On the Stability of Spatially Distributed Systems

In this note, a sufficient condition is derived for the stability of a spatially invariant distributed dynamical system, based on the geometrical structure of the null space of a matrix polynomial. This condition is less conservative than the available computationally feasible criteria. Moreover, using the idea of parameter dependent linear matrix inequalities, a necessary and sufficient condition is obtained. Both of these two conditions are expressed by LMIs. While the necessity of the latter is lost if the degree of the related matrix polynomials is small, its conservativeness can be sequentially reduced.      

On Mathematical Modeling of the Dynamics of Multilink Systems and Exoskeletons

Journal of Computer and Systems Sciences International - A review of well-known publications is given and some results of the authors’ research on modeling the dynamics of systems of rigid...     

完全和部分可观察离散事件系统状态反馈控制间的关系

讨论完全和部分可观察离散事件系统状态反馈控制间的关系,首先讨论了控制方案集及最大控制方案在两个系统这间的关系,由此通过重新定义可观察谓词,较为简单地证明了谓词Ｐ可综合的充要条件是它既可控又可观察。其次,我们在一定条件下将部分可观察ＤＥＳ转化为一个完全可观察ＤＥＳ,并探讨了两者之间的关系。     

An Approach to Mathematical Modeling of Ill-Posed Problems of Dynamics of Distributed-Parameter Systems

A technique for mathematical modeling of a state of a distributed-parameter dynamic system with incomplete data about their initial boundary conditions is proposed in the paper. Modeling accuracy and uniqueness conditions are formulated. An algorithm is proposed for recalculation of modeling results for different numbers of discrete observations of the initial boundary state of the system with point modeling effects.     

Distributed Measuring-Calculating Methods of Modeling Flows in Pipeline Systems

For modeling and identifying the distribution of homogeneous and heterogeneous flows in pipeline systems, measuring-calculating methods based on indirect measurements of the boundary conditions were proposed. They evaluate the directly non-measurable flow parameters. Homogeneous flows of the oil-field water from the group pumping stations to the injection wells and the gas-lift gas from the compressor stations to the oil-producing wells, as well as the heterogeneous flows of the water-oil and gas mix in multiple-pipeline systems from the producing wells to the automatic group measurement installations were discussed as particular applications.     

Multibody Dynamics Modeling of Variable Length Cable Systems

This paper presents a procedure for studying the dynamics ofvariable length cable systems. Such systems commonly occur in deploymentand retrieval (pay-out and reel-in) in cable towing systems such as inship and marine applications.The cable is modeled as a chainand treated as a multibody system. The chain links in turn are modeledas lumped masses. The pay-out/reel-in process is modeled with variablelength links near the towing point.Application in marine systems are presented and discussed.     

Approximation Modeling for the Online Performance Management of Distributed Computing Systems

A promising method of automating management tasks in computing systems is to formulate them as control or optimization problems in terms of performance metrics. For an online optimization scheme to be of practical value in a distributed setting, however, it must successfully tackle the curses of dimensionality and modeling. This paper develops a hierarchical control framework to solve performance management problems in distributed computing systems operating in a data center. Concepts from approximation theory are used to reduce the computational burden of controlling such large-scale systems. The relevant approximations are made in the construction of the dynamical models to predict system behavior and in the solution of the associated control equations. Using a dynamic resource-provisioning problem as a case study, we show that a computing system managed by the proposed control framework with approximation models realizes profit gains that are, in the best case, within 1% of a controller using an explicit model of the system.      

多Agent系统分布式问题求解的代数模型方法(Ⅱ): 群体智能和社会动力学

该文是组合论文中第二篇，讨论多Agent系统分布式问题求解的代数模型中的特性层和动力学层，即没粒度Agent群体的宏观群体智能的形式优化代数模型以及宏观社会智能与Agent个体间微观社会行为之间的社会动力学模型，提出了基于这种新的代数模型方法的超分布超并行社会智能问题求解算法，关于分布式多任务自组织规划和资源自组织分配的仿真实验以及与其它方法的比较分析，表明了该文提出了代数模型和问题求解方法的特点和有效性。     

