419,603 research outputs found

    Algorithmic considerations of integrated design for CSI on a hypercube architecture

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    An approach is presented to the integrated design problem for actively controlled large, flexible mechanical systems for which Control Structure Interaction (CSI) problems are of concern. The two coupled design problems were identified as the optimal Structural Design problem the optimal Controller Design problem. These two problems can be addressed within a decision making loop that would consider each separately, and then sequentially analyze the effects of one on the other. Embedded in such a loop would be the simulation and coordination tasks as part of the decision tools required in a total (software) package. All of the above are compute-intensive tasks. In any such task, possible decompositions and gains due to the inherent parallelism have to be exploited. The problems under consideration, as applied to large flexible mechanical structures, are particularly suited to be mapped onto multicomputer systems in a hypercube topology

    Flexible and dynamic replication control for interdependent distributed real-time embedded systems

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    Replication is a proven concept for increasing the availability of distributed systems. However, actively replicating every software component in distributed embedded systems may not be a feasible approach. Not only the available resources are often limited, but also the imposed overhead could significantly degrade the system’s performance. This paper proposes heuristics to dynamically determine which components to replicate based on their significance to the system as a whole, its consequent number of passive replicas, and where to place those replicas in the network. The activation of passive replicas is coordinated through a fast convergence protocol that reduces the complexity of the needed interactions among nodes until a new collective global service solution is determined

    Design abstraction for autonomous adaptive hardware systems on FPGAs

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    Adaptive hardware is gaining importance with the emergence of more autonomous systems that must process large volumes of sensor data and react within tight deadlines. To support such computation within the constraints of embedded deployments, a blend of high throughput hardware processing and adaptive control is required. FPGAs offer an ideal platform for implementing such systems by virtue of their hardware flexibility and sensor interfacing capabilities. FPGA SoCs are specifically well suited offering capable embedded processors that are tightly coupled with a flexible high performance FPGA fabric. This paper explores existing work on adaptive hardware systems before proposing a general model and implementation approach tailored towards these modern FPGA architectures, concluding with pointers for research in this emerging field

    Integrated structure and control design for mechatronic systems with configuration-dependent dynamics

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    This paper considers the optimal design of mechatronic systems with configuration-dependent dynamics. An optimal mechatronic design requires that, among the structural and control parameters, an optimal choice has to be made with respect to design specifications in the different domains. Two main challenges are treated in this paper: the non-convex nature of the optimization problem and the difficulty in modeling serial machines with flexible components and their embedded controllers. The optimization problem is treated using the direct design strategy which considers simultaneously structural and control parameters as variables and adopts non-convex optimization algorithms. Linear time-invariant and gain-scheduling PID controllers are addressed. This methodology is exploited for the multi-objective optimization of a pick-and-place assembly robot with a gripper carried by a variable-length flexible beam. The resulting design tradeoffs between system accuracy and control efforts demonstrate the advantage of an integrated design approach for mechatronic systems with configuration-dependent dynamics. 2009 Elsevier Ltd. All rights reserved

    Software Evolution Approach for the Development of Command and Control Systems

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    2000 Command and Control Research and Technology Symposium (CCRTS), June 11-13, 2000, Naval Postgraduate School, Monterey, CAThis paper addresses the problem of how to produce reliable software that is also flexible and cost effective for the DoD distributed software domain. DoD software systems fall into two categories: information systems and war fighter systems. Both types of systems can be distributed, heterogeneous and network-based, consisting of a set of components running on different platforms and working together via multiple communication links and protocols. We propose to tackle the problem using prototyping and a “wrapper and glue” technology for interoperability and integration. This paper describes a distributed development environment, CAPS (Computer- Aided Prototyping System), to support rapid prototyping and automatic generation of wrapper and glue software based on designer specifications. The CAPS system uses a fifth-generation prototyping language to model the communication structure, timing constraints, I/O control, and data buffering that comprise the requirements for an embedded software system. The language supports the specification of hard real-time systems with reusable components from domain specific component libraries. CAPS has been used successfully as a research tool in prototyping large war-fighter control systems (e.g. the command-and-control station, cruise missile flight control system, missile defense systems) and demonstrated its capability to support the development of large complex embedded software.This research was supported in part by the U. S. Army Research Office under contract/grant number 35037-MA and 40473-MA

    Design of embedded controller using hybrid systems for integrated building systems

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    The design of controllers for integrated building systems has been traditionally carried out using basic techniques validated frequently by simulation. However, the demands on occupants’ comfort, safety and energy consumption increase speedily as the current controllers used in buildings are not efficient and enough flexible to be adapted to any changes. To investigate such issues, this paper focuses mainly on the design of embedded control systems for integrated building plants. So therefore, the challenges of modeling embedded controller for building heating system are treated at higher-level of abstraction with the help of sophisticated tools and new development techniques. Particularity, this paper concerns the relevance and reliability of integrating distributed control and building performance simulation environments by run-time coupling, over TCP/IP protocol suite. In addition, this paper involves a case-study with an important setup where the simulated results are obtained within the use of run-time coupling approach

    Adaptivity in High-Performance Embedded Systems: a Reactive Control Model for Reliable and Flexible Design

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    International audienceSystem adaptivity is increasingly demanded in high-performance embedded systems, particularly in multimedia System-on-Chip (SoC), due to growing Quality of Service requirements. This paper presents a reactive control model that has been introduced in Gaspard, our framework dedicated to SoC hardware/software co-design. This model aims at expressing adaptivity as well as reconfigurability in systems performing data-intensive computations. It is generic enough to be used for description in the different parts of an embedded system, e.g. specification of how different data-intensive algorithms can be chosen according to some computation modes at the functional level; expression of how hardware components can be selected via the usage of a library of Intellectual Properties (IPs) according to execution performances. The transformation of this model towards synchronous languages is also presented, in order to allow an automatic code generation usable for formal verification, based of techniques such as model checking and controller synthesis as illustrated in the paper. This work, based on Model-Driven Engineering and the standard UML MARTE profile, has been implemented in Gaspard

    Neural Modeling and Control of Diesel Engine with Pollution Constraints

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    The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identification and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are flexible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The presented work extends optimal neuro-control to the multivariable case and shows the flexibility of neural optimisers. Considering the preliminary results, it appears that neural networks can be used as embedded models for engine control, to satisfy the more and more restricting pollutant emission legislation. Particularly, they are able to model nonlinear dynamics and outperform during transients the control schemes based on static mappings.Comment: 15 page
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