Experimental Research

1. Alberto Sangiovanni-Vincentelli University of California Berkeley Experimental Research

3. Overarching Criteria An application should exercise Theory: hybrid models, Models of Computation, control algorithms Tools and Environments Path to implementation An application should be relevant for industry or for government agencies

4. Outline Industrial cases Automotive (safety-critical distributed systems) System-on-Chip (high-complexity platforms) Internal experimental test benches Wireless Sensor Networks (security, low power) UAVs (complex control, sensor integration) New domains: Soft walls Biological Systems

5. Disaggregation:Electronic Systems Design Chain

6. Automotive Supply Chain:Car Manufacturers

7. Electronics for the Car: A Distributed System

8. Complexity, Quality, Time-to-Market: TODAY

9. 1.1.

10. Design Flow

11. Design Methodology

12. Power-train Specification

13. Model of Power-train

14. Single Cylinder Hybrid Model

15. Giotto Applications (TAH):Drive-by-Wire Throttle BMW Throttle Control OSEKWorks RTOS PID Controller Motorola MPC555 40Mhz Methodology:from a Matlab/Simulink Model of the Controller: a) Timing Code (Giotto):generated via S/G Translator.(University of Salzburg)b) Functionality Code (C):via Real-Time workshop.

16. Outline Industrial cases Automotive (safety-critical distributed systems) System-on-Chip (high-complexity platforms) (ASV, K. Keutzer) Internal experimental test benches Wireless Sensor Networks (security, low power) UAVs (complex control, sensor integration) New domains: Soft walls Biological Systems

17. Typical Application: Intel PXA800F

18. Typical Problem: Next Generation PXA800F This design example, with the redesign of the crossbar switch touches upon all the features and capabilities of Metro. I did not want to put anything here to say that this is going to be a crossbar switch. I just left it as an �Interconnection Module� and simply focused on the fact that we�ll be doing Power Estimation with Metro using Quantities (which is indeed one of the things we will do).This design example, with the redesign of the crossbar switch touches upon all the features and capabilities of Metro. I did not want to put anything here to say that this is going to be a crossbar switch. I just left it as an �Interconnection Module� and simply focused on the fact that we�ll be doing Power Estimation with Metro using Quantities (which is indeed one of the things we will do).

19. Typical Application: The Intel MXP5800 Complete Solution for high performance Digital Imaging Applications Multifunction Printers High End scanners

20. Outline Industrial cases Automotive (safety-critical distributed systems) System-on-Chip (high-complexity platforms) Internal experimental test benches Wireless Sensor Networks (security, low power) UAVs (complex control, sensor integration) New domains: Soft walls Biological Systems

21. Evolution of Motes

22. Tiny OS (TOS) Jason Hill, Robert Szewczyk, Alec Woo, David Culler TinyOS Ad hoc networking

23. Networks of Embedded Systems (SS) Pursuit Evasion Game Demo with 100 sensor motes performed in July 2003 10^4 mote scaling issues being discussed for oil pipeline surveillance and protection. For conceptual issues see Franceschetti and Bollobas talks to follow Drop experiment planned with 40 motes at China Lake in February 2003 Infrastructure Protection using secure networks of embedded systems is a new direction.

24. VisualSense: Modeling and Simulation of Wireless Sensor Nets Based on Ptolemy II

25. Picoradio Sensor Networks (BWRC, J. Rabaey and ASV) Key challenges Satisfy tight performance and cost constraints (especially power consumption) Identify Layers of Abstraction (Protocol Stack) Develop distributed algorithms (e.g. locationing, routing) for ubiquitous computing applications Design Embedded System Platform to implement Protocol Stack efficiently Quali sono i challenges: Queste reti wireless di sensori distribuiti in cui i criteri fondamentali sono basso costo, bassissima potenza e affidabilita� della rete nonostante la vulnerabilita� dei singoli nodi. La ricerca che si fa qui e� secondo linee simili utilizzando metodologie e protocolli che saranno sviluppati all�Aquila per applicazioni di nostro interesse Acquisire competenze in loco indispensabili all�avanzamento dello stato dell�arte in questo settore Quali sono i challenges: Queste reti wireless di sensori distribuiti in cui i criteri fondamentali sono basso costo, bassissima potenza e affidabilita� della rete nonostante la vulnerabilita� dei singoli nodi. La ricerca che si fa qui e� secondo linee simili utilizzando metodologie e protocolli che saranno sviluppati all�Aquila per applicazioni di nostro interesse Acquisire competenze in loco indispensabili all�avanzamento dello stato dell�arte in questo settore

