Stuff I’ve Worked OnThe Age of Intelligent Systems Has Arrived

…I REALLY LOVE MY JOB !

WAESO and NSF Bridge to the Doctorate

Friday, February 14th 2012

Arizona State University

Armando A. Rodriguez

Professor, Department of Electrical Engineering

Intelligent Embedded Systems Laboratory (IeSL)

GWC 352, aar@asu.edu

http://aar.faculty.asu.edu

Revolutionary Times

For the first time in history, amazing new

computing technologies are becoming

accessible to the masses!

- Intelligent Systems Are Coming….

- Intelligent Systems Require Feedback…

- This is what controls is about!

Acknowledgements

• Sponsors

– White House, NSF, NASA, DARPA, AFOSR, WAESO

– CEINT, Honeywell, Intel, Microsoft, Boeing, Xilinx, SEMY, Mathworks, Tektronix.

• My Students!

Outline

• What Is Controls?

• Where Is Controls Used?

• Prior and Current Research

• Summary

What Is Controls?

r e udi do

K P

n

y

Controller Plant

• Design K s.t. closed loop system exhibits

stability and high performance. (Want y = r)

- P : Physical System/Process to be Controlled

- K : System to be Designed

actual output

desired output

controlerror

sensor noise

disturbances

Example: Vehicle Cruise Control

• P - Vehicle

• r - Speed reference command (desired speed)

• y - Actual speed

• u - Fuel flow to engine

• K - Controller

– Want y = r– Actual speed to follow speed commands

Issues• Nonlinear Dynamics

– Ordinary/partial differential equations– Saturating actuators (hard control limits); Rate limits

• Noninvertible Dynamics– Instabilities (unbounded solutions, characteristic roots in open right half plane)– Time delays and other lag effects

• Uncertainty – only nominal models are available– Dynamic

• Actuator and sensor dynamics• High frequency parasitics

– Structural modes (e.g. flexible spacecraft); Time delays (e.g. CVD furnace)

– Parametric: Masses, aerodynamic coefficients, friction coefficients, etc.– Stochastic Disturbances and Sensor Noise

• Amplitude, mean, variance, and spectral content

• Digital Implementation Issues– Sampling and actuation rates– Analog-to-digital and Digital-to-analog - speed, resolution,

quantization/reconstruction error– Measurement noise, time delays (phase lag), and nonlinearities

Research: Need Systematic Control System Design Methodology

• Modeling, Simulation, Analysis

- Determination of Realistic Design Specifications

• Design Control System (via Model-Based Optimization)

- typically on the basis of linearized models

- gain scheduling (“glue” control design together)

• Evaluate design using hi-fidelity simulator

• Design Implementation (Rapid prototyping)

- computer, microprocessor, DSP, FPGAs

• Hardware Evaluation

NOTE: Control system design process is highly iterative!

Control System Design Process

CLAIM:

Controls Is Inherently Multidisciplinary

... it touches all disciplines…

•Acoustic - acoustic cancellation for a concert hall; intelligent hearing devices

•Aerospace - altitude hold system for aircraft; all-weather landing system; control of remotely piloted vehicles; launch vehicles; control of reconfigurable aircraft

•Automation and Manufacturing – coordination of autonomous robots; resource allocation within a semiconductor fabrication facility

•Biological - neuromuscoloskeletal control systems; cardiovascular control systems; disease and epidemic containment

What Needs To Be Controlled?

What Needs To Be Controlled?• Capital Investment - variable risk securities portfolio

risk/return; asset management

• Defense - high performance fighters; tactical missiles; ballistic missile theatre defense; guidance and navigation; combat assault helicopters

• Ecological - global warming and ozone depletion policy

• Economics - money supply and interest rate management

• Electrical/Chemical - diffusion furnaces; semiconductor processes; read/write head control for storage

• Mechanical - active suspension for mobile laboratory

• Materials - control of smart composite (deformable) materials

What Needs To Be Controlled?• Medical - control of telemedical robotic systems (e.g. microscope

positioning and vibration suppression) for precision surgery

• Nuclear - temperature control for nuclear reactor

• Ocean - depth control for underwater exploration vehicle; submarine

• Public Policy - resource allocation for urban planning and homeland

security

• Space Based Surveillance - pointing control system for telescopic imaging,

weather, surveillance, monitoring system; satellites

• Space Exploration – interplanetary probes, crew exploration vehicle,

robotic vehicles (e.g. Mars rovers)

• Structural - active earthquake control for skyscrapers

Pretty Amazing List!

