Feedback predictive control for constrained fuzzy systems with Markovian jumps

In this paper, a feedback model predictive control method is presented to tackle control problems with constrained multivariables for uncertain discrete‐time nonlinear Markovian jump systems. An uncertain Markovian jump fuzzy system (MJFS) is obtained by employing the Takagi‐Sugeno (T‐S) fuzzy model to represent a discrete‐time nonlinear system with norm bounded uncertainties and Markovain jump parameters. To achieve more generality, the transition probabilities of the Markov chain are assumed to be partly unknown and partly accessible. The predictive formulation adopts an on‐line optimization paradigm that utilizes the closed‐loop state feedback controller and is solved using the standard semi‐definite programming (SDP). To reduce the on‐line computational burden, a mode independent control move is calculated at every sampling time based on a stochastic fuzzy Lyapunov function (FLF) and a parallel distributed compensation (PDC) scheme. The robust mean square stability, performance minimization and constraint satisfaction properties are guaranteed under the control move for all admissible uncertainties. A numerical example is given to show the efficiency of the developed approach. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

RBF neural networks-based robust adaptive tracking control for switched uncertain nonlinear systems

In this paper, a robust adaptive H∞ control scheme is presented for a class of switched uncertain nonlinear systems. Radical basis function neural networks (RBF NNs) are employed to approximate unknown nonlinear functions and uncertain terms. A robust H∞ controller is designed to enhance robustness due to the existence of the compound disturbance which consists of approximation errors of the neural networks and external disturbance. Adaptive neural updated laws and switching signals are deducted from multiple Lyapunov function approach. It is proved that with the proposed control scheme, the resulting closed-loop switched system is robustly stable and uniformly ultimately bounded (UUB) such that good capabilities of tracking performance is attained and H∞ tracking error performance index is achieved. A practical example shows the effectiveness of the proposed control scheme.     

Improved stability conditions for systems with interval time-varying delay

The paper is concerned with the stability of linear systems with interval time-varying delay. Through constructing a new augmented Lyapunov-Krasovskii functional (LKF) which contains some quadruple-integral terms and estimating the time derivative of the LKF less conservatively, new stability criteria are derived without introducing any free matrices. Moreover, by proving the positive definiteness of the LKF with some integral inequalities, the constraints on some functional parameters are relaxed and the conservatism of the obtained results are further reduced. Numerical examples are also given to demonstrate the effectiveness and reduced conservatism of the obtained results.     

一种改进的基于多项式滤波的稳态检测方法

化工过程的数据中常常含有较多的随机误差和粗差干扰,导致传统的稳态检测方法无法得到准确的结果,从而降低系统故障诊断的可靠性。针对实际的工业过程数据,提出一种融合自适应平滑技术的稳态检测方法,该方法首先以基于导数分析的自适应平滑算法进行降噪处理,消除随机误差的影响,然后引入阈值拟合技术进一步抑制粗差干扰,以多项式滤波方法对数据进行稳态检测,根据测量信号的趋势特征确定过程是否处于稳态。仿真实验研究表明:融合自适应平滑技术的稳态检测方法能够克服传统稳态检测方法中随机误差和粗差干扰对检测结果的影响,进而显著提高稳态检测处理的准确性,检测结果明显优于传统的基于多项式滤波的检测方法。     

SNMP在网络音频传输中的应用研究

鉴于网络化音频传输技术的发展,开发基于SNMP协议的网络音频管理软件具有十分重要的意义。本文采用C#编程语言,基于C/S架构进行了网络音频管理程序的设计。客户端基于TCP/IP协议,服务器端采用SNMP协议进行了网络音频管理编程,硬件测试表明实现了网络化的音频管理。阐述的设计思路对SNMP应用于工程设计具有一定的参考价值。     

偏最小二乘回归在气温预测中的研究与应用

气温的预测要考虑多重气象因子,然而各气象因子间的多重相关性导致普通的多元回归模型失真,预测精度降低。为了解决以上问题,本研究采用偏最小二乘回归(Partial Least Squares Regression,简称PLS)建模,根据实际建模需要对算法进行改进。为了验证该模型,本研究以成都市10月份气温场为预报场,并结合成都市13个自动站气温数据,提取预报所需主要因子,进行PLS回归建模。实验表明该模型有较好的预测能力。     

星地激光通信相对运动研究与仿真

星地激光通信系统中,为了确定激光链路的传输方向,确定卫星相对于地面站的位置参数。采用两行星历数据的轨道六要素,根据坐标变换原理,依次计算卫星在地心轨道坐标系、地心惯性坐标系和地心地固坐标系中的位置,再由地面站的经纬度和海拔计算在地心地固坐标系中的位置分量,最后计算在观测坐标系中卫星相对于地面站的位置参数,包括方位角、仰角和斜距。在MATLAB上进行仿真,输出与卫星工具箱仿真的二体模型时空分布相一致,证明了方法的正确性,可为星地激光通信系统的研究提供参考。     

均衡化特征匹配的非刚体细胞形态跟踪

提出利用均衡化特征匹配来进行非刚性细胞形体跟踪的方法。采用重启动的随机游走方法建立并求解特征匹配概率模型,利用双向均衡方法对匹配邻接矩阵进行均衡化处理,得到指定目标与待跟踪目标之间的精确匹配,以获得目标的定位跟踪结果。同时利用特征匹配结果进行目标的自动标定,并应用图像分割方法进行目标的精确轮廓跟踪。实验结果表明,将该方法应用于视频中动态背景下的运动细胞形态跟踪时,在背景相似度较高及目标迅速移动的条件下,表现出了良好的性能,与同类方法相比可获得较高的定位精度以及更为准确的目标轮廓。     

基于雷达/红外成像的机动目标加速度估计

研究机动目标跟踪精度优化问题,需获取机动目标加速度准确信息。由于空间外界干扰造成雷达提供信息不准确,为此提出了基于雷达/红外成像的机动目标跟踪信息融合算法。建立了机动目标与空空导弹的相对运动目标机动数学模型,引入了雷达/红外成像导引头联合观测方法,并对两者的观测信息在时间上进行同步配准。采用雷达/红外成像信息融合跟踪扩展自适应卡尔曼滤波算法进行仿真。仿真结果表明,改进算法能够对机动目标加速度信息进行有效的、实时准确的估计,验证了所设计的跟踪算法的正确性,实现了以直接碰撞方式达到毁伤目标的目的。     

小型无人机对地跟踪系统图像清晰化及仿真

研究小型无人机机载摄像机图像退化的复原问题。为了提高盘旋工作状态下图像恢复效果,针对小型无人机盘旋工作状态与平飞作状态图像退化机理的差异,通过对图像模糊过程进行分析,根据小型无人机摄像特点,给出了小型无人机盘旋状态图像清晰化方案。即通过量化将同时存在不同像移量的图像分成几个区域,在各区域中像移量一致,再对各区域采用维纳滤波并行处理,最后合并成整体图像。仿真结果表明,清晰化方案在盘旋状态下,退化图像能取得较好的恢复效果,且抗噪性能较强。