Design Optimization and Synthesis of FlexRay Parameters for Embedded Control Applications

Samii, Soheil; Eles, Petru; Peng, Zebo; Cervin, Anton

doi:10.1109/delta.2011.22

Cited by 9 publications

(6 citation statements)

References 16 publications

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“…The actual important parameter related to control performance is the sampling-actuator delay distribution of the system. Thus, although we are considering staticcyclic scheduling in the examples, the conclusions of this section are also valid for priority-based scheduling and other communication protocols, which are supported by our design tool [16], [18].…”

Section: Motivational Examplementioning

confidence: 92%

Control-Quality Driven Task Mapping for Distributed Embedded Control Systems

Aminifar

Samii

Eles

et al. 2011

2011 IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications

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Abstract-Many embedded control systems are implemented on execution platforms with several computation nodes and communication components. Distributed embedded control systems typically comprise multiple control loops that share the available computation and communication resources of the platform. It is well known that such resource sharing leads to complex delay characteristics that degrade the control quality if not properly taken into account at design time. Scheduling in computation nodes and communication infrastructure, as well as execution periods of the controllers impact the delay characteristics and, consequently, the control quality. In addition, mapping of tasks on computation nodes affect both scheduling of tasks and messages, and the assignment of periods of the control applications. Therefore, control synthesis must be considered during mapping, scheduling, and period assignment in order to achieve high control quality. This paper presents a control-quality optimization approach for integrated mapping, scheduling, period selection, and control synthesis for distributed embedded control systems.

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Section: Motivational Examplementioning

confidence: 92%

Control-Quality Driven Task Mapping for Distributed Embedded Control Systems

Aminifar

Samii

Eles

et al. 2011

2011 IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications

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“…Next, a part of C l is designed exploiting/utilizing the information on the already designed part of Φ l and so on. In recent literature [18,16,19,17], it is shown that such an interactive design approach opens up scope for significant design optimization. We illustrate this joint design approach with an example in Section 4.…”

Section: Design Questionsmentioning

confidence: 99%

“…(Stability condition) Consider the closedloop system (16) with control input (17) and assume that A1 is Schur stable.…”

Section: Stability-based Requirementsmentioning

confidence: 99%

Model-based development and verification of control software for electric vehicles

Goswami¹,

Lukasiewycz²,

Kauer³

et al. 2013

Proceedings of the 50th Annual Design Automation Conference

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Most innovations in the automotive domain are realized by electronics and software. Modern cars have up to 100 Electronic Control Units (ECUs) that implement a variety of control applications in a distributed fashion. The tasks are mapped onto different ECUs, communicating via a heterogeneous network, comprising communication buses like CAN, FlexRay, and Ethernet. For electric vehicles, software functions play an essential role, replacing hydraulic and mechanic control systems. While model-based software development and verification are already used extensively in the automotive domain, their importance significantly increases in electric vehicles as safety-critical functions might no longer rely on mechanical (fall-back) solutions. The need for reducing costs, size, and weight in electric vehicles has also resulted in a considerable interest in topics such as the consolidation of ECUs as well as efficient implementation of control software. In this paper we discuss two broad issues related to model-based software development and verification in electric vehicles. The first is concerned with how to ensure that model-level semantics are preserved in an implementation, which has important implications on the verification and certification of control software. The second issue is related to techniques for reducing the computational and communication demands of distributed automotive control algorithms. For both these topics we provide a broad introduction to the problem followed by a discussion on state-ofthe-art techniques.

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“…Correspondingly, the control gains and the associated QoC values are computed. Later, Samii et al [107] extend their work with speciic characterization of the FlexRay parameters. In the same vein, Aminifar et al [108] have extended the approach developed for single-processor architecture [100], as mentioned in Section V-A1, with added complexity due to schedule computation for the communication bus (CAN bus).…”

Section: A Existing Cosynthesis Approachesmentioning

confidence: 99%