基于参数区间不确定性分析的无人机辅助物联网鲁棒优化

无人机辅助物联网技术被广泛应用于灾害应急通信中,但物联网设备的通信中存在多种不确定因素。针对位置参数区间存在不确定性的问题,提出了无人机辅助物联网通信的鲁棒优化方法。使用椭球不确定集对地面物联网设备位置参数区间不确定性进行描述,建立了包含不确定性的物联网设备通信鲁棒优化模型,并对模型进行了求解。为提高模型求解的准确性,提出一个有关位置参数区间不确定和椭球误差域之间的相关分析方法,分析了两类不确定因素对物联网设备通信模型的影响程度。以地面物联网设备最优部署和通信最小功率为目的,设计了仿真实验。结果表明,在不确定因素存在时,所提优化模型能有效实现地面物联网设备间的最优部署和通信功率最小化。     

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。     

SGCMGs驱动的挠性航天器有限时间自适应鲁棒控制

针对挠性航天器系统中同时存在单框架控制力矩陀螺群(Single gimbaled control moment gyroscopes, SGCMGs) 摩擦非线性、电磁干扰力矩、惯量摄动以及外部干扰等问题, 提出了一种有限时间自适应鲁棒控制(Finite-time adaptive robust control, FTARC) 方法. 针对系统中存在未知参数的情况, 分别设计自适应更新律, 使得控制器的设计不依赖参数信息, 同时减小外部干扰对系统的不利影响. 应用Lyapunov稳定性理论证明了闭环系统姿态角误差和姿态角速度误差可在有限时间内收敛到原点附近的邻域内. 仿真结果表明, 所提控制律可实现挠性航天器姿态快速机动, 并获得甚高指向精度.     

多时滞线性连续系统的最优H∞容错控制

针对状态具有多个时滞的线性连续系统,基于Lyapunov稳定性理论和线性矩阵不等式方法(LMI),采用无时滞记忆的状态反馈控制律,研究了在执行器发生故障的情况下,连续多时滞系统的最优H∞容错控制问题.首先,给出了系统没有干扰输入时存在无记忆状态反馈容错控制器的一个充分条件;进一步,给出了在H∞扰动衰减指标约束下,系统存在无记忆状态反馈H∞容错控制器的一个充分条件;最后,给出了最优无时滞记忆状态反馈H∞容错控制器的设计方法.仿真实例证明了所得最优H∞容错控制嚣设计方法的正确性和有效性.     

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     

Augmented Lyapunov functional approach for stability of neutral systems with mixed delays

This paper is concerned with the neutral‐delay‐dependent and discrete‐delay‐dependent stability for uncertain neutral systems with mixed delays and norm‐bounded uncertainties. Through constructing a new augmented Lyapunov‐Krasovskii functional and proving its positive definiteness, introducing some slack matrices and using integral inequality, the improved delay‐dependent stability criteria are derived in terms of linear matrix inequalities. Numerical examples are given to illustrate the significant improvement on the conservatism of the delay bound over some existing results. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Exponential stabilization of uncertain time‐delay linear systems with Markovian jumping parameters

This paper studies the exponential stabilization problem of uncertain time‐delay linear systems with Markovian jumping parameters. A novel delay decomposition approach is developed to derive delay‐dependent conditions under which the closed‐loop control system is mean square exponentially stable for all admissible uncertainties. It is shown that the feedback gain matrices and the decay rate can be obtained by solving coupled linear matrix inequalities. Moreover, the difficulties arising from searching for tuning parameters in the existing methods are overcome. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

考虑风电不确定性和机组故障停运风险的两阶段鲁棒机组组合

发电机故障停运是电力系统运行中的不确定事件。目前在含风电鲁棒机组组合中考虑机组故障停运的方法,不同程度地忽略了机组故障停运的概率特征,难以较好描述机组故障停运风险。在含风电鲁棒机组组合模型的基础上,引入电量不足期望以量化机组故障停运风险,基于成本收益分析建立了考虑风电不确定性和机组故障停运风险的两阶段鲁棒机组组合模型,并提出计算电量不足期望的简化模型以提升计算效率。基于改进的IEEE-RTS 26机系统验证所提模型和方法,结果表明该方法能较好考虑风电不确定性和机组故障停运风险的影响,该简化模型能显著减小问题求解规模、缩短计算时间。