MIMO离散时间系统混合l1/H2控制

研究了MIMO(多输入多输出)离散时间系统的混合l1/H2优化问题,该问题可描述为最优化一个传递函数矩阵的l1范数同时保证另一个传递函数矩阵的H2范数满足预定的指标.研究了最优目标函数值关于H2范数指标的连续性.证明了MIMO系统混合l1/H2控制问题最优解的存在性.由于基于标定-Q (scaled-Q)方法求解MIMO混合l1/H2问题,避免了进行零点插值运算的困难.通过求解有限维非线性规划问题可得到最优目标值的收敛的上下界.     

基于变量分离和交替最小化的图像修复

提出变量分离和交替最小化相结合解决l1正则优化问题,并用于非纹理图像的修复。基于变量分离技术,该算法将目标函数的l1成分和l2成分解耦,l1正则优化问题简化为一系列非约束优化问题。除了交替最小化迭代地求解这些非约束优化问题,还引入投影法加快和简化求解过程。实验在有噪声和无噪声的情况下,用提出的算法对信息丢失30%的图像进行修复。实验结果表明：该算法可有效解决包括图像修复在内的一系列图像复原问题;与某些同类算法相比,在修复速度和修复效果方面均具有优势。     

基于支持向量机的可分离非线性动态系统辨识

针对状态变量和控制变量可分离的非线性动态系统模型,通过引入两个非线性核函数重新设计了标准支持向量机的回归估计模型,使之适用于非线性动态系统的辨识. 它包含两个分别关于状态变量和控制变量的非线性函数,用于辨识可分离变量非线性动态系统中的两个非线性函数.文中的仿真实验验证了我们算法用于非线性动态系统辨识的有效性.     

基于l1-非凸非光滑函数的图像恢复方法

针对有整齐边界且加性噪声满足均匀、椒盐、拉普拉斯等非高斯分布的图像,根据逐步拟合及变量转换思想,提出一种基于l1-非凸、非光滑函数的逐步非凸图像恢复方法。根据原始非凸、非光滑函数建立一组拟合函数,获得原始问题的优良初始值,利用变量转换解决l1-非凸、非光滑函数的非可微性问题。实验结果表明,该方法恢复的图像效果较好,峰值信噪比较高。     

基于观测器的l~1鲁棒故障检测方法

基于参数化的控制系统输出观测器 ,将鲁棒控制理论中的l1最优化方法用于故障检测技术 ,提出一种新的控制系统鲁棒故障检测方法 .通过求解一个混合 0 1型整数线性规划问题 ,可得出l1优化残差函数 .仿真结果验证了所提方法的有效性     

具有时滞和干扰的多变量系统预测函数控制方法的研究

提出了一种新的多变量系统预测函数控制算法,该方法可以适用于具有时滞和外部干扰的多变量系统。利用该控制算法可得到一个解析的控制量计算方程,其中各个控制器参数均可离线计算,因此在线时算法简单,计算量小,可以广泛用于解决各种快、慢速对象的控制问题。仿真结果表明该多变量预测函数控制律具有克服干扰和时滞、跟踪性能好、控制精度高等特点。     

计算机符号积分系统INTG

本文给出了一个新的计算机符号积分系统INTG,可用于求解单变量初等函数的不定积分.该系统已在AI-M16微型机上实现.它可求解使用一种数学手册[1]上的不定积分表所能解决的大部分问题,并具有一定可扩充性.系统使用了符号处理与数值方法相结合的方法求有理函数积分,采用了连分数变换法求整系数多项式的所有实根.系统还可以根据用户要求,显示积分路径的有关信息.     

(2+1)维广义Borer-Kaup系统的变量分离解和半包局域结构

基于一个特殊的Painlev啨Bcklund变换和多线性变量分离方法,分析了(2+1)维非线性广义BorerKaup(GBK)系统,求得了该系统具有若干任意函数的变量分离严格解.根据得到的变量分离严格解,并通过选择解中的任意函数,引入恰当的局域函数和多值函数,找到了GBK系统一种新的具有实际物理意义的半包局域相干结构,如海洋表面波,并简要地讨论了这种半包局域相干结构的一些特殊的演化性质.结果表明:这种半包局域相干结构相互作用后,完全保持它们原有的速度、波形和波幅,即它们的演化性质是完全弹性的.     

