An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot

We present an iterative linear quadratic regulator(ILQR) method for trajectory tracking control of a wheeled mobile robot system.The proposed scheme involves a kinematic model linearization technique,a global trajectory generation algorithm,and trajectory tracking controller design.A lattice planner,which searches over a 3D(x,y,θ) configuration space,is adopted to generate the global trajectory.The ILQR method is used to design a local trajectory tracking controller.The effectiveness of the proposed method is demonstrated in simulation and experiment with a significantly asymmetric differential drive robot.The performance of the local controller is analyzed and compared with that of the existing linear quadratic regulator(LQR) method.According to the experiments,the new controller improves the control sequences(v,ω) iteratively and produces slightly better results.Specifically,two trajectories,’S’ and ’8’ courses,are followed with sufficient accuracy using the proposed controller.     

双轴旋转惯导系统误差传播特性分析

针对双轴旋转惯导系统的误差传播特性问题,推导出双轴旋转惯导系统的误差方程,通过特征值判据证明了误差方程在李雅普诺夫意义下的稳定性,设计了一种合理的十六次序转位方案,建立了研究误差传播特性的方法,分别仿真了初始对准误差角、陀螺常值漂移、陀螺安装误差、陀螺标度因数误差4种因素对导航误差传播特性的影响。结果表明,4种误差因素大小均与导航误差大小成线性关系,并且满足叠加性;4种误差因素会引起导航姿态、导航速度、导航纬度的常值误差和振荡误差,但不会引起积累误差;陀螺标度因数误差会引起导航经度误差的积累和发散。最后提出了减小双轴旋转惯导系统导航误差的措施,对设计双轴旋转惯导系统有一定的参考价值。     

水轮机调节系统的状态PI控制器研究

虽然状态PI控制器已经提出很多年,但至今未在水轮机转速控制中有所应用。本文应用状态PI控制,从水轮机控制系统状态反馈模型出发,设计水轮机调节系统状态PI控制器,并对状态PI最优控制与传统推荐PID最佳调节进行比较分析。仿真结果表明:两者动态过程明显不同,前者的动态过程呈现非周期快速稳定特点,而后者的动态过程则为衰减振荡过程,并且状态PI控制在负荷变化时有更好的控制品质。     

首系数奇异的二阶系统解耦

针对首系数奇异的二阶系统的解耦问题,提出了一种奇异二阶系统的同谱构造解耦方法。引入了对逆二阶系统,将难以描述的二阶系统无穷大特征值转化为其对逆二阶系统的零特征值来加以描述,分析了奇异二阶系统可对角化应该满足的条件及其相应的证明,并且给出了一种具体的奇异二阶系统的同谱构造解耦方法,从而实现了奇异二阶系统解耦,即将奇异二阶系统的3个参数矩阵同时对角化。数值试验中将一个三自由度的奇异质量弹簧二阶系统解耦成3个无关的单自由度二阶子系统,而且解耦前后系统不仅保持了相同的有限特征值及其重复度结构,还保持了相同的无限特征值及其重复度结构。工程应用前景十分广泛。     

gain bounds for systems with sector bounded and slope‐restricted nonlinearities

This paper proposes a new method for calculating a bound on the gain of a system comprising a linear time invariant part and a static nonlinear part, which is odd, bounded, zero at zero and has a restriction on its slope. The nonlinear part is also assumed to be sector bounded, with the sector bound being (possibly) different from that implied by the slope restriction. The computation of the gain bound is found by solving a set of linear matrix inequalities, which arise from an integral quadratic constraint formulation of a multiplier problem involving both Zames‐Falb and Popov multipliers. Examples illustrate the effectiveness of the results, and comparisons are made against the state‐of‐the‐art. Copyright © 2011 John Wiley & Sons, Ltd.     

Weighted principal component extraction with genetic algorithms

Pattern recognition techniques have been widely used in a variety of scientific disciplines including computer vision, artificial intelligence, biology, and so forth. Although many methods present satisfactory performances, they still have several weak points, thus leaving a lot of space for further improvements. In this paper, we propose two performance-driven subspace learning methods by extending the principal component analysis (PCA) and the kernel PCA (KPCA). Both methods adopt a common structure where genetic algorithms are employed to pursue optimal subspaces. Because the proposed feature extractors aim at achieving high classification accuracy, enhanced generalization ability can be expected. Extensive experiments are designed to evaluate the effectiveness of the proposed algorithms in real-world problems including object recognition and a number of machine learning tasks. Comparative studies with other state-of-the-art techniques show that the methods in this paper are capable of enhancing generalization ability for pattern recognition systems.     

保持几何特征的自适应弹性二次曲线模型

物体形状特征的准确提取往往受到图像获取、目标分割等过程中各种因素的影响,因而需要构造一种鲁棒的形状表现来保有其本质特征。揭示弹性二次曲线(EQW)模型中能量权重因子和样条重叠度因子与形状几何特性间的关系,提出一种自适应保持几何特征的EQW形状表现模型,并将该模型与交互式Live Wire算法相结合,应用至图像分割中,对于各种模态图像中的目标进行分割实验。直观上,本文方法能够在去除噪声同时较好地保持目标形状的显著特征;量化结果方面,交互式分割误差保持在较小稳定范围内,引入EQW模型带来的时间开销亦在可接受范围内。     

具有随机丢包的网络化多自主体系统的一致性

研究具有随机丢包的网络化多自主体系统的均方一致性问题,其中不同自主体间的通信通道具有相同的丢包情况并且均服从马尔可夫(Markov)分布。首先,利用系统变换和迭代方法,得到了系统达到均方一致的一个初等充要条件。然后,利用矩阵理论和图论知识,如果拓扑图含有有向生成树,则可以将系统的均方一致性转化成一个线性Markov跳变系统的均方稳定性,并且可以建立线性矩阵不等式形式的均方可镇定准则。最后,通过相应的仿真实例说明了所得结论的可行性。     

不确定离散系统的鲁棒Gl2滤波器设计

对于凸多面体不确定离散系统,研究了满足误差估计系统鲁棒稳定且满足一定Gl₂性能指标的线性全阶稳定滤波器设计方法.分别给出了确定性和不确定性离散系统具有Gl₂性能的线性矩阵不等式（linear matrix inequality, LMI)充要条件和充分条件.在此基础上,通过使用滤波器参数化方法,分别推导出了以LMI描述的确定性和不确定性系统的Gl₂滤波器存在的充要条件和充分条件,进而可以使用LMI凸优化程序求解滤波器.通过对算例的计算,结果表明,在噪声信号为独立范数有界情况下,鲁棒Gl₂滤波比H_∞滤波具有更少的保守性.     

非线性滤波在射线图像降噪增强中的应用

射线数字成像是当前射线检测与诊断技术发展的方向，图像降噪增强是提高射线成像检测灵敏度和分辨力的关键。重点探讨以排序滤波为代表的非线性滤波图像降噪增强方法，对射线图像的处理表明，线性滤波在降噪的同时会引起较大的边级模糊，而排序滤波不仅降低噪声且能保持图像细节，提高图像质量效果明显。