automotive CAN

image from Robert Bosch GmbH,
the developer of CAN

Principal Investigators

PI: João P. Hespanha
Email: hespanha @
Tel: +1 (805) 893-7042
Fax: +1 (805) 893-3262

coPI: Andrew R. Teel
Email: teel @
Tel: +1 (805) 893-3616
Fax: +1 (805) 893-3262

Electrical & Computer Engineering Dept. (ECE)
University of California, Santa Barbara (UCSB)

Postal address:
Room 5157, Harold Frank Hall
Dept. of Electrical & Computer Eng.
University of California
Santa Barbara, CA 93106-9560 USA

quick links

Project Summary

This three-year research and education project will develop protocols and algorithms required to build high-confidence networks of embedded sensors, actuators, and controllers. Essentially at every layer of the protocol stack, the protocols needed for such systems are fundamentally different than those needed for bulk data transfer or even for other "real-time" applications such as voice-over-ip or life video streaming. In view of this, fundamental research is needed to solve multiple open problems in the area of networked embedded systems. Ad-hoc solutions without a strong theoretical underpinning will fail to find appropriate solutions to these problems.

Although this project has a strong theoretical component, the research will be driven by two application areas: networked embedded systems arising in the automotive applications and networks of autonomous vehicles.

The research proposed will make significant contributions to the area of networked embedded systems. In particular, the following fundamental issues will be addressed:

  • Development of formal methods to model the dynamics of networks of embedded systems.
  • Development of formal tools for the analysis and design of impulsive systems.
  • Development of high-confidence algorithms and protocols for the interconnection of sensing, actuation, and control nodes.

The proposed activities will have a strong educational component aimed at motivating undergraduate students to pursue advanced degrees in the engineering sciences. This will be achieved through the following initiatives:

  • Increasing the research content of current UCSB undergraduate courses.
  • Expanding our undergraduate Summer Internships program.


All the results, including papers, reports, and software are available freely to the research community through the world-wide-web. The course materials (including lecture notes, homeworks, laboratory materials, etc.) are also freely available to the academic community.

The publications based upon research funded by this project can be found at the following URL:

This material is based upon work supported by the National Science Foundation under Grant No. CNS-0720842. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

Relevant Research Topics


As computers, digital networks, and embedded systems become ubiquitous and increasingly complex, one needs to understand the coupling between logic-based components and continuous physical systems. This prompted a shift in the standard control paradigm — in which dynamical systems were typically described by differential or difference equations — to allow the modeling, analysis, and design of systems that combine continuous dynamics with discrete logic. This new paradigm is often called hybrid, impulsive, or switched control.

hybrid systems example

The top diagram is a hybrid automaton model of a queuing system that receives jobs at a rate r and dispatches them at a rate B.

Below the hybrid automaton, we can see the corresponding modelica code.

This and other examples of hybrid systems can be found at the web site of the UCSB course ECE229 - Hybrid and Switched Systems .

Good starting points to learn about hybrid control systems include

  • the web site for the UCSB course ECE229 - Hybrid and Switched Systems
  • the following tutorial paper on hybrid control (mostly devoted to stability issues):
    J. Hespanha. Stabilization Through Hybrid Control. In Heinz Unbehauen, Encyclopedia of Life Support Systems (EOLSS), volume Control Systems, Robotics, and Automation, 2004. [bibtex] [pdf]

Our research covers several aspects of hybrid/switched systems:

  • construction of mathematical models to capture switching between discrete modes, delays, stochasticity, etc.
  • development of formal tools to analyze hybrid systems
  • development of methodologies to design control algorithms for hybrid systems.

Publications on this work can be found at the following URL:

While some of our work on hybrid systems is of a theoretical nature, it is motivated by several high-impact application areas, including networked control systems, cooperative control of autonomous systems, communication networks, and systems biology. Details on some of these application areas are included below.


Network Control Systems (NCSs) are spatially distributed systems in which the communication between sensors, actuators and controllers occurs through a shared band-limited digital communication network. The use of a multi-purpose shared network to connect spatially distributed elements results in flexible architectures and generally reduces installation and maintenance costs. Consequently, NCSs have been finding application in a broad range of areas such as the automotive and aerospace industries, mobile sensor networks, remote surgery, automated highway systems, and unmanned aerial vehicles.

NCS This diagram shows the general architecture of an NCS. Encoder blocks map measurements into streams of “symbols” that can be transmitted across the network. Encoders serve two purposes: they decide when to sample a continuous-time signal for transmission, and what to send through the network. Conversely, decoder blocks perform the task of mapping the streams of symbols received from the network into continuous actuation signals. One could also include in the diagram encoding/decoding blocks to mediate the controllers’ access to the network. We do not explicitly represent these blocks because the boundaries between a digital controller and encoder/decoder blocks are often blurry.

