Designing real-time embedded controllers using the anytime computing paradigm

In this paper we present a methodology for designing embedded controllers with a variable accuracy. The adopted paradigm is the so called any-time control, which derives from the computing paradigm known as “imprecise computation”. The most relevant contributions of the paper are a procedure for designing an incremental control law, whose different pieces cater for increasingly aggressive control requirements, and a modelling technique for the execution platform that allows us to design provably correct switching policies for the controllers. The methodology is validated by both simulations and experimental results.

[1]  X.S. Hu,et al.  Firm real-time system scheduling based on a novel QoS constraint , 2003, RTSS 2003. 24th IEEE Real-Time Systems Symposium, 2003.

[2]  Paulo Tabuada,et al.  Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks , 2007, IEEE Transactions on Automatic Control.

[3]  Alberto L. Sangiovanni-Vincentelli,et al.  Maximizing the stability radius of a set of systems under real-time scheduling constraints , 2005, IEEE Transactions on Automatic Control.

[4]  Karl-Erik Årzén,et al.  Feedback–Feedforward Scheduling of Control Tasks , 2002, Real-Time Systems.

[5]  G. Nicolao,et al.  On almost sure stability of discrete-time Markov jump linear systems , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[6]  Gene F. Franklin,et al.  Digital control of dynamic systems , 1980 .

[7]  Chung Laung Liu,et al.  Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment , 1989, JACM.

[8]  Antonio Bicchi,et al.  Almost sure stability of anytime controllers via stochastic scheduling , 2007, 2007 46th IEEE Conference on Decision and Control.

[9]  A. Morse,et al.  Basic problems in stability and design of switched systems , 1999 .

[10]  Giorgio C. Buttazzo,et al.  Quality-of-Control Management in Overloaded Real-Time Systems , 2007, IEEE Transactions on Computers.

[11]  Antonio Bicchi,et al.  Anytime Control Algorithms for Embedded Real-Time Systems , 2008, HSCC.

[12]  Riccardo Bettati,et al.  Imprecise computations , 1994, Proc. IEEE.

[13]  Qiang Ling,et al.  Scheduling tasks with Markov-chain based constraints , 2005, 17th Euromicro Conference on Real-Time Systems (ECRTS'05).

[14]  Michael D. Lemmon,et al.  Robust performance of soft real-time networked control systems with data dropouts , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[15]  Ben M. Chen.  Robust and H[∞] control , 2000 .

[16]  Parameswaran Ramanathan,et al.  Overload Management in Real-Time Control Applications Using (m, k)-Firm Guarantee , 1999, IEEE Trans. Parallel Distributed Syst..

[17]  Qiang Ling,et al.  Soft real-time scheduling of networked control systems with dropouts governed by a Markov chain , 2003, Proceedings of the 2003 American Control Conference, 2003..

[18]  Alan Burns,et al.  Weakly Hard Real-Time Systems , 2001, IEEE Trans. Computers.

[19]  Daniel Liberzon,et al.  Switching in Systems and Control , 2003, Systems & Control: Foundations & Applications.

[20]  Wei-Kuan Shih,et al.  Algorithms for scheduling imprecise computations , 1991, Computer.

[21]  K.-E. Arzen,et al.  How does control timing affect performance? Analysis and simulation of timing using Jitterbug and TrueTime , 2003, IEEE Control Systems.

[22]  K. Loparo,et al.  Almost sure and δmoment stability of jump linear systems , 1994 .

[23]  Thomas A. Henzinger,et al.  Embedded Control Systems Development with Giotto , 2001 .

[24]  Giorgio Buttazzo,et al.  Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications , 1997 .

[25]  BurnsAlan,et al.  Weakly Hard Real-Time Systems , 2001 .

[26]  Raja Sengupta,et al.  A bounded real lemma for jump systems , 2003, IEEE Trans. Autom. Control..