Task Scheduling for Control Oriented Requirements for Cyber-Physical Systems

Zhang, Fumin; Szwaykowska, Klementyna; Wolf, Wayne; Mooney, Vincent J.

doi:10.1109/rtss.2008.52

Cited by 105 publications

(61 citation statements)

References 17 publications

(19 reference statements)

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“…With respect to controller design, the literature does offer quite a few works that perform offline timing and control analysis together (e.g., [4,5,6,7,25]). However, as the name suggests, offline methods lead to overly conservative designs, and they are unsuitable to be employed in real-time as well as in conjunction with the MPC design [13,19].These are usually performed using computer simulations for all time stamps based on the employed scheduling algorithm.…”

Section: Review Of Literaturementioning

confidence: 99%

Online message delay prediction for model predictive control over controller area network

Rao

Zeng

2017

2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

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Today's Cyber-Physical Systems (CPS) are typically distributed over several computing nodes communicating by way of shared buses such as Controller Area Network (CAN). Their control performance gets degraded due to variable delays (jitters) incurred by messages on the shared CAN bus due to contention and network overhead. This work presents a novel online delay prediction approach that predicts the message delay at runtime based on real-time traffic information on CAN. It leverages the proposed method to improve control quality, by compensating for the message delay using the Model Predictive Control (MPC) algorithm in designing the controller. By simulating an automotive Cruise Control system and a DC Motor plant in a CAN environment, it goes on to demonstrate that the delay prediction is accurate, and that the MPC design which takes the message delay into consideration, performs considerably better. It also implements the proposed method on an 8-bit 16MHz work goes on to demonstrate that the delay prediction is accurate, and that the MPC design which takes the message delay into consideration, performs considerably better. It also implements the proposed approach on a low end microcontroller (8bit, 16MHz ATmega328P) and measures the time taken for predicting the delay for each message (execution overhead).The obtained results clearly indicate that the method is computationally feasible for use in a real-time scenario.To my parents, my sister, and my grandparents for the unconditional love and support.iv I would like to extend my special thanks to Dr. Anton Cervin (Lund University) for clarifying queries about TrueTime and Dr. Liuping Wang (RMIT University) for the discussions on MPC which proved invaluable in my research.

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Section: Review Of Literaturementioning

confidence: 99%

Online message delay prediction for model predictive control over controller area network

Rao

Zeng

2017

2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

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“…To that extent, it is suggested to enhance computing architecture abstractions so as to include time [Lee 2006;. With the exception of control-oriented studies [Zhang et al 2008], CPS scheduling work does not take the physical interactions and sensed information into account. Another active topic of research is the modeling and specification of CPS.…”

Section: Related Workmentioning

confidence: 99%

A Unified Methodology for Scheduling in Distributed Cyber-Physical Systems

Tang

Gupta

Varsamopoulos

2012

ACM Trans. Embed. Comput. Syst.

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A Distributed Cyber-Physical System (DCPS) may receive and induce energy-based interference from and to its environment. This paper presents a model and an associated methodology that can be used to: i) schedule tasks in DCPSs to ensure that the thermal effects of the task execution are within acceptable levels; and ii) verify that a given schedule meets the constraints. The model uses coarse discretization of space and linearity of interference. The methodology involves characterizing the interference of the task execution and fitting it into the model, then using the fitted model to verify a solution or explore the solution space.

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“…In typical approaches [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], the control tasks are all designed together in a way that some global cost (function of the control cost of the individual tasks) is minimized.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Design of Real-Time Servers for Control Applications

Aminifar

Bini

Eles

et al. 2016

IEEE Trans. Comput.

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Abstract-Today, a considerable portion of embedded systems, e.g., automotive and avionic, comprise several control applications. Guaranteeing the stability of these control applications in embedded systems, or cyber-physical systems, is perhaps the most fundamental requirement while implementing such applications. This is different from the classical hard real-time systems where often the acceptance criterion is meeting the deadline. In other words, in the case of control applications, guaranteeing stability is considered to be a main design goal, which is linked to the amount of delay and jitter a control application can tolerate before instability. This advocates the need for new design and analysis techniques for embedded real-time systems running control applications. In this paper, the analysis and design of such systems considering a server-based resource reservation mechanism are addressed. The benefits of employing servers are manifold: providing a compositional and scalable framework, protection against other tasks' misbehaviors, and systematic bandwidth assignment and co-design. We propose a methodology for designing bandwidth-optimal servers to stabilize control tasks. The pessimism involved in the proposed methodology is both discussed theoretically and evaluated experimentally.

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Task Scheduling for Control Oriented Requirements for Cyber-Physical Systems

Cited by 105 publications

References 17 publications

Online message delay prediction for model predictive control over controller area network

Online message delay prediction for model predictive control over controller area network

A Unified Methodology for Scheduling in Distributed Cyber-Physical Systems

Analysis and Design of Real-Time Servers for Control Applications

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