求解量子系统时间最优控制问题的同伦算法研究

针对数值求解量子系统时间最优控制问题中反复调用梯度算法导致计算量大的问题,本文提出一类同伦算法用以快速求解量子系统的时间最优控制问题.与已有算法不同,这一算法通过引入同伦变量在减小终端时间的方向上搜索最优解.在这一算法中,可通过自由函数构造保真度函数对控制变量的梯度方向,也可通过方向函数引导算法的搜索方向,以加快算法的搜索速度.本文将这一算法用于求解量子系统态转移和门变换的时间最优控制问题.仿真结果表明这一算法的有效性.     

一种用于线性参数的l1数据拟合的新方法

采用l1范数准则函数对数据进行拟合的方法称为l1数据拟合.提出了当测量数据列中存在个别数据有较大测量误差时,采用l1准则函数进行数据拟合要优于二次性准则函数.通过建立l1准则函数与二次准则函数间的关系,讨论一种用于线性参数的l1数据拟合的新方法,并给出了相关的结论.     

遗传算法在混合H_2/H_∞优化控制设计中的应用

介绍了现已成为关键智能计算之一的一种新的全局优化搜索算法—遗传算法，并探讨了在混合Ｈ２／Ｈ∞最优指标下优化控制设计中的应用。其最大特点是：本质并行、全局优化，它不要求目标函数连续和可微，比梯度法和随机搜索算法更适合于ＰＩＤ混合Ｈ２／Ｈ∞优化问题。     

An efficient robust optimization method with random and interval uncertainties

This paper develops a new mixed uncertainty robust optimization (MURO) method with both random and interval uncertainties. Existing strategies in literature always treat the system performance as a sequence of probability distribution with the interval factors varying within their domains. Moreover, the robust design objective and constraints are modeled in the form of combination of interval mean and interval deviations of performances, which cannot offer a quantitative robustness measurement of a design. The new MURO method is based on the sensitivity region concept and a hybrid robustness index is developed to represent the possibility that the uncertain vector locates within the worst-case sensitivity region (WCSR). This proposed index can offer a more quantitative and intuitive way to evaluate the robustness of a design. With the hybrid indices, the traditional robust optimization problem can be converted to an ordinary optimization with the robustness index constraints. Two numerical examples and two engineering examples with different combinations of interval and random factors are illustrated to demonstrate the applicability and efficiency of the proposed algorithm. The comparison results show that the new method can reduce the conservatism of previous method significantly with fewer computational efforts.     

Eulerian shape design sensitivity analysis and optimization with a fixed grid

Conventional shape optimization based on the finite element method uses Lagrangian representation in which the finite element mesh moves according to shape change, while modern topology optimization uses Eulerian representation. In this paper, an approach to shape optimization using Eulerian representation such that the mesh distortion problem in the conventional approach can be resolved is proposed. A continuum geometric model is defined on the fixed grid of finite elements. An active set of finite elements that defines the discrete domain is determined using a procedure similar to topology optimization, in which each element has a unique shape density. The shape design parameter that is defined on the geometric model is transformed into the corresponding shape density variation of the boundary elements. Using this transformation, it has been shown that the shape design problem can be treated as a parameter design problem, which is a much easier method than the former. A detailed derivation of how the shape design velocity field can be converted into the shape density variation is presented along with sensitivity calculation. Very efficient sensitivity coefficients are calculated by integrating only those elements that belong to the structural boundary. The accuracy of the sensitivity information is compared with that derived by the finite difference method with excellent agreement. Two design optimization problems are presented to show the feasibility of the proposed design approach.     

Interconnection-based performance analysis for a class of decentralized controllers

This paper is concerned with decentralized controller design for large-scale interconnected systems of pseudo-hierarchical structure. Given such a system, one can use existing techniques to design a decentralized controller for the reference hierarchical model, obtained by eliminating certain weak interconnections of the original system. Although this indirect controller design is appealing as far as the computational complexity is concerned, it does not necessarily result in satisfactory performance for the original pseudo-hierarchical system. An LQ cost function is defined in order to evaluate the performance discrepancy between the pseudo-hierarchical system and its reference hierarchical model under the designed decentralized controller. A discrete Lyapunov equation is then solved to compute this performance index. However, due to the large-scale nature of the system, this equation cannot be handled efficiently in many real-world systems. Thus, attaining an upper bound on this cost function can be more desirable than finding its exact value, in practice. For this purpose, a novel technique is proposed which only requires solving a simple LMI optimization problem with three variables. The problem is then reduced to a scalar optimization problem, for which an explicit solution is provided. It is also shown that when the original model is exactly hierarchical, then the upper bounds obtained from the LMI and scalar optimization problems will both be equal to zero.     

