基于小波逼近变换的非线性分布参数系统辨识

利用Haar小波正交规范基的微分运算矩阵及其运算性质,将描述一类非线性分布参数系统的偏微分方程转化为代数矩阵方程,结合最小二乘法,确定出待辨识的系统参数,避免了对偏微分方程进行多重积分运算的繁琐;并且,可以不考虑初始条件和边界条件,较其他采用积分运算矩阵的辨识方法要简单得多,简化了分布参数系统辨识的求解过程。该方法简单,计算量小,辨识精度高。仿真结果表明了该算法应用在非线性分布参数系统辨识中的有效性。     

时变非线性分布参数控制系统的小波辨识算法

基于正交函数逼近理论,在Haar小波正交规范基的基础上,总结并推导出了其积分运算矩阵、微分运算矩阵、乘积运算矩阵及其运算性质,并应用于一类时变非线性分布参数系统的辨识.借助于正交小波函数逼近方法对分布参数系统进行辨识,经正交小波逼近变换转化为代数矩阵方程,因此该方法可以不考虑初始条件和边界条件,较其他辨识方法要简单得多.该算法简单、计算量小、简化了分布参数系统辨识的求解过程,应用在分布参数系统辨识中不失为一种有效的分析方法.     

不确定拟哈密顿系统的随机最优控制

本文提出了不确定拟哈密顿系统、基于随机平均法、随机极大值原理和随机微分对策理论的一种随机极大极小最优控制策略.首先,运用拟哈密顿系统的随机平均法,将系统状态从速度和位移的快变量形式转化为能量的慢变量形式,得到部分平均的It随机微分方程;其次,给定控制性能指标,对于不确定拟哈密顿系统的随机最优控制,根据随机微分对策理论,将其转化为一个极小极大控制问题;再根据随机极大值原理,建立关于系统与伴随过程的前向-后向随机微分方程,随机最优控制表达为哈密顿控制函数的极大极小条件,由此得到最坏情形下的扰动参数与极大极小最优控制;然后,将最坏扰动参数与最优控制代入部分平均的It随机微分方程并完成平均,求解与完全平均的It随机微分方程相应的Fokker-Planck-Kolmogorov(FPK)方程,可得受控系统的响应量并计算控制效果;最后,将上述不确定拟哈密顿系统的随机最优控制策略应用于一个两自由度非线性系统,通过数值结果说明该随机极大极小控制策略的控制效果.     

基于Taylor级数的分布参数系统最优控制

结合钢坯加热过程讨论了分布参数系统的最优控制问题.针对钢坯加热过程,建立了分布参数系统的数学模型,利用Taylor级数近似变换,并引入Taylor级教基函数的微分运算矩阵和向量积矩阵,将钢坯温度的最优控制问题转化为相应集总参数系统的最优控制问题,然后对集总参数系统进行求解,并将求得的逼近解进行逆变换,即求得分布参数系统最优控制的逼近解.并通过仿真示例验证了该算法的有型,取得了满意的结果,为分布参数系统的控制算法提出了一条解决方案.     

基于小波算法的二阶线性定常分布参数系统的辨识

本文基于正交函数逼近方法,借助于小波变换,并利用其运算矩阵及其运算性质,研究了分布参数系统的辨识问题。将Haar小波正交基应用于分布参数系统的辨识中,经正交小波逼近变换,将原偏微分描述的分布参数系统转化为代数矩阵方程,并且,考虑了初始条件和边界条件,获得了算法简单、计算方便、具有较高精度的辨识算法,简化了分布参数系统辨识的求解过程,应用在分布参数系统辨识中不失为一种有效的分析方法。仿真实例表明了本文所提出的算法的有效性。     

分布参数系统边界控制的Haar小波算法

由于分布参数系统通常由偏微分方程描述,采用解析法求解分布参数系统最优边界控制问题,是非常难以解决的.正交函数逼近的方法在分布参数系统控制方面,已经取得了较好的效果.Haar小波作为正交基函数,利用小波的一些运算及变换矩阵,将分布参数系统转化为集总参数系统,再求其逼近解.仿真示例验证了所提出的算法是非常有效的.该方法为分布参数系统的控制算法提出了一条新的解决方案.     

