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Distributed Processes (distributed + process)
Selected AbstractsOperative Platform Applied to Building AutomationCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 1 2009Joćo Figueiredo This structure is composed by three interrelated levels: the Operational level,where the field equipment is controlled, the Inter-Active level,where inhabitants communicate the building their preferences regarding control variables (lights, temperature, etc.), and the higher-level control, the Overall Building Well-Being Model, which manages the global building, taking into account the optimization of the inhabitants preferences, constrained by the available resources. At this third level, the inter-building communication is available. Each building has the capability to communicate with its neighbors, informing about fires, floods, security problems, power consumption expectations, and so on. This article implements one of the three above-referred interrelated control levels: the Operational-level control. This operative platform is structured over a cascade hierarchical control architecture where inner loops are performed by local PLCs (Programmable Logic Controllers), and the outer loop is managed by a centralized SCADA system (Supervisory Control and Data Acquisition) that interacts with the entire PLC network. The lower-level control loop assures high processing velocity tasks, the upper-level control loop updates the local references, knowing the complete system state. This operative model is tested on two prototypes, where all instrumentation in place is controlled by the industrial PLC network. Both prototypes worked perfectly showing the huge potential of communication systems between distributed processes. These communication systems allow intelligent centralized algorithms to manage decision-making problems in real-time environments. The system presented in this article combines several technologies (local PLCs, SCADA systems, and network communications) to reach the goal of efficient management of intelligent buildings. [source] Robust diagnosis and fault-tolerant control of distributed processes over communication networksINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 8 2009Sathyendra Ghantasala Abstract This paper develops a robust fault detection and isolation (FDI) and fault-tolerant control (FTC) structure for distributed processes modeled by nonlinear parabolic partial differential equations (PDEs) with control constraints, time-varying uncertain variables, and a finite number of sensors that transmit their data over a communication network. The network imposes limitations on the accuracy of the output measurements used for diagnosis and control purposes that need to be accounted for in the design methodology. To facilitate the controller synthesis and fault diagnosis tasks, a finite-dimensional system that captures the dominant dynamic modes of the PDE is initially derived and transformed into a form where each dominant mode is excited directly by only one actuator. A robustly stabilizing bounded output feedback controller is then designed for each dominant mode by combining a bounded Lyapunov-based robust state feedback controller with a state estimation scheme that relies on the available output measurements to provide estimates of the dominant modes. The controller synthesis procedure facilitates the derivation of: (1) an explicit characterization of the fault-free behavior of each mode in terms of a time-varying bound on the dissipation rate of the corresponding Lyapunov function, which accounts for the uncertainty and network-induced measurement errors and (2) an explicit characterization of the robust stability region where constraint satisfaction and robustness with respect to uncertainty and measurement errors are guaranteed. Using the fault-free Lyapunov dissipation bounds as thresholds for FDI, the detection and isolation of faults in a given actuator are accomplished by monitoring the evolution of the dominant modes within the stability region and declaring a fault when the threshold is breached. The effects of network-induced measurement errors are mitigated by confining the FDI region to an appropriate subset of the stability region and enlarging the FDI residual thresholds appropriately. It is shown that these safeguards can be tightened or relaxed by proper selection of the sensor spatial configuration. Finally, the implementation of the networked FDI,FTC architecture on the infinite-dimensional system is discussed and the proposed methodology is demonstrated using a diffusion,reaction process example. Copyright © 2008 John Wiley & Sons, Ltd. [source] Time-steppers and ,coarse' control of distributed microscopic processesINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 2 2004Antonios Armaou Abstract We present an equation-free multiscale computational framework for the design of ,coarse' controllers for complex spatially distributed processes described by microscopic/mesoscopic evolution rules. We illustrate this framework by designing discrete-time, coarse linear controllers for a Lattice,Boltzmann (LB) scheme modelling a reaction,diffusion process (a kinetic-theory based realization of the FitzHugh,Nagumo equation dynamics in one spatial dimension). Short ,bursts' of appropriately initialized simulation of the LB model are used to extract the stationary states (stable and unstable) and to estimate the information required to design the coarse controller (e.g. the action of the coarse slow Jacobian of the process). Copyright © 2004 John Wiley & Sons, Ltd. [source] Feedback control of dissipative PDE systems using adaptive model reductionAICHE JOURNAL, Issue 4 2009Amit Varshney Abstract The problem of feedback control of spatially distributed processes described by highly dissipative partial differential equations (PDEs) is considered. Typically, this problem is addressed through model reduction, where finite dimensional approximations to the original infinite dimensional PDE system are derived and used for controller design. The key step in this approach is the computation of basis functions that are subsequently utilized to obtain finite dimensional ordinary differential equation (ODE) models using the method of weighted residuals. A common approach to this task is the Karhunen-Ločve expansion combined with the method of snapshots. To circumvent the issue of a priori availability of a sufficiently large ensemble of PDE solution data, the focus is on the recursive computation of eigenfunctions as additional data from the process becomes available. Initially, an ensemble of eigenfunctions is constructed based on a relatively small number of snapshots, and the covariance matrix is computed. The dominant eigenspace of this matrix is then utilized to compute the empirical eigenfunctions required for model reduction. This dominant eigenspace is recomputed with the addition of each snapshot with possible increase or decrease in its dimensionality; due to its small dimensionality the computational burden is relatively small. The proposed approach is applied to representative examples of dissipative PDEs, with both linear and nonlinear spatial differential operators, to demonstrate its effectiveness of the proposed methodology. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source] Robust detection and accommodation of incipient component and actuator faults in nonlinear distributed processesAICHE JOURNAL, Issue 10 2008Antonios Armaou Abstract A class of nonlinear distributed processes with component and actuator faults is presented. An adaptive detection observer with a time varying threshold is proposed that provides additional robustness with respect to false declarations of faults and minimizes the fault detection time. Additionally, an adaptive diagnostic observer is proposed that is subsequently utilized in an automated control reconfiguration scheme that accommodates the component and actuator faults. An integrated optimal actuator location and fault accommodation scheme is provided in which the actuator locations are chosen in order to provide additional robustness with respect to actuator and component faults. Simulation studies of the Kuramoto-Sivashinsky nonlinear partial differential equation are included to demonstrate the proposed fault detection and accommodation scheme. © 2008 American Institute of Chemical Engineers AIChE J, 2008 [source] Lessons learned by participants of distributed software developmentKNOWLEDGE AND PROCESS MANAGEMENT: THE JOURNAL OF CORPORATE TRANSFORMATION, Issue 2 2005Seija Komi-Sirviö The maturation of the technical infrastructure has enabled the emergence and growth of distributed software development. This has created tempting opportunities for companies to distribute their software development, for example, to economically favourable countries so as to gain needed expertise or to get closer to customers. Nonetheless, such distribution potentially creates problems that need to be understood and addressed in order to make possible the gains offered. To clarify and understand the most difficult problems and their nature, a survey of individuals engaged in distributed software development was conducted. The purpose of this survey was to gather and share lessons learned in order to better understand the nature of the software development process when operating in a distributed software development environment and the problems that may be associated with such distributed processes. Through a clear appreciation of the risks associated with distributed development it becomes possible to develop approaches for the mitigation of these risks. This paper presents the results of the survey, focusing on the most serious problems raised by the respondents. Some practical guidelines that have been developed by industry to overcome these problems are also briefly summarized. Copyright © 2005 John Wiley & Sons, Ltd. [source] | ||||||||||