模糊滑模迭代学习控制算法在液压系统中应用

普通比例(P, Proportion)和比例微分(PD, Proportion and Differential)迭 代学习控制(ILC, Iterative Learning Control)算法在液压位置伺服系统中收敛速度比较 慢,很难在实际中应用.为了提高ILC算法的收敛速度,将滑模控制算法引入ILC,提出模糊 滑模迭代学习控制(FSMILC, Fuzzy Sliding Mode Iterative Learning Control)算法,利 用滑模控制响应快的优点来加速ILC的收敛速度,利用模糊控制来减小滑模控制所引起的抖 动问题.FSMILC算法的实质是以系统的滑模函数作为模糊控制器的输入,以模糊控制器的输 出作为ILC的控制增量.通过仿真可以看出,FSMILC算法能够实现系统快速收敛,相对于P型 和PD型具有明显优势.      

一种基于切比雪夫插值的联想记忆系统

提出了一种基于切比雪夫插值的高阶联想记忆系统(TI-AMS),能提供对任意阶多变量多项式函数的无误差逼近.切比雪夫插值的近似于最优一致逼近的性质从理论上保证了对任意连续函数的全局逼近精度.特别在对一些不连续函数(如矩形脉冲函数)的逼近中也有其它AMS无法比拟的优势.理论分析和数值模拟表明,该系统具有计算简单、学习精度高、收敛速度快、总的存储单元空间较小等优点.可广泛应用于图像压缩、模式识别、及高精度实时智能控制等领域.      

新型自适应Terminal滑模控制及其应用

针对一类高阶MIMO非线性系统设计了基于快速模糊干扰观测器的自适应Terminal滑模控制方案.通过设计快速模糊干扰观测器,克服了传统模糊干扰观测器在误差较小时收敛速度慢的缺点.严格证明了跟踪误差及观测误差均在有限时间内收敛到零的小区域.最后在高超声速条件下,对空天飞行器再入过程的姿态控制进行仿真,结果表明了所设计干扰观测器的优越性和闭环控制方案的有效性.      

Finite-time composite guidance law with input constraint and dynamics compensation

Guidance laws are proposed for a near space interceptor with on–off type thrust as output. The target-interceptor engagement kinematics is integrated with the first-order dynamics of thruster to design guidance laws. The bang-bang type guidance law with linear sliding mode is proposed to deal with thruster dynamics, and the sufficient condition for finite time convergence is rigorously proved based on the finite-time convergence theory. According to the sufficient condition, a sliding mode guidance law with hysteresis-band switching is introduced to reduce the switching frequency of thruster. Then two guidance laws are combined into a composite guidance law to improve the guidance performance. Simulation results show that the line-of-sight angular rate can converge to a neighborhood of the equilibrium point before the final time of the guidance process, and the composite guidance law has better performance than typical guidance laws.     

交错级数的审敛法

本文给出交错级数及双项交错级数的一种类型的审敛法，并分别给出判定交错级数及双项交错级数绝对收敛的一种方法。     

测量数据部分丢失的非线性系统迭代学习控制

研究非线性离散系统的迭代学习控制．利用并行分配补偿方法(PDC)确定非线性系统的T-S模型,把非线性模型特换为局部线性模型。假定数据丢失的概率已知,采用满足Bernoulli分布的序列来描述测量数据的丢失,研究具有测量数据部分丢失的线性离散系统的迭代学习控制器的设计。结合T-S模型设计了数据丢失的迭代学习控制器,所设计的迭代学习控制器具有期望收敛特性和二次型性能指标。仿真结果表明了该设计方法的有效性。     

变容量限制多阶段存储问题及其求解算法

本文给出了求变容量限制多阶段存储问题的最优存储方案的一个数值算法，证明了它的理论依据，并举例说明了算法的应用。该算法具有概念清楚、步骤明确、收敛性好、易于编程实现等优点，在存贮管理中有推广应用价值。     

基于快速模糊干扰观测器的UASV再入Terminal滑模控制

针对无人空天飞行器再人大气层过程中气动参数变化剧烈、控制精度要求高的特点，设计了基于快速模糊干扰观测器的Terminal滑模控制方案。通过改进传统模糊干扰观测器的学习律，提出一种快速模糊干扰观测器，增强了其在线逼近干扰及系统不确定的能力。Terminal滑模的有限时间收敛特性提高了系统跟踪速度，同时采用快速模糊干扰观测器消除全部扰动的影响，从而保证了飞行品质。最后，仿真结果表明了快速模糊干扰观测器的优越性及闭环控制方案的有效性。     

数列与级数收敛性判定的一个注记

数列xnm^（k）～rnm^（k）＋q审敛原理是数列xnm～rnm＋p审敛原理更加一般性的推广，进一步扩大了数列xnm～rnm＋p审敛原理的适用范围；利用数列xnm～rnm＋p印审敛原理还得到了判别数列收敛性的“子列～局部夹”准则。     

Joint Iterative Decoding for Network-Coding-Based Multisource LDPC-Coded Cooperative MIMO

A network-coding-based multisource LDPC-coded cooperative MIMO scheme is proposed,where multiple sources transmit their messages to the destination with the assistance from a single relay.The relay cooperates with multiple sources simultaneously via network-coding.It avoids the issues of imperfect frequency/timing synchronization and large transmission delay which may be introduced by frequency-division multiple access(FDMA)/code-division multiple access(CDMA)and time-division multiple access(TDMA)manners.The proposed joint″Min-Sum″iterative decoding is effectively carried out in the destination.Such a decoding algorithm agrees with the introduced equivalent joint Tanner graph which can be used to fully characterize LDPC codes employed by the sources and relay.Theoretical analysis and numerical simulation show that the proposed scheme with joint iterative decoding can achieve significant cooperation diversity gain.Furthermore,for the relay,compared with the cascade scheme,the proposed scheme has much lower complexity of LDPC-encoding and is easier to be implemented in the hardware with similar bit error rate(BER)performance.