非线性动态传感器系统的H模型神经网络辨识

针对非线性动态传感器模型辨识问题,提出一种新的Hammerstein模型神经网络结构辨识法。非线性动态传感器系统采用Hammerstein模型描述,将系统分解为非线性静态增益串接线性动态环节。再设计一种网络权系数对应于相应的Hammerstein模型参数的新型神经网络结构,推导了基于反向传播的网络权系数调整方法。通过网络迭代训练同时得到静态与动态两个环节的模型参数。最后通过一个H模型的数值仿真来验证方法的有效性,仿真结果表明所提辨识方法是有效的。     

基于非线性自回归时序模型的振动系统辨识

针对线性和弱非线性振动系统进行了研究,提出采用非线性自回归时序(GNAR)模型进行系统频率辨识和判断系统性或非线性基本特征的方法。首先根据摄动法求解非线性微分方程的理论,论证GNAR模型与线性和弱非线性系统之间的本质联系,推导出GNAR模型系数与线性和非线性系统频率之间的解析关系,然后给出由GNAR模型系数和结构判断系统是否存在非线性,及辨识系统频率和非线性项基本特征的方法。最后,以单自由度线性振动系统和无阻尼Duffing振动系统为算例验证该辨识方法的有效性和准确性。实验结果表明,基于GNAR模型的振动系统基本特征辨识方法具有较好的识别精度,能用于估计系统的动力学特性。     

质子交换膜燃料电池的分数阶非线性状态空间模型研究

针对质子交换膜燃料电池(PEMFC)发电过程中的分数阶和非线性特性,本文提出了一种分数阶子空间辨识方法建立了PEMFC非线性状态空间模型.首先,为了降低建模复杂度,采用典型相关分析法和相关分析法确定了模型输入变量;其次,将分数阶微分理论与Hammerstein模型子空间辨识方法相结合,采用Poisson矩函数对输入输出数据进行预处理,构造了子空间辨识方法的输入输出矩阵,并引入分数阶短时记忆法减少辨识算法计算量;最后,选取多项式作为Hammerstein模型前端静态非线性环节,采用模糊遗传算法优化系统分数阶阶次和系数矩阵.仿真结果验证了算法的有效性,改进的辨识算法可以明显减小计算时间,所得PEMFC辨识模型能够准确地描述PEMFC的动态过程.     

基于SVR的传感器Hammerstein模型辨识

提出一种基于支持向量回归机的非线性动态传感器Hammerstein模型辨识方法并给出了相关的数学理论及学习算法.在该模型中,用非线性静态子环节和线性动态子环节串联来描述传感器的非线性动态特性.再利用函数展开将模型的非线性传递函数转换为等价的线性中间模型,并通过SVR求取中间模型参数.最后,推导出中间模型参数与传感器Hammerstein模型参数之间的关系,并由该关系实现非线性静态环节和线性动态环节的同时辨识.用实际力传感器动态标定实验数据进行测试,结果表明与常规非线性传感器辨识方法不同,所提方法只需进行一次动态标定实验就能给出非线性动态模型的数学解析表达式.且建立的力传感器Hammerstein模型阶次为4,而线性动态系统模型则需要6阶才能达到相同的精度.因此该研究为传感器非线性动态系统辨识又提供了一种可选方法.     

基于快速响应码的非线性光学图像加密算法

为增强加密系统的抗破译能力,提出快速响应码耦合Shearlet变换的非线性光学加密算法。引入非线性复合混沌系统,构建交叉置乱方法,改变明文的像素位置;借助二维码生成器,将置乱结果转换成对应的快速响应码QR (quick response)码;采用Shearlet变换,对QR码实施5级分解,输出5个剪切系数,利用一个安全图像与第一个剪切系数互换,联合其它4个系数,借助可逆Shearlet变换,生成过渡图像;设计调制融合掩码,基于Gyrator变换,对过渡图像实施加密,获取Gyrator频谱;通过幅度-相位截断,将Gyrator频谱实施分割,输出密文。测试数据表明,与已有的光学加密方法相比,所提方案具备更高加密安全性与复原质量。     

基于支持向量机的直接逆模型辨识

在简单讨论逆模型辨识原理的基础上,利用支持向量机(SVM)对函数逼近的能力,提出了基于支持向量机的直接逆模型辨识方法.分别采用二次核函数以及高斯RBF核函数,利用训练数据对线性和非线性系统进行黑箱辨识.仿真结果表明,基于支持向量机的直接逆模型辨识方法在处理线性和非线性对象时,辨识性能都优于传统的BP神经网络,不仅辨识精度高,辨识速度快,而且泛化能力较强.     

一种基于粒子群优化的非线性系统辨识方法

针对单入单出离散时间非线性动态系统提出一种辨识方法.该方法采用带误差修正的改进泛模型作为非线性系统的结构模型,模型中的时变特征参量及误差修正系数采用粒子群（PSO）算法优化,优化后的模型可以逼近非线性系统.该方法简单、易于实现.通过对Box-Jenkins煤气炉数据等非线性被控对象的仿真研究及对模型的分析,表明了所提出算法的有效性.     