The interest in NCSs has been steadily rising due to several factors:

  • Low-cost, low-power, small embedded processors are widely available, which permits endowing sensors and actuators with local processing and sophisticated network protocols.
  • Low-power, high-bandwidth digital communication is widely available to interconnect a large number of sensors, actuators, and controller nodes. Wireless connections are especially attractive because they have minimal installation costs (although they can be severely constrained in terms of bandwidth).

Inexpensive computation and ubiquitous embedded sensing, actuation, and communication provide tremendous opportunities for societal impact, but also great challenges in the design of networked control systems, because the traditional unity feedback loop that operates in continuous time or at a fixed sampling rate is not adequate when sensor data arrives from multiple sources, asynchronously, delayed, and possibly corrupted. Moreover, the design of NCSs poses novel questions that lie at the intersection of control, communication, and signal processing:

  • How often/When should a sensor transmit a measurement to a control unit?
  • How often/When should a control unit send a control update to an actuator?
  • What forms of error correction/routing/data compression are most adequate for control applications?
  • Which wireless medium-access methods are most effective for control applications?
  • How can one implement a control/estimation algorithm within an embedded processor so as to minimize energy expenditure?

Our research on NCSs is motivated by the following observations:

  • At essentially every layer of the protocol stack, the protocols needed for networks of embedded systems are fundamentally different than those needed for bulk data transfer or even for other “real-time” applications such as voice-over-ip or live video streaming.
  • Fundamental research is needed to solve multiple open problems in the area of networked embedded systems. Adhoc approaches without a strong theoretical underpinning will fail to find appropriate solutions to these problems.
automotive CAN

The widely used Controller Area Network (CAN) bus standard manages the medium access for wireline connections of electronic control units (ECUs). Originally developed for automobiles, the CAN bus was specifically designed to be robust in electromagnetically noisy environments such as those arising in the Supervisory Control And Data Acquisition (SCADA) systems used to monitor or to control chemical or transport processes, in municipal water supply systems, to control electric power generation, transmission and distribution, gas and oil pipelines, and other distributed processes. The CAN standard uses a priority-based collision-free medium access protocol. Image from Robert Bosch GmbH, the developer of CAN.

A good starting point to learn about the design of controllers for NCSs is the following survey:

J. Hespanha, P. Naghshtabrizi, Y. Xu. A Survey of Recent Results in Networked Control Systems. Proc. of IEEE Special Issue on Technology of Networked Control Systems, 95(1):138—162, Jan. 2007. [bibtex] [pdf]

Publications on this work can be found at the following URL:


Robotic agents have the potential to free humans from unpleasant, dangerous, and/or repetitive tasks in which human performance would degrade over time due to fatigue. Currently, assembly lines for the automotive industry are highly automated using robots for welding, painting, machine loading, parts transfer and assembly, etc. However, these robotic systems have little autonomy and essentially continuously execute preprogrammed motions with little cognition of their surroundings.

The expression autonomous agents refers to the control of ground, aerial or aquatic robots so as to perform tasks that require a significant amount of information gathering, data processing, and decision making, without explicit human control. Especially promising (and challenging) is the use of groups of robots to perform complex tasks in a cooperative fashion. These tasks include:

  • environmental monitoring, e.g., for air/water/soil temperature, water pH and salinity, toxic compounds, or mapping endangered species
  • search and rescue operations for disaster response
  • law enforcement activities, such as surveillance or supporting a swat team
  • agricultural activities such as crop spraying

The interest in this area sparked in the last few years because of two main factors:

  • Cost: Advances in materials and fabrication processes have significantly reduced the cost of the hardware platforms (airframes, motors, etc.) and advances in MEMS and VLSI have resulted in sensors (inertial, magnetic, and GPS) and flight control systems that are lightweight, very energy efficient, and cheap.
  • Computation: Because microprocessors and hard drives are becoming fast, small, rugged, energy efficient, and cheap, it is now possible to place significant computational power onboard a flying or ground-moving robot. This allows for the deployment of algorithms that lead to sophisticated autonomous behavior.
Unicorn UAV Unicorn UAV - detail gimbal

The Unicorn UAV from Procerus Technologies is basically a foam wing powered by an electric motor. It has an onboard auto-pilot fed by a GPS unit, three-axis rate gyros and accelerometers, differential and absolute air pressure sensors, and a magnetometer. The autopilot communicates with a ground station through a radio link. We have used Unicorns to test our cooperative control algorithms.

