Control-quality driven design of cyber-physical systems with robustness guarantees

Many cyber-physical systems comprise several control applications sharing communication and computation resources. The design of such systems requires special attention due to the complex timing behavior that can lead to poor control quality or even instability. The two main requirements of control applications are: (1) robustness and, in particular, stability and (2) high control quality. Although it is essential to guarantee stability and provide a certain degree of robustness even in the worst-case scenario, a design procedure which merely takes the worst-case scenario into consideration can lead to a poor expected (average-case) control quality, since the design is solely tuned to a scenario that occurs very rarely. On the other hand, considering only the expected quality of control does not necessarily provide robustness and stability in the worst-case. Therefore, both the robustness and the expected control quality should be taken into account in the design process. This paper presents an efficient and integrated approach for designing high-quality cyber-physical systems with robustness guarantees.

[1]  Martin Sanfridson,et al.  Integration of off-line scheduling and optimal control , 2000, Proceedings 12th Euromicro Conference on Real-Time Systems. Euromicro RTS 2000.

[2]  João P. Hespanha,et al.  Position Paper : Distributed Control Systems With Shared Communication and Computation Resources , 2008 .

[3]  Anton Cervin,et al.  Stability and worst-case performance analysis of sampled-data control systems with input and output jitter , 2012, 2012 American Control Conference (ACC).

[4]  J.C. Palencia Gutierrez,et al.  On the schedulability analysis for distributed hard real-time systems , 1997, Proceedings Ninth Euromicro Workshop on Real Time Systems.

[5]  Rolf Ernst,et al.  System level performance analysis - the SymTA/S approach , 2005 .

[6]  Petru Eles,et al.  Designing High-Quality Embedded Control Systems with Guaranteed Stability , 2012, 2012 IEEE 33rd Real-Time Systems Symposium.

[7]  Fumin Zhang,et al.  Task Scheduling for Control Oriented Requirements for Cyber-Physical Systems , 2008, 2008 Real-Time Systems Symposium.

[8]  Anton Cervin,et al.  JITTERBUG: a tool for analysis of real-time control performance , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[9]  Martin Lukasiewycz,et al.  Time-triggered implementations of mixed-criticality automotive software , 2012, 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[10]  Petru Eles,et al.  Integrated scheduling and synthesis of control applications on distributed embedded systems , 2009, 2009 Design, Automation & Test in Europe Conference & Exhibition.

[11]  Joao P. Hespanha,et al.  Analysis of distributed control systems with shared communication and computation resources , 2009, 2009 American Control Conference.

[12]  Lothar Thiele,et al.  A hybrid approach to cyber-physical systems verification , 2012, DAC Design Automation Conference 2012.

[13]  Rupak Majumdar,et al.  Performance-aware scheduler synthesis for control systems , 2011, 2011 Proceedings of the Ninth ACM International Conference on Embedded Software (EMSOFT).

[14]  Michael González Harbour,et al.  Schedulability analysis for tasks with static and dynamic offsets , 1998, Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279).

[15]  Astrom.  Computer Controlled Systems , 1990 .

[16]  Alan Burns,et al.  Controller Area Network (CAN) schedulability analysis: Refuted, revisited and revised , 2007, Real-Time Systems.

[17]  Lui Sha,et al.  On task schedulability in real-time control systems , 1996, 17th IEEE Real-Time Systems Symposium.

[18]  Anton Cervin,et al.  Delay-Aware Period Assignment in Control Systems , 2008, 2008 Real-Time Systems Symposium.

[19]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[20]  K.-E. Arzen,et al.  An introduction to control and scheduling co-design , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[21]  Robert Hooke,et al.  `` Direct Search'' Solution of Numerical and Statistical Problems , 1961, JACM.

[22]  J. Nilsson,et al.  Timing problems in real-time control systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[23]  John A. Clark,et al.  Holistic schedulability analysis for distributed hard real-time systems , 1994, Microprocess. Microprogramming.

[24]  Karl-Erik Årzén,et al.  The Jitter Margin and Its Application in the Design of Real-Time Control Systems , 2004 .

[25]  J. Javier Gutiérrez,et al.  Best-case analysis for improving the worst-case schedulability test for distributed hard real-time systems , 1998, Proceeding. 10th EUROMICRO Workshop on Real-Time Systems (Cat. No.98EX168).