偏微分方程的算子自定义小波解耦算法研究

利用小波算法求解偏微分方程最困难的问题是随着尺度的升高,系统方程的耦合度越来越高,极大降低了计算效率和精度.针对此问题提出了采用算子自定义小波的多尺度解耦算法,首先建立有限元多分辨空间和小波细化关系,提出偏微分方程的多尺度计算理论方法.在优化方案的基础上,提出算子自定义小波的构造方法及解耦条件.改进方法的突出优点在于根据工程问题的实际需要灵活构造具有期望特性的小波基.提出偏微分方程的多尺度算子自定义小波算法,充分利用算子自定义小波的嵌套逼近和尺度解耦特性,实现问题的高效求解.仿真结果表明,改进的算子自定义小波解耦算法具有计算效率高、精度高等特点.     

基于Taylor级数的分布参数系统最优控制

结合钢坯加热过程讨论了分布参数系统的最优控制问题。针对钢坯加热过程,建立了分布参数系统的数学模型,利用Taylor级数近似变换,并引入Taylor级数基函数的微分运算矩阵和向量积矩阵,将钢坯温度的最优控制问题转化为相应集总参数系统的最优控制问题,然后对集总参数系统进行求解,并将求得的逼近解进行逆变换,即求得分布参数系统最优控制的逼近解。并通过仿真示例验证了该算法的有型,取得了满意的结果,为分布参数系统的控制算法提出了一条解决方案。     

基于小波变换的线性定常分布参数系统最优逼近控制

借助于正交函数逼近方法研究了线性定常分布参数系统的最优控制问题,将Haar小波正交基应用于分布参数系统的最优控制,获得了性能较好的最优控制逼近算法.仿真实例说明了算法的有效性.     

具有不等式路径约束的微分代数方程系统的动态优化

针对具有不等式路径约束的微分代数方程（Differential-algebraic equations，DAE）系统的动态优化问题，通常将DAE中的等式路径约束进行微分处理，或者将其转化为点约束或不等式约束进行求解.前者需要考虑初值条件的相容性或增加约束，在变量间耦合度较高的情况下这种转化求解方法是不可行的；后者将等式约束转化为其他类型的约束会增加约束条件，增加了求解难度.为了克服该缺点，本文提出了结合后向差分法对DAE直接处理来求解上述动态优化问题的方法.首先利用控制向量参数化方法将无限维的最优控制问题转化为有限维的最优控制问题，再利用分点离散法用有限个内点约束去代替原不等式路径约束，最后用序列二次规划（Sequential quadratic programming，SQP）法使得在有限步数的迭代下，得到满足用户指定的路径约束违反容忍度下的KKT（Karush Kuhn Tucker）最优点.理论上证明了该算法在有限步内收敛.最后将所提出的方法应用在具有不等式路径约束的微分代数方程系统中进行仿真，结果验证了该方法的有效性.     

Control input separation by actuation mode expansion for flow control problems

A control input separation method is proposed for reduced-order modelling in boundary control problems. The dynamics of flow systems are typically described by partial differential equations where the input affects the system through boundary conditions. From a control design perspective it is most desirable and natural to employ finite-dimensional representations in which the input enters the dynamics directly. The method proposed here to resolve the input from the boundary conditions is based on obtaining a proper orthogonal decomposition of the unforced flow of the system, and then augmenting this decomposition by optimally computed actuation modes, built using snapshots of the actuated flow. A reduced-order Galerkin model is then derived for this expansion, in which the input appears as an explicit term in the system dynamics. The model reduces exactly to the original baseline case under zero input conditions. The proposed method is then compared to an existing input separation technique, namely the sub-domain separation method. A boundary control example regarding the 2D incompressible Navier–Stokes equation is considered to illustrate the proposed method, where a controller is designed to achieve tracking of a desired 2D spatial profile for the flow velocity.     

New spatial basis functions for the model reduction of nonlinear distributed parameter systems

The selection of spatial basis functions is important for the model reduction of nonlinear distributed parameter systems (DPSs). Such a selection will significantly affect the accuracy and efficiency of modeling. The current study proposes new spatial orthogonal basis functions for the model reduction of nonlinear DPSs. Each new spatial basis function is a linear combination of the orthogonal eigenfunctions of such systems. The basis function transformation matrix is obtained using the balanced truncation method, which results in a straightforward derivation of the transformation matrix and low computation cost. This performance is proven theoretically. A numerical example is used to demonstrate the effectiveness of the proposed method.     

