离散系统LQ调节器的鲁棒性分析

本文研究了离散ＬＱ调节器系统鲁棒稳定性问题，稳定的不确定参数是通过考虑参数摄动的方向而求得的，这种方法比现有文献提供的结果具有更好的稳定范围。     

先进控制在环管法聚丙烯装置中的应用

以九江石油化工总厂70kt/a聚丙烯装置产率控制为例,介绍先进过程控制系统在石油化工装置上的应用情况。     

Identification environment and robust forecasting for nonlinear time series

In this paper, the methods of time series for nonlinearity are briefly surveyed, with particular attention paid to a new test design based on a neural network specification. The proposed integrated expert system contains two main components: an identification environment and a robust forecasting design. The identification environment can be viewed as a integrated dynamic design in which cognitive capabilities arise as a direct consequence of their self-organizational properties. The integrated framework used for discussing the similarities and differences in the nonlinear time series behavior is presented. Moreover, its performance in prediction proves to be superior than the former work. For the investigation of robust forecasting, we perform a simulation study to demonstrate the applicability and the forecasting performance.     

新的e修正鲁棒自适应控制方法在航空发动机上的应用

针对航空发动机模型的结构和参数的不确定性,提出一种基于非李亚普诺夫方程(NQLF)的e修正鲁棒模型参考自适应控制法。该方法无需知道发动机精确数学模型,抗干扰能力强,在输出误差信号的作用下具有比普通方法更快的收敛性,振荡性能够得到很好的控制。从仿真结果可见控制器能使系统比较好地跟踪参考模型的输出,对发动机模型参数和结构的变化有一定的适应能力,鲁棒性较好。     

基于改进HBA算法的生鲜闭环供应链网络鲁棒优化设计

针对生鲜闭环供应链网络设计问题,建立了一种基于生鲜闭环供应链网络的鲁棒优化模型,以解决供应链网络中的不确定性问题。首先,针对涵盖五个节点的生鲜供应链网络结构建立了多周期、多产品,以最小化成本、最小环境影响为目标的混合整数规划模型,采用模糊折中规划与区间数据鲁棒优化方法进行处理;其次,在原有蜜獾算法的基础上引入差分进化原则,增强算法的全局搜索能力与收敛速度;最后,通过MATLAB数值分析与仿真实例表明,所提鲁棒优化模型与蜜獾算法在求解生鲜闭环供应链网络设计问题中具有明显优势。     

一种低复杂度的鲁棒自适应波束形成算法

传统基于干扰噪声协方差矩阵（interference-plus-noise covariance matrix,INCM）重构的鲁棒自适应波束形成（robust adaptive beamformer,RAB）算法在多种样本数据协方差矩阵误差和信号导向向量误差的失配环境中具有较强的鲁棒性,但目前主流的INCM重构法都是对信号和干扰的导向向量通过建立凸优化模型来估计,这带来了很高的计算复杂度。为了解决这个问题,提出了一种低复杂度的基于INCM重构的RAB算法。该算法首先将干扰信号的导向向量分解为对应标称项和误差项的和,然后通过一种子空间方法估计得到误差项的单位向量。接下来对一个Capon空间谱功率最大问题进行求解,得到误差项的模值,以此得到重构的INCM。同时利用Capon空间谱中残差噪声的存在,使用交替投影法估计得到期望信号的导向向量,最后得到所提算法的权重向量。仿真实验表明所提算法在多种误差环境下具有较强鲁棒性的同时,还具有较低的计算复杂度。     

Robust stability and stabilization of discrete singular systems with interval time-varying delay and linear fractional uncertainty

The robust stability and robust stabilization problems for discrete singular systems with interval time-varying delay and linear fractional uncertainty are discussed. A new delay-dependent criterion is established for the nominal discrete singular delay systems to be regular, causal and stable by employing the linear matrix inequality (LMI) approach. It is shown that the newly proposed criterion can provide less conservative results than some existing ones. Then, with this criterion, the problems of robust stability and robust stabilization for uncertain discrete singular delay systems are solved, and the delay-dependent LMI conditions are obtained. Finally, numerical examples are given to illustrate the e?ectiveness of the proposed approach.     

An Intelligent Robust Tracking Control for a Class of Electrically Driven Mobile Robots

This paper addresses the problem of designing robust tracking control for a class of uncertain wheeled mobile robots actuated by brushed direct current motors. This class of electrically‐driven mechanical systems consists of the robot kinematics, the robot dynamics, and the wheel actuator dynamics. Via the backstepping technique, an intelligent robust tracking control scheme that integrates a kinematic controller and an adaptive neural network‐based (or fuzzy‐based) controller is developed such that all of the states and signals of the closed‐loop system are bounded and the tracking error can be made as small as possible. Two adaptive approximation systems are constructed to learn the behaviors of unknown mechanical and electrical dynamics. The effects of both the approximation errors and the unmodeled time‐varying perturbations in the input and virtual‐input weighting matrices are counteracted by suitably tuning the control gains. Consequently, the robust control scheme developed here can be employed to handle a broader class of electrically‐driven wheeled mobile robots in the presence of high‐degree time‐varying uncertainties. Finally, a simulation example is given to demonstrate the effectiveness of the developed control scheme.     

Uncertainty modeling and robust minimax LQR control of multivariable nonlinear systems with application to hypersonic flight

For a class of multi‐input and multi‐output nonlinear uncertainty systems, a novel approach to design a nonlinear controller using minimax linear quadratic regulator (LQR) control is proposed. The proposed method combines a feedback linearization method with the robust minimax LQR approach in the presence of time‐varying uncertain parameters. The uncertainties, which are assumed to satisfy a certain integral quadratic constraint condition, do not necessarily satisfy a generalized matching condition. The procedure consists of feedback linearization of the nominal model and linearization of the remaining nonlinear uncertain terms with respect to each individual uncertainty at a local operating point. This two‐stage linearization process, followed by a robust minimax LQR control design, provides a robustly stable closed loop system. To demonstrate the effectiveness of the proposed approach, an application study is provided for a flight control problem of an air‐breathing hypersonic flight vehicle (AHFV), where the outputs to be controlled are the longitudinal velocity and altitude, and the control variables are the throttle setting and elevator deflection. The proposed method is used to derive a linearized uncertainty model for the longitudinal motion dynamics of the AHFV first, and then a robust minimax LQR controller is designed, which is based on this uncertainty model. The controller is synthesized considering seven uncertain aerodynamic and inertial parameters. The stability and performance of the synthesized controller is evaluated numerically via single scenario simulations for particular cruise conditions as well as a Monte‐Carlo type simulation based on numerous cases. It is observed that the control scheme proposed in this paper performs better, especially from the aspect of robustness to large ranges of uncertainties, than some controller design schemes previously published in the literature. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society