分布式软件系统交互行为建模、验证与测试

为了确保分析与设计阶段分布式软件系统中模块之间交互行为的正确性,提出了一种分布式软件系统模块交互的抽象方法,分别通过系统状态机图和对象状态机图对各模块状态变迁进行建模,使用UML2.0序列图对模块之间交互行为进行描述.采用基于命题投影时序逻辑的模型检测技术,将对象状态机图转换为Promela模型,系统交互性质转换为命题投影时序逻辑公式,通过模型检测器验证交互模型是否满足于系统的性质,若不满足于该性质,则能够获得反例执行的路径.给出了一个分布式软件系统测试框架,在验证后的序列图模型基础上,使用基于模型的测试用例自动生成方法得到测试用例集合,该集合能够实现对交互行为的有效测试.实例结果表明,该方法可以提高分布式软件系统中模块交互行为的有效性和可靠性.     

分布式卫星系统仿真支撑框架设计

分布式卫星系统是卫星技术发展的一个重要方向,但分布式卫星系统的复杂性也给传统的仿真技术提出了挑战.为降低仿真开发的难度,为分布式卫星系统仿真从模捌建立、仿真定义到仿真运行设计了支撑软件框架.基于支持实时分布式条件下通信的数据分发服务实现.并定义了进程间和进程内两层仿真支撑框架,使得可以根据仿真成员的特性灵活布置仿真成员.提高分布式仿真的计算效率.分布式卫星系统仿真支撑框架提高了仿真开发的灵活性和效率,并能满足分布式卫星系统仿真在仿真成员互操作性和可重用性方面的需求.     

Distributed Containment Control of Multi-agent Systems with General Linear Dynamics and Time-delays

Containment control problems for high-order linear time-invariant multi-agent systems with fixed communication time-delays are investigated. Based on Lyapunov-Krasovskii functional method and the linear matrix inequality (LMI) method, sufcient conditions on the communication digraph, the feedback gains, and the allowed upper bound of the delays to ensure containment control of the multi-agent systems under the different containment control algorithms are given. Finally, numerical simulations are presented to demonstrate theoretical results.     

Mathematical Models and Problems of Fractional-Differential Dynamics of Some Relaxation Filtration Processes

The author constructs fractional-differential mathematical models to describe the dynamics of geofiltration processes under pressure relaxation. The models are based on the concepts of the generalized Caputo and Hilfer derivatives, as fractional-order derivatives of a function with respect to another function. Within the framework of these models, analytical solutions of some filtration boundary-value problems, including the problem with nonlocal boundary conditions, are obtained.     

The Role of Modeling and Asynchronous Distributed Simulation in Analyzing Complex Systems of the Future

The word simulate implies to imitate or to mimic while the word modeling refers to a small object, usually built to scale, that represents some existing object. Although the art of mimicking and modeling may be traced back to the beginning of civilization, with the emergence of computers, a few decades ago, the art of modeling and simulation experienced a remarkable transformation. The computational intelligence of the computer imparted the ability to encapsulate and simulate specific characteristics of not only living and inanimate objects but abstract concepts. While the human brain is equally capable of simulating abstract concepts, the precision and speed of the computers are unparalleled and they impart computer modeling and simulation a qualitative jump in its capability and fidelity. Also, while intimately connected to each other, modeling refers to the notion of representing the desired behavior of the target object or idea in the host computer and simulation refers to the execution of the model on a host computer. Today, towards the end of the twentieth century, the nature of modeling and simulation is undergoing another radical transformation. The emergence of economical and powerful computers coupled with the ability to network a large number of computers, promises the ability to model and simulate complex, real-world systems, that are rapidly becoming commonplace in the society, successfully and with a high degree of fidelity. Already, today's real-world systems including complex banking, credit-card transaction, transportation, ground-based communication, and space-based tele-communication systems defy the analytical modeling that had characterized the efforts over the past three decades. Virtually all analytical studies are severely restricted in the number of variables and the number of interacting units that may be modeled. Tomorrow's systems are expected to be far more complex, implying that modeling and large-scale simulation may be the most logical and, often, the only vehicle to study them objectively. This paper presents a fundamental analysis of the nature of complex physical and natural processes that will increasingly constitute the challenging problems of the future. It then develops a set of principles for modeling complex systems. Finally, it examines the role of asynchronous, distributed simulation in the study of a number of real-world systems. In general, modeling and simulation enables one to detect design errors, prior to developing a prototype, in a cost effective manner, identify potential problems during system operation, detect rare and elusive errors, and investigate hypothetical concepts that do not exist in nature. Upon execution, the simulation provides greater quantitative and qualitative insight into the behavior of the actual system. In addition, an asynchronous, distributed simulation, executing on a loosely-coupled parallel processor, closely resembles the actual, operational system, yielding results that potentially reflect reality, as close as possible. Furthermore, elements of the simulation code that emulate the system behavior may be transferred directly onto the operational system with minimal modifications. The knowledge encapsulated in this paper, has been derived from a number of actual case studies involving the modeling and simulation of a number of real-world problems.     

