Organizers: Vijay Gupta
(University of Notre Dame) and Paulo Tabuada
(UCLA).
Presenters: Antonio Bicchi, Luca
Greco, Luigi Palopoli, Daniele Fontanelli, Manel Velasco, Pau Marti, Fumin Zhang
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Cyberphysical systems (CPS) represent the next generation of engineered systems. Such
systems - also known by terms such as networked and embedded control systems - use computation
and communication embedded in and interacting with physical processes to add capabilities to
physical systems. As such systems become ubiquitous, it will be necessary to evolve a systematic
design theory for them. Such a theory would unify diverse branches of systems theory, including
estimation and control, networks, information theory, distributed processing, and so on.
While the interaction of communication with control has been studied over the last decade or
so, issues that arise at the intersection of control and processor design are less well-understood.
This workshop focuses on the co-design of control and processing algorithms. Traditional design
approach assumes a separation of concerns between the two domains. Control designs have largely
ignored the limitations and possibilities of various software and processor implementations. Due
to the deeply embedded nature of CPS, issues such as scheduling of control tasks, anytime and
event triggered control algorithms, and battery consumption due to control algorithm execution
become extremely important. On the other hand, computational and scheduling models need to be
tailored to and be flexible with respect to the demands of control applications.
This workshop will bring together researchers working towards developing a unified theory that
integrates process control and real-time computing. In particular, topics related to real time control,
event triggered and and anytime control, and battery aware control will be covered.
The duration will be half-day, on the morning of Dec 14, 2010.
The tentative schedule is as follows: (Slides will be posted following the workshop.)
| 9:00am-9:10am | V. Gupta, P. Tabuada Welcome, Overview |
| 9:10am-9:50am | A. Bicchi, L. Greco, “Anytime Control Paradigm for Stochastic Embedded Real-Time Systems” |
| 9:50am-10:30am | L. Palopoli, D. Fontanelli, “Implementation of Anytime Control for Stochastic Embedded Real-Time Systems” |
| 10:30am-11:10am | P. Marti, “Feedback Scheduling: Theory and Practice” |
| 11:10am-11:20am | Break |
| 11:20am-12:00pm | M. Velasco, “Sampling in Event-driven Control Systems” |
| 12:00pm-12:40pm | F. Zhang, “Battery Supported CPS” |
| 12:40pm-1:00pm | Discussion and Wrap Up |
Anytime Control Paradigm for Stochastic Embedded Real-Time Systems: In this talk we
consider the problem of designing controllers for linear plants to be implemented in embedded platforms under stringent real-time constraints. These include preemptive scheduling
schemes, under which the execution time allowed for control tasks is uncertain. In a conservative design approach, only a control algorithm that is executable (in the worst case) within
the minimum time slot guaranteed by the scheduler at each period would be employed. On
the opposite, we consider here a more flexible “Anytime Control” design approach, based
on a hierarchy of controllers for the same plant. Higher controllers in the hierarchy provide
better closed-loop performance, while typically requiring a longer execution time. Stochastic models of the scheduler and of controllers execution times are used to infer probabilities
that controllers of different complexity can be executed at different periods. We propose
a strategy (in the form of a switching policy) for choosing among executable controllers,
maximizing the usage of higher controllers, which affords better exploitation of the computational platform than the conservative design while guaranteeing stability (in a suitable
stochastic sense). Simulation results on the control of two prototypical mechanical systems
show that performance is substantially enhanced by our anytime control technique w.r.t.
worst case-based scheduling.
Implementation of the Anytime Control for Stochastic Embedded Real-Time Systems:In this
talk we present a methodology for designing embedded controllers based on the so–called
“Anytime Control” paradigm. A control law is split into a sequence of subroutine calls,
each one fulfilling a control goal and refining the result produced by the previous one. We
propose a design methodology to define a feedback controller structured in accordance with
this paradigm and with the ensuing stochastic switching policy for closed loop system stability. The cornerstone of this construction is a stochastic model describing the probability
of executing, in each activation of the controller, the different subroutines. We show how
to construct such a stochastic scheduler model for realistic real-time task sets and how to
let the switching policy be robust with respect to uncertainties on the task model. Since the
performance of the closed loop system can be severely impaired by switching between different controllers in the case of reference-tracking tasks, a simple practical bumpless transfer
technique to assist in making smooth transitions between controllers is also presented and
adapted to the Anytime Control paradigm. Finally, experimental validation of the proposed
technique is reported using a mechanical system endowed with an embedded real-time platform.
Feedback Scheduling: Theory and Practice: The most common method to the analysis, design and implementation of networked and embedded control systems consists on assuming the periodic execution of control algorithms. However, for resource-constrained systems, this assumption may be inappropriate because the selection of fixed rates of execution is not an easy task (low rates imply low resource utilization but also imply low control performance, and viceversa) and because the enforcement of a fixed rate may be not suitable in front of changes in the CPU/network load and in the controlled plants. To overcome these periodicity limitations, feedback scheduling aims at applying efficient sampling period selection techniques that account for load and plants dynamics in such a way that the aggregated control performance delivered by the set of control loops is improved. The talk will give an overview of existing work on feedback scheduling for micro-processor and networked control architectures, outlining and discussing main results, while placing an special focus on implementation aspects. The talk will finish discussing open problems
Sampling in Event-driven Control Systems:
The standard design of control systems is based on the periodic
sampling. Every period the data is read from the input, the control
law is computed, and the output is written to the actuators. However
the periodicity of the sampling instants is a constraint that arises
from the ease of implementation and it is not strictly necessary in
the control system. This talk will give an overview of event-driven
control systems, whose execution model mandates to sample the input
``when needed'': the controller is activated upon some condition on
the system status and not periodically. As a result, controllers
resource demands can decrease while stability and acceptable control
performance is still guaranteed. The talk will place an emphasis on
the impact of event-driven controllers on the computing platform. To
this extend, their computational load will be analysed in terms of
activation patterns and real-time feasibility analysis. The
implementation of this controllers adopting the self triggered
approach will be also presented. Finally, open problems will discussed.