Two key technical challenges in this area have driven our research:

  • Computational complexity: Optimal solutions to many (most!) of the problems that one would like to solve using teams of autonomous agents have large computational complexity. Sometimes this complexity is present even in single-agent versions of these problems (e.g., search), whereas other times is arises when one seeks decentralized solutions, i.e., solutions that do not require centralized decision making.
  • Limited communication: Wireless communication is typically used by a team of agents to coordinate their actions. However, wireless networks are severely constrained in terms of bandwidth and range. In addition, wireless communication is notoriously unreliable. In view of this, for an algorithm to be useful in practice it must require little inter-agent communication and it must be robust with respect to communication faults.

Path planning for an Unmanned Air Vehicle (UAV) with a camera mounted on a gimbal system. By controlling the field-of-view (FOV) of the camera, one enlarges the field-of-regard (FOR) that can be imaged from each position of the UAV.

When computing an optimal path for the UAV, one should take into account that the FOV of the camera can be controlled through the gimbal mechanism. For maximum coverage, one thus needs to consider jointly the problems of path planning for the UAV with that of scheduling the motion of the camera. By solving these problems jointly, one can significantly increase coverage, at the expense of larger (but still manageable) computational complexity.

This picture refers to joint work between our research group (mostly former PhD student James Riehl) and the Toyon Research Corp. (Dr. Gaemus Collins). The algorithms developed were flight tested in Unicorn UAVs in November 2007. In these tests, a team of 4 UAVs (two real and two simulated) cooperated in searching for and tracking a moving ground target.

Publications on this work can be found at the following URLs:

Relevant Courses

  • ECE147C — Control Systems Design Project & ME106A — Advanced Mechanical Engineering Laboratory (Spring’04, Spring'05, Spring’06, Spring'07)
  • ECE229 — Hybrid and Switched Systems (Winter’04, Fall’05), see
  • ECE594D — Modeling and Control of Large-Scale Distributed Systems (Winter'02)
  • ECE594D — Hybrid Control and Switched Systems (Spring'02)

Recent talks & events


“Stochastic Hybrid Systems: Modeling, analysis, and applications to networks and biology” Electrical Engineering and Computer Science Seminar, UC Berkeley, May 1, 2006. [slides]

“Internet Routing Games” Invited talk at the Workshop on Learning and Information in Games and Control, California Institute of Technology, Mar. 22, 2006. [slides]

“Game theoretical approaches to secure and robust routing,” UC Berkeley Seminar, Apr. 22, 2005. [slides]


Course on Modeling Analysis and Design of Hybrid Control Systems at the HYCON Graduate School on Control from the European Embedded Control Institute, February 12-16, 2007.

Students, Postdocs, and Visitors


Shaunak Bopardikar, BT/MT in Mechanical Engineering 2004 (Indian Institute of Technology, Bombay), started PhD in Fall 2005 (co-advised with Prof. Francesco Bullo).

Alexandre Mesquita, Undergraduate Degree in Electrical Engineering 2006 (Divisão de Engenharia Eletrônica, Instituto Tecnológico de Aeronáutica - ITA), started PhD in Fall 2006.


Abhyudai Singh, PhD 2008, BT in Mechanical Engineering (Indian Institute of Technology, Kaput), currently Postdoctoral Scholar, University of California, San Diego (as of Oct. 2008).

James Riehl, PhD 2007, BS in Engineering 2002 (Harvey Mudd College), currently Systems Design Engineer Specialist, AT&T Government Solutions, Inc. (as of Oct. 2007).

Payam Naghshtabrizi, PhD 2007, BS in Electrical Engineering 1997 (Sharif University of Technology, Tehran, Iran), currently at Ford Motor Company (as of Oct.~2007).

Prabir Barooah, PhD 2007, BT 1996 (Indian Institute of Technology, Kanpur), currently Assistant Professor at the Department of Mechanical Engineering, University of Florida, Gainsville (as of Sep 2007).


Daniel Klein, PhD 2007 (University of Washington, Seattle, WA).


This list only contains visitors that stayed at UCSB for 2 weeks or longer (list sorted by date of last departure)

Duarte Antunes, PhD student, Inst. Superior Técnico, Lisbon, Portugal, 8/20/07-12/20/07, 4/4/08-6/28/08, 10/1/08-12/12/08.

Pietro Tessi, PhD student, University of Florence, Italy, 9/3/08-2/25/09

Prof. Kenji Hirata, Dept. of Mechanical Engineering, Nagaoka University of Technology, Japan, 9/1/08-8/31/09.

Prof. Ti-Chung Lee, EE dept., Minghsin Univ. of Science & Tech, Taiwan, 8/3/06-8/24/06 and 7/13/07-8/3/07