不确定离散系统的最优保性能控制*

对一类具有范数有界时变参数不确定性的离散时间线性系统和一个二次型性能指标,研究其最优保性能状态反馈控制律的设计问题。     

一种基于LMI的鲁棒故障诊断滤波器设计

研究了一类含有扰动的线性系统鲁棒故障诊断滤波器设计问题. 文中引入一种能同时体现残差对扰动信号鲁棒性和对故障信号灵敏性的性能指标, 利用H_∞理论把求解滤波器的问题转化为H_∞优化设计问题. 应用线性矩阵不等式(LMI)技术, 对此性能指标进行优化, 给出并证明了该设计问题解的存在性条件和滤波器增益阵的求解方法, 最后, 通过仿真实例验证了方法的有效性.     

A mixed PI/VI design method for nonlinear H∞ Control

This paper proposes a new mixed policy iteration and value iteration (PI/VI) design method for nonlinear H_∞ control based on the theories of polynomial optimization and Lasserre's hierarchy. The design of a mixed PI/VI controller can be carried out in four steps: firstly, initialize design parameters and expand nonlinear system matrices; secondly, obtain a polynomial matrix inequality for policy improvement; thirdly, obtain the Lasserre's hierarchy of a global polynomial optimization problem for value improvement; fourthly, perform the mixed PI/VI algorithm to approximate the optimal nonlinear H_∞ control law. The novelty of this work lies in that the problem of designing a nonlinear H_∞ controller is translated into a polynomial global optimization problem, which can be solved by Lasserre's hierarchy directly, and then, the mixed PI/VI algorithm is presented to approximate the optimal nonlinear H_∞ control law by updating global optimizers iteratively. The main results of this paper consist of the mixed PI/VI algorithm and the related three theorems, which guarantee robust stability and performance of the closed‐loop nonlinear system. Numerical simulations show that the mixed PI/VI algorithm converges very fast and achieves good robust stability and performance in transient behavior, disturbance rejection, and enlarging the domain of attraction of the close‐loop system.     

一种新的时滞系统鲁棒故障诊断滤波器设计方法

研究具有扰动不确定的状态时滞系统鲁棒故障诊断滤波器的设计问题.通过对系统传递函数输入输出通道的组合变换,引入一种能够同时体现残差对扰动信号鲁棒性和对故障信号灵敏性的性能指标,将基于状态观测器的鲁棒故障诊断滤波器设计问题转化为H∞优化设计问题,应用线性矩阵不等式(LMI)技术,给出并证明了该设计问题解存在的条件和求解方法.最后,通过一个仿真算例来验证本方法的有效性.     

基于BMI的一类不确定分段线性系统的最优控制设计

将不确定分段线性系统的最优控制问题转化成最优控制性能界的优化问题．其中性能上界的优化是以反馈增益为寻优参数的一组双线性矩阵不等式(BMI)问题，对此将遗传算法和内点法结合， 设计了一种混合算法进行求解．最后的算例表明控制律的设计及其求解算法的有效性．     

Robust optimization with convex model considering bounded constraints on performance variation

In robust optimization, double-looped structures are often adopted where the outer loop is used to seek for the optimal design and the optimization performed in the inner loop is for the robustness assessment of the candidate solutions. However, the double-looped techniques usually will lead to a significant increase in computational efforts. Therefore, in this paper, a new robustness index is developed to handle bounded constraints on performance variation where no optimization run is required for the robustness evaluation work in the inner loop. The computation of this new index is based on the sensitivity Jacobian matrix of the system performances with respect to the uncertainties and it can quantitatively measure the maximal allowable magnitude of system variations. By introducing this index, the robust design problem can be reformulated as a deterministic optimization with robustness indices requirements. Two numerical examples are tested to show the effectiveness and efficiency of the proposed approach, whose solutions and computational efforts are compared to those from a double-looped approach proposed in previous literature.