26. PicoRadio: Applications

27. Objectives To develop experimental platforms of increasing complexity in order to develop Distributed and embedded observation and control design tools Robust and scalable observers and controllers Hybrid and distributed fault tolerant controllers and observers Specific Experimental Platforms Vibro-acoustic structures with embedded Smart Structures technology Launch vehicle payload fairing scale prototype Acoustic distributed sensor network Critical issues at the interface of mechanical & computational systems: Observation and control design in an embedded and distributed computational environment Effects of embedded system limitations on observation and control Leveraging embedded software technologies for control

28. Acoustic Localization Experiments (K.Frampton, Vanderbilt) Sensor platform: UCB MICA2: 8MHz microcontroller, 4KB RAM, 433MHz radio, TinyOS ISIS Acoustic Sensorboard: 3 acoustic channels, programmable up to 1MHz ADC, Xilinx Spartan FPGA, I2C interface

29. Current Applications Launch vehicle payload faring

30. Outline Industrial cases Automotive (safety-critical distributed systems) System-on-Chip (high-complexity platforms) Internal experimental test benches Wireless Sensor Networks (security, low power) UAVs (complex control, sensor integration) New domains: Soft walls Biological Systems

31. High-level control system development, High-resolution vision-based navigation platformHigh QoS wireless communication, formation flight test-bed In berkeley , we started our UAV research in 1996. At this time, we were primarily interested in the design of single UAV low-level control system. As our research progresses, we have broaden our interests on hierarchical vehicle control, multiple vehicle control, formal verification of flight control system in terms of hybrid automata and so on. Also, in terms of UAV platform, we have acquired 11 helicopters and 3 of them are currently fully instrumented. IN the top, we have 60-class helicopter called ursa minors, in the middle, ursa magna based on Yamaha Agiriculturla helicopter R-50, and at the bottom, ursa maxima series based on Yamaha R-MAX.In berkeley , we started our UAV research in 1996. At this time, we were primarily interested in the design of single UAV low-level control system. As our research progresses, we have broaden our interests on hierarchical vehicle control, multiple vehicle control, formal verification of flight control system in terms of hybrid automata and so on. Also, in terms of UAV platform, we have acquired 11 helicopters and 3 of them are currently fully instrumented. IN the top, we have 60-class helicopter called ursa minors, in the middle, ursa magna based on Yamaha Agiriculturla helicopter R-50, and at the bottom, ursa maxima series based on Yamaha R-MAX.

32. The Legacy of Success in UAV Research at BErkeley AeRobotics Pursuit-evasion games 2000- to date Architecture for multi-level rotorcraft UAVs 1996- to date Landing autonomously using vision on pitching decks 2001- to date Multi-target tracking 2001- to date Formation flying and formation change 2002, 2003 Conflict resolution with model predictive control/ stochastic hybrid systems, 2003 Airspace Management and personal aviation, 2004?

