论了多项式非线性动力学系统的多维频率响应函数(MFRF)的结构形式及推导方法,证明多项式非线性动力学系统的高阶频率响应函数完全由一阶频率响应函数表示。并且讨论了多维频率响应函数的极点。为这类系统的参数识别和响应的谱分析提供了基础。     

基于李群谱配点法的卫星姿态仿真

为了提高卫星姿态控制系统仿真的精度、可信性和长时间稳定性,提出了一种基于李群谱配点法的卫星姿态仿真方法。对于李群上动力学系统的仿真,李群谱配点法具有独特的优势,不仅能很好地保持系统的几何结构,而且具有几何收敛性。主要结合李群算法和谱方法各自的优势,给出了几何动力学与控制系统李群谱配点法的构造方法并将该算法应用于欠驱动卫星系统的姿态控制系统仿真中。     

Self-Tuning Multisensor Weighted Measurement Fusion Kalman Filter

For the multisensor systems with unknown noise variances, based on the solution of the matrix equations for the correlation function, the on-line estimators of the noise variance matrices are obtained, whose consistency is proved using the ergodicity of sampled correlation function. Further, two self-tuning weighted measurement fusion Kalman filters are presented for the multisensor systems with identical and different measurement matrices, respectively. Based on the stability of the dynamic error system, a new convergence analysis tool is presented for a self-tuning fuser, which is called the dynamic error system analysis (DESA) method. A new concept of convergence in a realization is presented, which is weaker than the convergence with probability one. It is rigorously proved that the proposed self-tuning Kalman fusers converge to the steady-state optimal Kalman fusers in a realization or with probability one, so that they have asymptotic global optimality. A simulation example for a target tracking system with 3 sensors shows their effectiveness.     

飞机的全局稳定性分析和非线性控制

现代军用飞机常设计为在大迎角下飞行。此时飞机是一个高度非线性系统，其稳定特性不能用线性方法求解。而实现控制，特别是在非线性不稳定性的情况下，更是十分困难的。本文介绍了一种综合的分析飞机非线性稳定性和控制的方法。即用分岐理论来决定飞机的全局稳定性。用四阶龙格－库塔积分来计算飞机运动的平衡面和分岐点，并构造运动状态的扰动传播矩阵，而此矩阵的特征值可用来预测稳定性的时变性。此外，还利用扰动传播矩阵来求得为满足规定的飞机反应特性（通常由频率和阻尼表示）所需的操纵，即各操纵面反馈回路的放大系数值。对典型飞机的算例计算结果表明，非线性控制是成功的。     

离散广义线性系统的若干结论

本文将常义离散线性系统中的部分结论推广到了广义系统的情形，给出了广义系统的正则性定理，稳定性定理、能稳性定理和输出调节定理。     

不确定线性时滞系统的鲁棒镇定控制

提出了利用构造系统的Lyapunov不等式的对称正定解，采用放大矩阵不等式的新方法，通过对鲁棒反馈控制系统不确定项进行结构表出，基于二次反馈策略构造系统的反馈镇定控制器。首先得到不确定线性时滞鲁棒系统稳定的充分条件，进而给出判别不确定线性时滞反馈系统鲁棒镇定的充分条件。所给出的定理争件易于表达，由于参数少而容易检验。     

Optimal and self-tuning information fusion Kalman multi-step predictor

Based on the optimal fusion algorithm weighted by matrices in the linear minimum variance (LMV) sense, a distributed optimal information fusion for the steady-state Kalman multi-step predictor is given for discrete linear stochastic control systems with multiple sensors and correlated noises, where the same sample period is assumed. When the noise statistics information is unknown, the distributed information fusion estimators for the noise statistics parameters are presented based on the correlation functions and the weighting average approach. Further, a self-tuning information fusion multi-step predictor is obtained. It has a two-stage fusion structure. The first-stage fusion is to obtain the fused noise statistics information. The second-stage fusion is to obtain the fused multi-step predictor. A simulation example shows the effectiveness.