稳定的非线性系统广义预测控制

针对广义预测控制(GPC)算法稳定性分析困难,对参数未知非线性系统提出一种稳定广义预测控制(DGPC)方法。该方法首先将非线性系统转换为时变线性系统,然后利用三次样条基函数逼近时变系统中的系数,通过带时变遗忘因子的递推最小二乘算法辨识系数获得对象模型。基于模型通过性能指标中的前馈增益设计来保证控制系统稳定,仿真结果验证了该方法的有效性。     

一类非线性系统的自适应预测控制

针对一类非线性系统,将其等价为时变线性系统,然后用三次样条函数逼近时变系数,利用梯度算法在线辨识多项式的系数以实现时变系统的参数估计,最后运用广义预测控制策略,实现了对原非线性系统的自适应预测控制.仿真结果表明了所提方法的有效性.     

一类非线性系统的自适应预测控制

针对一类非线性系统, 将其等价为时变线性系统, 然后用三次样条函数逼近时变系数, 利用梯度算法在线辨识多项式的系数以实现时变系统的参数估计, 最后运用广义预测控制策略, 实现了对原非线性系统的自适应预测控制. 仿真结果表明了所提方法的有效性.     

Varieties of Codes and Kraft Inequality

Decipherability conditions for codes are investigated by using the approach of Guzman, who introduced in [7] the notion of variety of codes and established a connection between classes of codes and varieties of monoids. The class of Uniquely Decipherable (UD) codes is a special case of variety of codes, corresponding to the variety of all monoids. It is well known that the Kraft inequality is a necessary condition for UD codes, but it is not sufficient, in the sense that there exist codes that are not UD and that satisfy the Kraft inequality. The main result of the present paper states that, given a variety V of codes, if all the elements of V satisfy the Kraft inequality, then V is the variety of UD codes. Thus, in terms of varieties, Kraft inequality characterizes UD codes.     

基于代码检测的软件故障定位方法

针对现有软件故障定位方法的缺陷,提出了一种基于代码检测的软件故障定位方法,用嵌入式模块获取软件发生故障时的模块运行序列,分析出软件故障可疑模块集及其故障系数,在此基础上对故障模块进行代码的分类检测,根据上述过程中得到的结果进行综合分析运算,得出软件故障的可疑代码集和故障系数,采用代码分析辅助工具进行排查,定位故障。该方法已成功应用于软件密集型系统的故障诊断,能快速有效地实现软件故障定位。     

Performance Criteria for Constrained Nonlinear Programming Codes

A set of performance criteria for evaluating optimization software with respect to efficiency, reliability, and accuracy is presented and discussed. A numerical comparison of five constrained nonlinear programming codes is described, which was carried out in order to test the usefulness and general applicability of the proposed performance criteria. The results of the numerical comparison are discussed, and the proposed criteria are compared to the criteria traditionally used in comparative evaluations of nonlinear programming codes, with particular reference to machine dependence and the applicability to test problems with unknown solutions. A separate small scale computational experiment is described which was carried out specifically to test the machine dependence of the criteria. The observed deficiencies of the proposed new criteria are also discussed.     

Adaptive control of uncertain pure-feedback nonlinear systems

An adaptive control approach is proposed to solve the globally asymptotic state stabilisation problem for uncertain pure-feedback nonlinear systems which can be transformed into the pseudo-affine form. The pseudo-affine pure-feedback nonlinear system under consideration is with nonlinearly parameterised uncertainties and possibly unknown control coefficients. Based on the parameter separation technique, a novel backstepping controller is designed by adopting the adaptive high gain idea. The proposed control approach could avoid the drawbacks of the approximation-based approaches since no estimators are needed to estimate the virtual and the actual controllers. In addition, it could guarantee globally asymptotic state stabilisation even though there exist nonlinearly parameterised uncertainties in the considered system while comparing to the existing approximation-free approaches. A numerical and a realistic examples are employed to demonstrate the effectiveness of the proposed control method.     

A self-propelled robotic system with a visco-elastic joint: dynamics and motion analysis

This paper studies the dynamics and motion generation of a self-propelled robotic system with a visco-elastic joint. The system is underactuated, legless and wheelless, and has potential applications in environmental inspection and operation in restricted spaces which are inaccessible to human beings, such as pipeline inspection, medical assistance and disaster rescue. Locomotion of the system relies on the stick–slip effects, which interacts with the frictional force of the surface in contact. The nonlinear robotic model utilizes combined tangential-wise and normal-wise vibrations for underactuated locomotion, which features a generic significance for the studies on self-propelled systems. To identify the characteristics of the visco-elastic joint and shed light on the energy efficacy, parameter dependences on stiffness and damping coefficients are thoroughly analysed. Our studies demonstrate that the dynamic behaviour of the self-propelled system is mainly periodic and desirable forward motion is achieved via identification of the variation laws of the control parameters and elaborate selection of the stiffness and damping coefficients. A motion generation strategy is developed, and an analytical two-stage motion profile is proposed based on the system response and dynamic constraint analysis, followed by a parameterization procedure to optimally generate the trajectory. The proposed method provides a novel approach in generating self-propelled locomotion, and designing and computing the visco-elastic parameters for energy efficacy. Simulation results are presented to demonstrate the effectiveness and feasibility of the proposed model and motion generation approach.