Efficient solution of non-Markovian covariance evolution equations in fluid turbulence

A method is described for efficient treatment of the time-history effects that arise in closure models constructed by truncation of renormalized perturbation expansions. The scheme is based on rational polynomial (Padé) approximations for the time-lagged functions, combined with Gaussian quadrature applied to a coarse-time evolution equation for equal-time covariances. Power series coefficients required for the Padé approximants are generated by recursion relations resulting from successive differentiation of the slow-varying form of the dynamic equations for time-lagged functions. This strategy is illustrated by applications to equations of the direct interaction approximation for fluid turbulence. Several benefits accrue from such an approach. Computational efficiency comparable to that of Markovian closures is obtained without introduction of arbitrary constants orad hoc Markovianization assumptions: (1) Scaling of the leading operations count is reduced fromO(n _T ³ ) toO(n _g n _t ), wheren _T is the number of steps in coarse time, and n_g 4–8. For typical problems in fluid turbulence, this results in savings of afactor40 in computing time. (2) Scaling of working array size is reduced fromO(n _T ² ) toO(p), wherep is the order of Padé approximant; this reduces in-core storage requirements for dynamical quantities by afactor 20. These and other advantages depend on the order of Padé approximant required to give acceptable accuracy. Test cases from several problems in fluid turbulence indicate very substantial savings, such that certain CPU-intensive problems with spatial inhomogeneities become computationally feasible.     

A new analytical study of MHD stagnation-point flow in porous media with heat transfer

The similarity solution for the MHD Hiemenz flow against a flat plate with variable wall temperature in a porous medium gives a system of nonlinear partial differential equations. These equations are solved analytically by using a novel analytical method (DTM-Padé technique which is a combination of the differential transform method and the Padé approximation). This method is applied to give solutions of nonlinear differential equations with boundary conditions at infinity. Graphical results are presented to investigate influence of the Prandtl number, permeability parameter, Hartmann number and suction/blowing parameter on the velocity and temperature profiles.     

Development and Applications of Holonic Manufacturing Systems: A Survey

This paper surveys the literature in the holonic manufacturing systems area in an attempt to bring together the key issues in the development and applications of holonic systems. A brief introduction presents the characteristics of today’s manufacturing environment and the requirements for next generation manufacturing systems. Then, starting with considerations about the origins of the holonic concept and its first applications in manufacturing, the paper presents the advances made in applying the holonic concept to manufacturing systems area. Several considerations for the development of holonic manufacturing systems and specific holonic system requirements are discussed. As holonic concept is considered a solution for next generation manufacturing systems, there is a significant number of applications and implementations of the holonic concept in manufacturing systems domain. The most important and relevant approaches developed so far are presented. Finally, a short conclusion and future research directions in the area are provided     

A general framework of a Reference Model for Intelligent Integrated Manufacturing Systems (REMIMS)

Today's highly competitive business environment forces the managers to continuously make the best decisions in the shortest possible time. The ability to provide concurrency among manufacturing functions is a critical need for modern organizations as, especially, distributed environment requires synchronization of manufacturing functions. Moreover, manufacturing companies need to have strong capability of adaptation (agility) mainly because of the dynamic relationships that must be established between manufacturing units. To achieve these, there is a need for an integrated manufacturing system that will handle all interactions and interrelationships which will then be affected by the changes and create maximum gain under limited resources. In order to create and effectively manage such an integrated manufacturing system there is a need for a reference model. In this paper, such a reference model called REference Model for intelligent Integrated Manufacturing System (REMIMS) is introduced. REMIMS has hierarchical architecture with several agents responsible for different manufacturing functions. To facilitate REMIMS and allow interaction among the agents to share their knowledge, a specific knowledge exchange protocol in a knowledge network is being developed.     

Modeling, Analysis, and Optimal Control of a Class of Hybrid Systems

We propose a modeling framework for a class of hybrid systems which arise in many manufacturing environments and study related optimal control problems. In this framework, discrete entities have a state characterized by a temporal component whose evolution is described by event-driven dynamics, and a physical component whose evolution is described by time-driven dynamics. As a first step towards developing an optimal control theory for such hybrid systems, we formulate a problem consisting of a single-stage manufacturing process and use calculus of variations techniques to obtain structural properties and an explicit algorithm for deriving optimal policies.     

Conception and Implementation of an Object Request Broker for the Integration of the Process Level in Manufacturing Systems

In order to be able to react quickly to altering production states, planning tools such as Manufacturing Resource Planning and Enterprise Resource Planning heavily rely on up to date information about the process itself. Thus, access to process level data is one of the most important issues within the production industry. However, the process level lacks support for open, connective communication systems as the number of incompatible fieldbus systems shows. Current solutions, e.g., OLE for Process Control, only focus on a unified interface to the process level, but do not allow to access the functionality of a field device directly. The approach presented in this paper introduces FIMO, the Fieldbus Messaging Object Request Broker, to be deployed in field devices and utilizing the existing fieldbus protocols. With the use of FIMO, devices connected to a fieldbus can be seamlessly integrated in the whole manufacturing hierarchy. The paper gives a brief overview of thestate of the art for accessing process level data. Then, the FIMO architecture is presented in detail including its core services and the mapping of the communication services to the underlying fieldbus system.     

Adaptive-Predictive Control of a Class of SISO Nonlinear Systems

In this paper, an adaptive-predictive control algorithm is developed for a class of SISO nonlinear discrete-time systems based on a generalized predictive control (GPC) approach. The design is model-free, based directly on pseudo-partial-derivatives derived on-line from the input and output information of the system using a recursive least squares type of identification algorithm. The proposed control is especially useful for nonlinear systems with vaguely known dynamics. Robust stability of the closed-loop system is analyzed and proven in the paper. Simulation and real-time application examples are provided for real nonlinear systems which are known to be difficult to model and control.     

