Topic
Control reconfiguration
About: Control reconfiguration is a research topic. Over the lifetime, 22423 publications have been published within this topic receiving 334217 citations.
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TL;DR: In this paper, a mixed-integer nonlinear programming model is proposed to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment, where the objective is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs, such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads
Abstract: This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment. The proposed model, to the best of the author’s knowledge, is the most comprehensive model to date with more integrated approach to the DCMSs. The proposed DCMS model integrates concurrently the important manufacturing attributes in existing models in a single model such as machine breakdown effect in terms of machine repair cost effect and production time loss cost effect to incorporate reliability modeling; production planning in terms of part inventory holding, part internal production cost, and part outsourcing; process batch size; transfer batch size for intracell travel; transfer batch size for intercell travel; lot splitting; alternative process plan, and routing and sequence of operation; multiple copies of identical copies; machine capacity, cutting tooling requirements, work load balancing, and machine in different cells constraint; machine in same cell constraint; and machine procurements and multiple period dynamic cell reconfiguration. Further, the objective of the proposed model is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads, etc. ,in an integrated manner. Nonlinear terms of objective functions are transformed into linear terms to make mixed-integer linear programming model. The proposed model has been demonstrated with several problems, and results have been presented accordingly.
84 citations
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02 Mar 2006TL;DR: In this paper, a real-time and on-demand reconfiguration of silicon area personalized on suitable granularities demonstrates high situation adaptivity and perspectives for next generation microelectronics.
Abstract: Short time-to-market pressure, high cost and risks and power consumption are keywords in development of microelectronic solutions for embedded systems as well as for universal and application tailored processor architectures. Modularity and flexibility while design-time, e.g. for system-on-chip (SoC) component design, is not sufficient if the possibility of run-time reconfiguration of novel architectures has to be considered. Here, exploitation of real-time and on-demand reconfiguration of silicon area personalized on suitable granularities demonstrates high situation adaptivity and perspectives for next generation microelectronics. This paper discusses our implemented, synthesized and tested on-demand and partial reconfiguration approaches for fine-grain (Xilinx Virtex FPGAs) data paths. This includes also very new dynamic and partial reconfiguration for 2D placement and routing adaptation for today's fine-grain Xilinx FPGAs.
84 citations
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TL;DR: This paper starts with a description of how the global behavior of this discrete-event system is modeled by using communicating finite state machines and explains how this model is used for analyzing the stream of alarms and diagnosing the network.
Abstract: Detection and isolation of failures in large and complex systems such as telecommunication networks are crucial and challenging tasks. The problem considered here is that of diagnosing the largest French packet switching network. The challenge is to be as efficient as the existing expert system while providing greater generality and flexibility with respect to technological and reconfiguration changes in the network. The network is made up of interconnected components each of which can send, receive and transmit messages via its ports. The problem we are faced with is to follow the evolution of the network on the basis of the stream of time-stamped alarms which arrive at the supervision center. We have decided to use model-based techniques which are recognized to be more adapted to evolutive systems than expertise-based approaches are. This paper starts with a description of how we model the global behavior of this discrete-event system by using communicating finite state machines. It goes on to explain how this model is used for analyzing the stream of alarms and diagnosing the network. Our work is based on the diagnoser approach proposed by Sampath et al. (1995). Starting from a model of the network adapted to simulate faults, this approach transforms it into a finite state automaton, called a diagnoser, in order to analyze the stream of alarms. The approach described in Sampath et al. (1995; 1996) proved to be grounded on certain basic hypotheses which were too restrictive for our application. This paper extends Sampath’s proposal to communicating finite state machines. The difficulties we had to cope with are outlined and the way we overcome them is presented. A major difficulty is the huge size of the global model of the system. To solve this problem we take advantage of the hierarchical structure of the network and rely on a generic model of the system for building a generic diagnoser.
84 citations
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TL;DR: This article presents two languages: FPath, a domain-specific language that provides a concise yet powerful notation to navigate inside and query Fractal architectures, and FScript, a scripting language that embeds FPath and supports the definition of complex reconfigurations.
Abstract: Component-based systems must support dynamic reconfigurations to adapt to their execution context, but not at the cost of reliability. Fractal provides intrinsic support for dynamic reconfiguration, but its definition in terms of low-level APIs makes it complex to write reconfigurations and to ensure their reliability. This article presents a language-based approach to solve these issues: direct and focused language support for architecture navigation and reconfiguration make it easier both to write the reconfigurations and to ensure their reliability. Concretely, this article presents two languages: (1) FPath, a domain-specific language that provides a concise yet powerful notation to navigate inside and query Fractal architectures, and (2) FScript, a scripting language that embeds FPath and supports the definition of complex reconfigurations. FScript ensures the reliability of these reconfigurations thanks to sophisticated run-time control, which provides transactional semantics (ACID properties) to the reconfigurations.
84 citations
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TL;DR: In this paper, a hybrid estimation/learning approach is presented for accommodating the remaining unanticipated faults. But, the tradeoff exists between the time to attain a solution to the reconfiguration problem and the generality of the approach.
Abstract: Procedures exist to rapidly accommodate certain types of faults, based on a priori specification of the postfault dynamics. A methodology is presented for accommodating the remaining unanticipated faults. For these two approaches, a tradeoff exists between the time to attain a solution to the reconfiguration problem and the generality of the approach. Unanticipated faults are represented as unmodeled forces and torques. Models of these forces and torques are developed online using a hybrid estimation/learning approach. The hybrid system is designed for fast estimation during the initial transient when a fault occurs, with continually improving performance as postfault information is accumulated by the learning system. Fault accommodation is achieved by a feedforward/feedback control architecture that employs an actuator distribution system to convert desired forces into individual actuator commands. This approach is demonstrated on a simulated autonomous vehicle, where the addition of a hybrid estimation/learning capability is shown to increase performance greatly over time. >
84 citations