Some Results of the Theory of Nonsearching Adaptive Systems and Their Application

Some problems of flight vehicle control that date back to the 1950s and gave rise to the theory of adaptive control and, in the 1960s and 1970s, self-adjusting automatic pilots were discussed.     

Mathematical Modeling and Experimental Identification of an Unmanned Helicopter Robot with Flybar Dynamics

This paper presents a mathematical model for a model‐scale unmanned helicopter robot, with emphasis on the dynamics of the flybar. The interaction between the flybar and the main rotor blade is explained in detail; it is shown how the flapping of the flybar increases the stability of the helicopter robot as well as assists in its actuation. The model helicopter has a fast time‐domain response due to its small size, and is inherently unstable. Therefore, most commercially available model helicopters use the flybar to augment stability and make it easier for a pilot to fly. Working from first principles and basic aerodynamics, the equations of motion for full six degree‐of‐freedom with flybar‐degree of freedom are derived. System identification experiments and results are presented to verify the mathematical model structure and to identify model parameters such as inertias and aerodynamic constants. © 2004 Wiley Periodicals, Inc.     

Use of Mathematical Modeling for Estimation of the Toxic Action of Some Medical Agents

A mathematical model of a granulocytic series of blood formation (hemopoiesis) is set out, with the aid of which it is possible to solve effectively the problem involved with the determination of the sensitivity of cells of the bone marrow to the toxic action of cytostatic agents that are widely used in medicine, in particular, for the cure of oncologic diseases. The results of numerical model experiments on a computer make it possible to analyze an unlimited number of versions describing various situations of the lesion of cells of the bone marrow in the framework of the presented model and trace the dynamics of recovery of the hemopoietic system after the injection of agents with a different mechanism of the toxic effect.     

Performance Modeling and Evaluation of Distributed Component-Based Systems Using Queueing Petri Nets

Performance models are used increasingly throughout the phases of the software engineering lifecycle of distributed component-based systems. However, as systems grow in size and complexity, building models that accurately capture the different aspects of their behavior becomes a more and more challenging task. In this paper, we present a novel case study of a realistic distributed component-based system, showing how Queueing Petri Net models can be exploited as a powerful performance prediction tool in the software engineering process. A detailed system model is built in a step-by-step fashion, validated, and then used to evaluate the system performance and scalability. Along with the case study, a practical performance modeling methodology is presented which helps to construct models that accurately reflect the system performance and scalability characteristics. Taking advantage of the modeling power and expressiveness of Queueing Petri Nets, our approach makes it possible to model the system at a higher degree of accuracy, providing a number of important benefits.     

Modeling and Tracking of Transaction Flow Dynamics for Fault Detection in Complex Systems

With the prevalence of Internet services and the increase of their complexity, there is a growing need to improve their operational reliability and availability. While a large amount of monitoring data can be collected from systems for fault analysis, it is hard to correlate this data effectively across distributed systems and observation time. In this paper, we analyze the mass characteristics of user requests and propose a novel approach to model and track transaction flow dynamics for fault detection in complex information systems. We measure the flow intensity at multiple checkpoints inside the system and apply system identification methods to model transaction flow dynamics between these measurements. With the learned analytical models, a model-based fault detection and isolation method is applied to track the flow dynamics in real time for fault detection. We also propose an algorithm to automatically search and validate the dynamic relationship between randomly selected monitoring points. Our algorithm enables systems to have self-cognition capability for system management. Our approach is tested in a real system with a list of injected faults. Experimental results demonstrate the effectiveness of our approach and algorithms