关于一类分布参数系统的快速控制问题

本文研究了某类分布参数系统快速控制表达式.用一种新方法证明了快速控制属于允 许控制集合的边界,并求出了最速时间应满足的方程,因此可由计算机求出最速时间的数值. 最后举出了计算实例,说明本文方法可用于计算受控弹性梁的快速镇定等问题.     

Optimal control of switched systems based on parameterization of the switching instants

This paper presents a new approach for solving optimal control problems for switched systems. We focus on problems in which a prespecified sequence of active subsystems is given. For such problems, we need to seek both the optimal switching instants and the optimal continuous inputs. In order to search for the optimal switching instants, the derivatives of the optimal cost with respect to the switching instants need to be known. The most important contribution of the paper is a method which first transcribes an optimal control problem into an equivalent problem parameterized by the switching instants and then obtains the values of the derivatives based on the solution of a two point boundary value differential algebraic equation formed by the state, costate, stationarity equations, the boundary and continuity conditions, along with their differentiations. This method is applied to general switched linear quadratic problems and an efficient method based on the solution of an initial value ordinary differential equation is developed. An extension of the method is also applied to problems with internally forced switching. Examples are shown to illustrate the results in the paper.     

Sequential linear quadratic control of bilinear parabolic PDEs based on POD model reduction

We present a framework to solve a finite-time optimal control problem for parabolic partial differential equations (PDEs) with diffusivity-interior actuators, which is motivated by the control of the current density profile in tokamak plasmas. The proposed approach is based on reduced order modeling (ROM) and successive optimal control computation. First we either simulate the parabolic PDE system or carry out experiments to generate data ensembles, from which we then extract the most energetic modes to obtain a reduced order model based on the proper orthogonal decomposition (POD) method and Galerkin projection. The obtained reduced order model corresponds to a bilinear control system. Based on quasi-linearization of the optimality conditions derived from Pontryagin’s maximum principle, and stated as a two boundary value problem, we propose an iterative scheme for suboptimal closed-loop control. We take advantage of linear synthesis methods in each iteration step to construct a sequence of controllers. The convergence of the controller sequence is proved in appropriate functional spaces. When compared with previous iterative schemes for optimal control of bilinear systems, the proposed scheme avoids repeated numerical computation of the Riccati equation and therefore reduces significantly the number of ODEs that must be solved at each iteration step. A numerical simulation study shows the effectiveness of this approach.     

求解非线性期权定价模型的自适应小波同伦摄动技术

Leland 模型是在考虑交易费用的情况下,对 Black - Scholes 模型进行修改得到的非线性期权定价模型. 本文针对 Leland 模型,提出了一种求解非线性动力学模型的自适应多尺度小波同伦摄动法. 该方法首先利用插值小波理论构造了用于逼近连续函数的多尺度小波插值算子,利用该算子可以将非线性期权定价模型方程自适应离散为非线性常微分方程组; 然后将用于求解非线性常微分方程组的同伦摄动技术和小波变换的动态过程相结合,构造了求解 Leland 模型的自适应数值求解方法. 数值模拟结果验证了该方法在数值精度和计算效率方面的优越性.     

Cyber-physical Systems as General Distributed Parameter Systems: Three Types of Fractional Order Models and Emerging Research Opportunities

Cyber-physical systems (CPSs) are man-made complex systems coupled with natural processes that, as a whole, should be described by distributed parameter systems (DPSs) in general forms. This paper presents three such general models for generalized DPSs that can be used to characterize complex CPSs. These three different types of fractional operators based DPS models are: fractional Laplacian operator, fractional power of operator or fractional derivative. This research investigation is motivated by many fractional order models describing natural, physical, and anomalous phenomena, such as sub-diffusion process or super-diffusion process. The relationships among these three different operators are explored and explained. Several potential future research opportunities are then articulated followed by some conclusions and remarks.      

Exact computation of traces and H/sup 2/ norms for a class of infinite-dimensional problems

We derive a formula for the trace of a class of differential operators defined by forced two point boundary value problems. The formula involves finite-dimensional computations with matrices whose dimension is no larger than the order of the differential operator. Thus, we achieve an exact reduction of an infinite-dimensional problem to a finite-dimensional one. We relate this trace calculation to computation of the H/sup 2/ norm for certain infinite-dimensional systems. An example from fluid dynamics is included to illustrate the method.