An Internal-Model Controller for a Class of Single-Input Single-Output Nonlinear Systems: Stability and Robustness

A controller design procedure for a class of nonlinear systems is presented. The structure of the control system corresponds to the so-called internal-model controller that, for linear systems, has exhibited good performance and stability robustness with respect to disturbances and to uncertainty in the plant parameters. The systems involved are single-input single-output and fully linearizable by coordinates transformation and state feedback. It is shown that the plant output converges to a constant reference, even under the presence of constant disturbances and parameter uncertainties, provided the closed-loop system has an asymptotically stable equilibrium point placed anywhere. This scheme does not need an explicit design of a nonlinear observer; instead, it uses the state of a plant model. A conservative stability robustness margin is estimated by applying standard results of Lyapunov theory.     

一类网络控制系统的建模及分析

网络控制系统由于将通信网络引入控制系统的闭环反馈中,使得对其的分析、仿真和设计非常复杂。作为这些工作的基础,对网络控制系统如何建模以及建立合适的模型,意义尤显重要。在给出一定合理假设的条件下,对通信网络只存在于传感器和控制器之间的一类网络控制系统结构进行了分析,建立了其适当的数学模型。考虑到网络控制系统中通信网络的存在会导致多数据包传输的情况,因此在给出模型的基础上,又建立了多数据包传输的网络控制系统模型,并做了分析。     

Output Feedback Stabilization of a Class of Uncertain Nonaffine Nonlinear Systems

In this paper, output feedback control is presented for a general class of uncertain nonaffine nonlinear systems, that does not rely on state estimation. Under the condition that only the system output is available for feedback, a dynamic linear filter is built to estimate unknown nonlinearities, and an output feedback controller is developed to stabilize the systems by utilizing the estimation to compensate for the unknown nonlinearities. One important feature of the proposed control is that the controller is developed under mild conditions with simple control algorithms, which is of great significance in engineering practice. Simulation results show the effectiveness of the control approach.     

一类诱导时滞网络控制系统自抗扰控制器设计

针对一类具有网络时滞小于采样周期的网络控制系统提出网络控制的主要问题是网络通信系统模型的不确定性导致控制性能不佳;针对这一问题,采用基于无模型的自抗扰算法,将网络环节和被控对象一同视为控制对象,将网络时滞作为被控对象的不确定性因素,利用扩张状态观测器对不确定性因素进行实时观测估计;Matlab/TrueTime网络控制实验表明:自抗扰控制方法能够有效地减小网络诱导时滞对控制系统的影响。     

一类非线性系统的输出反馈模糊控制

针对一类具有不确定性的非线性系统，提出一种模糊控制方案，控制中只利用系统输出信号和一些辅助信号。利用李亚鲁诺夫方法证明了闭环模糊控制系统全局稳定．仿真表明该控制方案可回避通常滑模控制中不可避免的颤动，且系统具有很强的鲁棒性。     

Integration of Hardware and Software Platforms in Creating Manufacturing Computer Systems

An approach to the choice of an optimum combination of hardware and software platforms as a basis of a computer system is proposed. The procedures of choice and estimation criteria proposed are oriented towards the implementation in the form of a "business logic" algorithm embedded into an interactive information support system.     

一类非线性系统鲁棒自适应控制器

反步设计法是针时不确定非线性系统的进行鲁棒自适应控制器设计的主要方法之一,它主要是靠递推来完成,方法简单,但存在过参数化问题.在反步设计法的基础上,通过引入调节函数,选取合适的虚拟控制律,设计一种鲁棒自适应控制器.然后,利用Lyapunov稳定性理论证明了该设计不仅能够克服过参数化的问题,而且能够保证所设计的系统具有鲁棒自适应稳定性.仿真实例证明了该方法的有效性.     

一类非线性系统的变结构控制策略

对一类不确定非线性系统提出了一种变结构控制平滑方法，推导出变结构控制系统的稳态误差指标与饱和特性宽度之间定量的数学关系，通过系统的稳态误差指标可以设计出宽度变化的饱和特性，从而既减小了系统的抖振又满足了对系统稳态误差指标的要求。仿真结果验证了该方法的有效性。     

一类不确定性时滞关联大系统的分散鲁棒稳定控制器设计

对一类满足匹配条件的不确定性关联大系统,设计了基于一组线性矩阵不等式（LMI）有解的系统状态反馈镇定的充分条件。本文采用了实对称矩阵集合的最小上界定理,并对设计参数进行优化处理,从而使得所设计的控制器具有较小反馈增益。同时系统的不确定性采用区间矩阵表示,因此该设计方法具有很好的普遍性。最后给出的仿真实例说明了该方法的有效性。     

An Adaptive Control Using Fuzzy Basis Function Expansions for a Class of Nonlinear Systems

An adaptive control using fuzzy basis function expansions is proposed for a class of nonlinear systems in this paper. It is shown that two system uncertainty bounds are approximated in a compact set by using fuzzy basis function expansion networks in the Lyapunov sense, and the outputs of the fuzzy networks are then used as the parameters of the controller to adaptively compensate for the effects of system uncertainties. Using this scheme, not only strong robustness with respect to unknown system dynamics and nonlinearities can be obtained, but also the output tracking error between the plant output and the desired reference output can be guaranteed to asymptotically converge to zero. Simulation results are provided to demonstrate the effectiveness, simplicity and practicality of the proposed control scheme.