33. Platform-Based Design of Unmanned Aerial Vehicles (source: J. Liebman)

34. UAV System: Sensor Overview

35. UAV System: Sensor Configurations As I mentioned towards the beginning, changes need to be made to the hardware part of the system as well, in order to create an entirely synchronous hybrid system. First, the system needs one clock, which would be updated by the gps clock. Next the system would need an actuation scheme which could be time triggered. Cedric pointed out the issues involved with the current event driven servo system, time triggered actuators do exist on other helicopters. Finally, the sensors would need to be used in a pull configuration instead of the current push configuration. So upon a software request the sensors would provide the most recent data.As I mentioned towards the beginning, changes need to be made to the hardware part of the system as well, in order to create an entirely synchronous hybrid system. First, the system needs one clock, which would be updated by the gps clock. Next the system would need an actuation scheme which could be time triggered. Cedric pointed out the issues involved with the current event driven servo system, time triggered actuators do exist on other helicopters. Finally, the sensors would need to be used in a pull configuration instead of the current push configuration. So upon a software request the sensors would provide the most recent data.

36. Platform Based Design for UAVs Goal Abstract details of sensors, actuators, and vehicle hardware from control applications

37. Platform Based Design for UAVs Device Platform Isolates details of sensor/actuators from embedded control programs Communicates with each sensor/actuator according to its own data format, context, and timing requirements Presents an API to embedded control programs for accessing sensors/actuators Language Platform Provides an environment in which synchronous control programs can be scheduled and run Assumes the use of generic data formats for sensors/actuators made possible by the Device Platform

38. Giotto Applications:Unmanned Helicopter Control Systems

39. Targeting a DARPA/SEC Application:The Caltech Vehicles (EAL) Experimental code generation using component specialization. Heterogeneous modeling for hardware-in-the-loop simulation. Mobile code experiments for rapid reconfiguration. A safe system for avionics experiments

40. Experimental Test Bed (G. Biswas, Vanderbilt): Fuel Transfer System Always have adequate flow to engines Avoid imbalances that affect center of gravity of system Two primary subsystems, left and right symmetric Engine feed system Transfer system Engine Feed System Feed tanks with level control valves, Boost pump, interconnect valve, pipes Transfer System Fuselage and Wing Tanks, Redundant pump system, Transfer manifold, pipes

41. Tool Chain for Experiments

42. Recent Efforts Experimental Platforms are complete Computational Platform is complete Distributed closed loop sampling rate of 2kHz Current Efforts Testing of distributed control algorithms Development of distributed system identification Testing of distributed acoustic tracking

43. Outline Industrial cases Automotive (safety-critical distributed systems) System-on-Chip (high-complexity platforms) Internal experimental test benches Wireless Sensor Networks (security, low power) UAVs (complex control, sensor integration) New domains: Soft walls Biological Systems

44. Soft Walls: Motivation (EAL) Reduce reliance on Anti-aircraft batteries Scrambled fighters Armed air marshals or pilots Cockpit fortifications

45. Basic Idea Protect airspaces using on-board avionics Non-networked solution Non-hackable solution Maximize pilot authority

46. Key Design Objective

47. Outline Industrial cases Automotive (safety-critical distributed systems) System-on-Chip (high-complexity platforms) Internal experimental test benches Wireless Sensor Networks (security, low power) UAVs (complex control, sensor integration) New domains: Soft walls Biological Systems

48. Stochastic Hybrid Systems and the Analysis of Cellular Networks

49. Example 2: E. coli Piliation A population of K E. coli Certain amount of available food Each E. coli is either piliated or unpiliated. Piliated E. coli generate food Unpiliated E. coli consume food Lack of food ? E. coli more likely switch to or remain piliated Abundant food ? E. coli more likely switch to or remain unpiliated

50. Challenges of Systems (post genomic biology) Hybrid Systems Models for Intracellular functioning: stochastic hybrid systems (see talk by Abate) Hybrid Systems tools for ensembles of cells: group behavior of complex networked systems Biologically complex networks are an exemplar of how networked embedded systems could evolve, self-organize and reprogram themselves (network programming?) See talk by Franceschetti

51. Concluding Remarks Applications are critical to drive research and to test quality of results Safety-critical Real Time and secure system emphasis Industrial and Experimental Test Benches Rigorous methodology for hybrid distributed systems

52. Embedded Software: Today

53. Embedded Software: Future?