混沌的模糊神经网络逆系统控制

提出用Sugeno型的模糊推理神经网络建立混沌系统的逆系统模型,并采用逆系统方法进行混沌的控制.这种方法的特点是可以不必建立混沌系统的解析模型,通过模糊神经网络学习混沌系统的运动规律,通过学习获得的规律对混沌进行有效的控制,并且该控制方法可以控制混沌系统以一定精度跟踪连续变化的给定信号.理论分析及针对虫口模型和Henon模型仿真研究证明了该方法的有效性 关键词： 混沌 模糊神经网络 逆系统控制     

Application of stochastic optimal control to the suboptimal design of thrust-mass profiles

Stochastic optimal control techniques are applied to compare the performance of identical medium-range air-to-air missiles which have different thrust-mass profiles. The measure of the performance is the probability of reaching a lock-on-point with a favorable range of guidance and flight parameters, during a fixed time interval [0,t _f ], given that, during the flight, the trajectories of the missile are subjected to a variety of constraints including dynamic pressure constraints.     

叶栅全三维粘性反问题的数值解

本文发展了一种解叶栅全三维粘性反问题的新的数值方法.基于非正交曲线坐标与相应的非正交速度分量下完全守恒型的Navier－Stokes方程,全三维反问题规定叶片表面的无量纲压力分布反求叶型。计算中叶片表面的边界条件采用一种特殊的方式来处理，即一方面强加给定的压力分布条件,另方面叶面的几何位置在迭代过程中又是可移动的，其移动速度将与Navier—Stokes方程在当地的解联系起来，从而形成一种解定常问题的新的不定常过程.试算证明了本文方法的可行性。     

柔性变截面滑移式机械手的控制

研究了柔性变截面滑移式机械手臂的控制。首先，基于有限元法导出系统的动力学方程，然后分别建立了两种控制方式的状态方程：１）以加速度和角加速度作为控制变量：２）以力和力矩作为控制变量。控制过程分为“粗控”和“精控”两步进行。“精控”过程采用线性二次型高斯控制。最后给出了数值模拟的结果。     

生料配料系统的回归-校正控制方法研究

针对通常生料配料系统所出现的问题,提出了对生料配料过程进行多目标综合控制的基本思想,在这一基础上,给出了控制生料饱和参数、生料成分的系统控制结构,并着重论述了饱和系数回归分析与回归控制及成分校正控制的原理、模型与方法。     

W-算子在设计电气传动控制系统中的应用

本文利用作者最近提出的一种新的算子方法——W-算子方法,从理论和应用方面探讨了电气传动控制系统的设计问题,并对算法的收敛性进行了分析。该算法具有结构简单,算法严密,计算方便的特点,避免了实际应用中用传统最优控制方法设计所带来的困难。     

浅水中污染物扩散的自适应有限元分析法

介绍浅水中污染物扩散分析中的有限元法.分析包括两个部分:1)流场速度、水面高度的计算;2)根据扩散模型计算污染物浓度场.联合使用了自适应网格技术以期提高解的精度,同时减少计算时间和计算机内存的消耗.通过几个有已知解的实例验证了有限元公式和计算机程序.最后,使用这种联合方法分析泰国Chao Phraya河附近海湾中的污染物扩散.     

“Slow” active control of combustion instabilities by modification of liquid fuel spray properties

This paper describes an experimental investigation of the feasibility of using “slow” active control approaches, which “instantaneously” change liquid fuel spray properties, to suppress combustion instabilities. The objective of this control approach was to break up the feedback between the combustion process heat release and combustor pressure oscillations that drive the instability by changing the characteristics of the combustion process (e.g., the characteristic combustion time). To demonstrate the feasibility of such control, this study used a proprietary fuel injector (Nanomiser^TM), which can vary its fuel spray properties, to investigate the dependence of acoustics–combustion process coupling, i.e., the driving of combustion instabilities, upon the fuel spray properties. This study showed that by changing the spray characteristics it is possible to significantly damp combustion instabilities. Furthermore, using combustion zone chemiluminescence distributions, which were obtained by Abel’s deconvolution synchronized with measured acoustic data, it has been shown that the instabilities were mostly driven midway between the combustor centerline and wall, a short distance downstream from the flame holder, where the mean axial flow velocity is approximately zero in the vortex near the flame holder. The results of this study strongly suggest that a “slow” active control system that employs controllable fuel injectors could be effectively used to prevent the onset of detrimental combustion instabilities.     

A numerical experimental study of inverse preconditioning for the parallel iterative solution to 3D finite element flow equations

Integration of the subsurface flow equation by finite elements (FE) in space and finite differences (FD) in time requires the repeated solution to sparse symmetric positive definite systems of linear equations. Iterative techniques based on preconditioned conjugate gradients (PCG) are one of the most attractive tool to solve the problem on sequential computers. A present challenge is to make PCG attractive in a parallel computing environment as well. To this aim a key factor is the development of an efficient parallel preconditioner. FSAI (factorized sparse approximate inverse) and enlarged FSAI relying on the approximate inverse of the coefficient matrix appears to be a most promising parallel preconditioner. In the present paper PCG using FSAI, diagonal and pARMS (parallel algebraic recursive multilevel solvers) preconditioners is implemented on the IBM SP4/512 and CLX/768 supercomputers with up to 32 processors to solve underground flow problems of a large size. The results show that FSAI may allow for a parallel relative efficiency larger than 50% on the largest problems with p=32 processors. Moreover, FSAI turns out to be significantly less expensive and more robust than pARMS. Finally, it is shown that for p in the upper range may be much improved if PCG–FSAI is implemented on CLX.     

Estimates for Elements of Inverse Matrices for a Class of Operators with Matrices of Special Structure

In this paper, we consider questions related to the structure of inverse matrices of linear bounded operators acting in infinite-dimensional complex Banach spaces. We obtain specific estimates of elements of inverse matrices for bounded operators whose matrices have a special structure. Matrices are introduced as special operator-valued functions on an index set. The matrix structure is described by the behavior of the given function on elements of a special partition of the index set. The method used for deriving the estimates is based on an analysis of Fourier series of strongly continuous periodic functions.