Robustness Analysis for Battery Supported Cyber-Physical Systems: We introduce methods
to analyze the robustness of battery supported cyber physical systems under co-designed
control, scheduling and battery management algorithms. Robustness refers to the ability
to maintain system performance under perturbations. Robustness in controller design has
been well defined and understood for a large class of systems, yet robustness of schedul-
ing and battery management methods are relatively less understood. We analyze robustness
of scheduling algorithms by introducing a novel concept of dynamic schedulability. It is
then possible to measure robustness of scheduling algorithms through the strength of the
perturbations that break the dynamic schedulability. Robustness of battery management al-
gorithms is measured by the capability to endure or reject potentially damaging discharge.
Utilizing a dynamic nonlinear battery model, we implement a particle filtering algorithm to
accurately predict the status of the battery under any possible discharge patterns predicted by
the controller and the scheduling algorithms. This procedure allows any battery management
algorithm to make proper decisions.
Antonio Bicchi is Professor of System Theory and Robotics at the
University of Pisa. He
graduated at the University of Bologna in 1988 and was a postdoc scholar at M.I.T. A.I. Lab
in 1988–1990. His main research interests are in Dynamics, kinematics and control of cplex mechanical systems, including robots, autonomous vehicles, and automotive systems;
Haptics and dextrous manipulation; Theory and control of nonlinear systems, in particular
hybrid (logic/dynamic, symbol/signal) systems. He has published more than 200 papers on
international journals, books, and refereed conferences. He currently serves as the Director of the Interdepartmental Research Center “E. Piaggio” of the University of Pisa, and as
Editor in Chief of the Conference Editorial Board for the IEEE Robotics and Automation Society (RAS). Antonio Bicchi is an IEEE Fellow since 2005. He has served as Vice President
of IEEE RAS, Distinguished Lecturer, and editor for several scientific journals including
Transactions on Robotics and Automation and Int.l J. Robotics Research. He has organized
and co-chaired the first WorldHaptics Conference (2005) and Hybrid Systems: Computation
and Control (2007).
Luca
Greco received the “laureadegree in Computer Engineering in 2001 and the Ph.D.
degree in Robotics and Industrial Automation in 2005 from University of Pisa, Italy. From
2005 to 2007 he has been a postdoc at the Interdepartmental Research Center “EPiaggio”,
University of Pisa, Italy. From 2007 to 2009 he has been a postdoc at DIIMA, University of Salerno, Italy. Since September 2009 he is postdoc at L2S – Supélec, Gif-sur-Yvette, France.
During his Ph.D. he studied stability problems for variable structure and switched systems.
Quantized and symbolic control problems have also been considered. His current research
interests concern anytime control, sensor deployment and network controlled systems.
Luigi Palopoli received the computer engineering degree from the
University of Pisa, Pisa,
Italy, in 1992 and the Ph.D. degree in computer engineering from “Scuola Superiore Sant’Anna,
Pisa” in 2002. He is an Assistant Professor of computer engineering at the University of
Trento, Trento, Italy. His main research activities are in embedded system design with a
particular focus on resource–aware control design and adaptive mechanisms for quality-of-
service management. He has served on the program committee of different conferences in
the area of real-time and control systems.
Daniele Fontanelli
received the M.S. degree in Information Engineering in 2001, and the
Ph.D. degree in Automation, Robotics and Bioengineering in 2006, both from the University
of Pisa, Pisa, Italy. He was a Visiting Scientist with the Vision Lab of the University of
California at Los Angeles, Los Angeles, US, from 2006 to 2007. From 2007 to 2008, he
has been an Associate Researcher with the Interdepartmental Research Center “E. Piaggio”,
University of Pisa. From 2008 he joined as an Associate Researcher the Department of
Information Engineering and Computer Science, University of Trento, Trento, Italy. His
research interests include robotics and visual servoing, embedded system control, wireless
sensor networks, networked and distributed control.
Manel Velasco graduated in maritime engineering in 1999 and received the
PhD degree
in automatic control in 2006, both from the Technical University of Catalonia, Barcelona,
Spain. Since 2002, he has been an assistant professor in the Department of Automatic Control at the Technical University of Catalonia. He has been involved in research on artificial
intelligence from 1999 to 2002 and, since 2000, on the impact of real-time systems on control
systems. His research interests include artificial intelligence, real-time control systems, and
collaborative control systems, especially on redundant controllers and multiple controllers
with self-interacting systems.
Pau Marti received the degree in computer science and the PhD degree in automatic
control
from the Technical University of Catalonia, Barcelona, Spain, in 1996 and 2002, respectively.
Since 1996, he has held different teaching positions in the Department of Automatic Control at the Technical University of Catalonia. From 1999 to 2002, he spent several
months as a visiting student at Malardalen University, Vasteras, Sweden, working on real-
time control systems with Prof. Gerhard Fohler. From 2003 to 2004, he held a research
fellow appointment in the Computer Science Department at the University of California at
Santa Cruz, working with Prof. Scott A. Brandt in research on soft realtime systems. His
research interests are real-time control systems, with emphasis on the interaction and integration of control systems, real-time systems, and communication systems.
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