CMPE 142: Introduction to

Cyber-physical Systems (CPS)

Ricardo SanfeliceDepartment of Computer EngineeringHybrid Dynamics and Control LabUniversity of California, Santa Cruz

Broad Scope of Cyber-physical Systems

Cyber-physicalSystems

ComputerNetworks

NonsmoothControlSystems

DigitalControl

Multi-modeControl

DistributedControl

PowerNetworks

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Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Broad Scope of Cyber-physical Systems

Systems of today feature:

◮ Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).

◮ Modular hardware for flexibility andreconfigurability.

◮ Distributed coordination and control.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Broad Scope of Cyber-physical Systems

Systems of today feature:

◮ Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).

◮ Modular hardware for flexibility andreconfigurability.

◮ Distributed coordination and control.

xuplant

controller

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Broad Scope of Cyber-physical Systems

Systems of today feature:

◮ Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).

◮ Modular hardware for flexibility andreconfigurability.

◮ Distributed coordination and control.

xu

logic for decision making multiple control laws

plant

controller

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Broad Scope of Cyber-physical Systems

Systems of today feature:

◮ Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).

◮ Modular hardware for flexibility andreconfigurability.

◮ Distributed coordination and control.

xu

distributed

logic for decision making multiple control laws

plant

controller

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Broad Scope of Cyber-physical Systems

Systems of today feature:

◮ Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).

◮ Modular hardware for flexibility andreconfigurability.

◮ Distributed coordination and control.

xu

interfaceinterface

logic for decision making multiple control laws

plant

controller

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Broad Scope of Cyber-physical Systems

Systems of today feature:

◮ Heterogeneous components and interfaces(e.g. humans, networks, analog/digital devices).

◮ Modular hardware for flexibility andreconfigurability.

◮ Distributed coordination and control.

xu

D/A

A/D

network

interfaceinterface

environment

logic for decision making multiple control laws

perturbations

human interaction

ZOH

plant

controller

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS Projects

Feedback Control for Smart Grids

◮ Hetereogeneous networked power sources,buses, users, and loads

◮ Conversion required between differentwaveforms

◮ Dynamic demands and supplies

◮ Multiple time scales(e.g., fast and slow switching)

Classical approaches:

◮ Steady-state and averaged models

◮ Linear control design

◮ Bening conditions

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...

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~

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DC bus

AC busPhotovoltaicarray

DC

DC

DC

DC

DC

DC

AC

AC

AC

AC

Diesel generator

Turbine

Fuel cells

Storage

AC loads

DC loads

Communication ( )

and Control ( ) bus

Electric power grid

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS ProjectsPower Conversion for Smart Grids

◮ Renewables provide power with highfluctuation

◮ DC/DC conversion is required beforeinjection to the grid

◮ Adaptive DC/AC conversion

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s1

vDC

iL io

vc

vgL,R

c

DC/AC

HybridController

~

...

...

~

~

DC bus

AC busPhotovoltaicarray

DC

DC

DC

DC

DC

DC

AC

AC

AC

AC

Diesel generator

Turbine

Fuel cells

Storage

AC loads

DC loads

Communication ( )

and Control ( ) bus

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS ProjectsPower Conversion for Smart Grids

◮ Renewables provide power with highfluctuation

◮ DC/DC conversion is required beforeinjection to the grid

◮ Adaptive DC/AC conversion

sos4

s3 s2

s1

vDC

iL io

vc

vgL,R

c

DC/AC

HybridController

High Penetration of RenewablesU.S.: 20% by 2030Europe: 16% by 2020

~

...

...

~

~

DC bus

AC busPhotovoltaicarray

DC

DC

DC

DC

DC

DC

AC

AC

AC

AC

Diesel generator

Turbine

Fuel cells

Storage

AC loads

DC loads

Communication ( )

and Control ( ) bus

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS ProjectsPower Conversion for Smart Grids

◮ Renewables provide power with highfluctuation

◮ DC/DC conversion is required beforeinjection to the grid

◮ Adaptive DC/AC conversion

sos4

s3 s2

s1

vDC

iL io

vc

vgL,R

c

DC/AC

HybridController

High Penetration of RenewablesU.S.: 20% by 2030Europe: 16% by 2020

~

...

...

~

~

DC bus

AC busPhotovoltaicarray

DC

DC

DC

DC

DC

DC

AC

AC

AC

AC

Diesel generator

Turbine

Fuel cells

Storage

AC loads

DC loads

Communication ( )

and Control ( ) bus

Collaboration with Sandia NationalLabs on testing of control algo-rithms in their platform (DETL)

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS Projects

dynamic communication

network Adversaries

Static and Mobile Agents

Control of Reconfigurable Multi-Robot Systems

◮ Groups of heterogeneousnetworked agents

◮ Adversaries can disruptthe network(jamming, destructive actions)

◮ Locations and capabilitiesunknown

Scenarios of DoD interest:

◮ Electronic warfare

◮ Satellite communications

◮ Disaster relief

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS Projects

Reconfigurable Satellite Communications

◮ Dynamic ground-satellite links

◮ Dynamic signal-to-noise ratio oncommunication channels

◮ Jamming attacks (MILSATCOM)

GEO

LEOground station

adversary

satellite

dynamicnetwork

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS Projects

Reconfigurable Satellite Communications

◮ Dynamic ground-satellite links

◮ Dynamic signal-to-noise ratio oncommunication channels

◮ Jamming attacks (MILSATCOM)

GEO

LEOground station

adversary

satellite

dynamicnetwork

Recent initiatives, such asthe National BroadbandPlan, challenge the tradi-tional FCC approach to allo-cating spectrum, requestinga new U.S. spectrum policyallowing for dynamic alloca-tion and utilization.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS Projects

Control of Aerial Vehicles with Limited and Faulty Sensors

◮ Autonomous recovery control

◮ Low cost sensing for autonomous navigation

◮ Sensor failures affect stability and performance

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS Projects

Control of Aerial Vehicles with Limited and Faulty Sensors

◮ Autonomous recovery control

◮ Low cost sensing for autonomous navigation

◮ Sensor failures affect stability and performance

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Sample CPS Projects

Control of Aerial Vehicles with Limited and Faulty Sensors

◮ Autonomous recovery control

◮ Low cost sensing for autonomous navigation

◮ Sensor failures affect stability and performance

UAVs in the National Air Space(NAS): 2012 bill giving FAA threeyears to “integrate” UAVs into theNAS (set policies, standards, etc.)

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

What’s CMPE 142 about?

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

What’s CMPE 142 about?

◮ Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical process

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

What’s CMPE 142 about?

◮ Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

What’s CMPE 142 about?

◮ Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation

◮ Modeling of the physical and the cyber

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

What’s CMPE 142 about?

◮ Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation

◮ Modeling of the physical and the cyber

◮ Tools to analyze the behavior of systems with bothcomponents

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

What’s CMPE 142 about?

◮ Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation

◮ Modeling of the physical and the cyber

◮ Tools to analyze the behavior of systems with bothcomponents

tools solely for the physical or for cyber do not apply

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

What’s CMPE 142 about?

◮ Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation

◮ Modeling of the physical and the cyber

◮ Tools to analyze the behavior of systems with bothcomponents

tools solely for the physical or for cyber do not apply

◮ Understand core theoretical concepts needed to study CPS

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

What’s CMPE 142 about?

◮ Systems that combine physical and cyber components,potentially networked and with computations integrated withphysical processphysical = physical plant/process/networkcyber = software/algorithm/computation

◮ Modeling of the physical and the cyber

◮ Tools to analyze the behavior of systems with bothcomponents

tools solely for the physical or for cyber do not apply

◮ Understand core theoretical concepts needed to study CPS

◮ Apply tools and concepts to a CPS application

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Course Description

Cyber-physical systems combine digital and analog devices, inter-faces, networks, computer systems, and the like with the naturaland man-made physical world. The inherent interconnected andheterogeneous combination of behaviors in these systems makestheir analysis and design a challenging task. Safety and relia-bility specifications imposed in cyber-physical applications, whichare typically translated into stringent robustness standards, aggra-vate the matter. Unfortunately, state-of-the-art tools for systemanalysis and design cannot cope with the intrinsic complexity incyber-physical systems. Tools suitable for analysis and designof cyber-physical systems must allow a combination of phys-ical or continuous dynamics and the cyber or computationalcomponents, as well as handle a variety of types of perturbations,such as exogenous disturbances, time delays, and system failures.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

◮ Event triggered systems

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

◮ Event triggered systems

◮ Stateflow

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

◮ Event triggered systems

◮ Stateflow

◮ Timed automata

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

◮ Event triggered systems

◮ Stateflow

◮ Timed automata

◮ Hybrid automata

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

◮ Event triggered systems

◮ Stateflow

◮ Timed automata

◮ Hybrid automata

◮ Concurrency

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

◮ Event triggered systems

◮ Stateflow

◮ Timed automata

◮ Hybrid automata

◮ Concurrency

◮ Invariants

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

◮ Event triggered systems

◮ Stateflow

◮ Timed automata

◮ Hybrid automata

◮ Concurrency

◮ Invariants

◮ Linear temporal logic

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Plan of Work

◮ Continuous-time systems

◮ Modeling of physical processes

◮ Linear time-invariant systems

◮ Numerical simulation of differential equations

◮ Discrete-time systems and return maps

◮ Finite state machines

◮ Event triggered systems

◮ Stateflow

◮ Timed automata

◮ Hybrid automata

◮ Concurrency

◮ Invariants

◮ Linear temporal logic

◮ Verification

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Some Items in Fine Print

Prerequisites: The course is self contained. Students are expectedto have basic background on logic circuits (CMPE 100 orequivalent), programming (CMPE 13 or equivalent), mathematicalmodeling of dynamical systems (CMPE 8 recommended),differential equations, linear algebra, and basic calculus.Knowledge of Matlab/Simulink will be useful.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Some Items in Fine Print

Structure and Grading Scheme:

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Some Items in Fine Print

Structure and Grading Scheme:

◮ Homework will account for 20% of final grade.Schedule: ≈ one HW every other week.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Some Items in Fine Print

Structure and Grading Scheme:

◮ Homework will account for 20% of final grade.Schedule: ≈ one HW every other week.

◮ Quizz, will account for 10% of final grade.Schedule: announced 1.5 days in advance.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Some Items in Fine Print

Structure and Grading Scheme:

◮ Homework will account for 20% of final grade.Schedule: ≈ one HW every other week.

◮ Quizz, will account for 10% of final grade.Schedule: announced 1.5 days in advance.

◮ Midterm, 20% of final grade.Schedule: 4pm on 11/04, in class.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Some Items in Fine Print

Structure and Grading Scheme:

◮ Homework will account for 20% of final grade.Schedule: ≈ one HW every other week.

◮ Quizz, will account for 10% of final grade.Schedule: announced 1.5 days in advance.

◮ Midterm, 20% of final grade.Schedule: 4pm on 11/04, in class.

◮ Final, 30% of final grade.Schedule: 4pm on 12/15, in class.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Some Items in Fine Print

Structure and Grading Scheme:

◮ Homework will account for 20% of final grade.Schedule: ≈ one HW every other week.

◮ Quizz, will account for 10% of final grade.Schedule: announced 1.5 days in advance.

◮ Midterm, 20% of final grade.Schedule: 4pm on 11/04, in class.

◮ Final, 30% of final grade.Schedule: 4pm on 12/15, in class.

◮ Presentations and project report, 20% of final grade.Schedule: Presentations on 12/11, in class; final projectreport due 5pm on 12/17.

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz

Some Items in Fine Print

Structure and Grading Scheme:

◮ Homework will account for 20% of final grade.Schedule: ≈ one HW every other week.

◮ Quizz, will account for 10% of final grade.Schedule: announced 1.5 days in advance.

◮ Midterm, 20% of final grade.Schedule: 4pm on 11/04, in class.

◮ Final, 30% of final grade.Schedule: 4pm on 12/15, in class.

◮ Presentations and project report, 20% of final grade.Schedule: Presentations on 12/11, in class; final projectreport due 5pm on 12/17.

Talk about the Project...

Ricardo Sanfelice - Computer Engineering - University of California, Santa Cruz