Does the list help you understand what control engineers do?

Specific Areas of Research

• Optimization Based Control System Design for– MIMO Nonlinear Systems– Distributed Parameter Systems– Systems with Multiple Hard Nonlinearities– Sampled Data and Multi-Rate Systems

• Application Areas– Aerospace and robotic systems, space structures,

semiconductors, low power electronics, advanced vehicles and transportation systems

Research Focal Areas

• Modeling, Simulation Animation, and Real-Time Control (MoSART)

• Flexible Autonomous Machines operating in an uncertain Environment (FAME)

• Intelligent Embedded Systems

• Integrated Real-Time Health Monitoring, Modeling, and Fault-Tolerant Control– Fault detection, classification, and control law adaptation– Reconfigurable hardware (FPGAs)

Select Control Projects • Semiconductor Manufacturing Facility (e.g. fab scheduling) • Molecular Beam Epitaxy (MBE), Chemical Vapor Deposition (CVD)• Missile Guidance and Control Systems (e.g. Patriot, EMRAAT)• High Performance Jets (e.g. JSF, High Speed Civil Transport)• Rotorcraft (e.g. Blackhawk, Apache, TLHS), Tilt-wing Rotorcraft (TWRC)• Unpilotted Air Vehicles (UAVs), Micro Air Vehicles (MAVs)• Scramjet-Powered Hypersonic Vehicle Control and Design• Jet Engines (e.g. GE turbofan)• Submarines• Automotive (e.g. cruise, engine emissions, suspension, noise cancellation)• Flexible Space Structure (e.g. SPICE: Laser Weapon, Telescope)• Satellites, Spacecraft, and space probes (e.g. JIMO) • Intelligent Robotic Systems (e.g. Astronaut Personal Satellite Assistant -PSA)• Intelligent Fault-Tolerant Embedded Systems• Power Conversion (e.g. DC-DC converters)• Fishery & Irrigation System Management, Sustainable Systems

A Message• Modeling and Simulation is used

everywhere!

• You don’t build a – 787 Dreamliner

– Pentium Chip

– F22 Raptor, Joint Strike Fighter, etc…

– Space Shuttle

without investing a few

billion in M&S!

Modeling and Simulation is just getting started!

The Age of Intelligent Systems is Upon Us!

New Technologies are Coming!

• New Propulsion Technologies

• Smart Materials and Structures

• Miniature Electromechanical Systems (MEMs), Nanotechnology, Spintronics

• Optical and Biological Computing Machines

• Distributed Computation

• New Sensor and Actuation Technologies

• Regenerative and Personalized Medicine

Intel

• Chandler, AZ

• Allocation of Resources within a Reentrant Semiconductor Manufacturing Line (e.g. Pentium Fab)

• Maximize $$ in presence of machine/customer/process uncertainty

• Minimize average throughput time

– make promises

• Minimize variance of throughput time

– keep promises

Molecular Beam Epitaxy (MBE)

• ASU

• Method for depositing single crystals

• Source material heated to produce evaporated beam of particles - travel through ultra-high vacuum onto substrate

• Slow deposition rate ~1000 nm/hr

• Used for growing III-V semi crystals

• Thin filmed semiconductor materials

• Control thickness – single layer of atoms

Thermal Management ofMulti-Core Processors

• Intel

• Maximize performance per watt

• Dynamic voltage and frequency scaling (DVFS)

– Increase voltage or frequency (CPU throttling) to increase performance

– In progress

Hypersonic Vehicle Design

• NASA Ames, Langley, Glenn

• Mach 5-15

• unstable, aero-thermo-elastic-propulsive, nonlinear coupling/dynamics

• Two-stage-to-orbit (TSTO) vision

Honeywell Transport Systems

• Glendale, AZ

• High Speed Civil Transport (HSCT)

• Mach 2.2, 300+ passengers

• Automatic Landing System

• Issues:

– Long, thin, flexible

Integrated Real-Time Health Monitoring, Modeling, and Controls for Future NASA Missions

• Next generation general “avionics” (C4) box for

– Crew exploration vehicle

– Rovers

– Astronaut life support

Integrated Real-Time Health Monitoring, Modeling, and Controls for Future NASA Missions

• Partners

– NASA Ames, JPL, Kennedy Space Center

– Rockwell, Nuvation

– Carnegie Mellon, Iowa State

• Fault Tolerance– 3 Levels:

1. Chip level - Reconfigurable fault-tolerant hardware (FPGAs)

2. Board level 3. System/Actuator/Sensor level

NASA’s Astronaut Personal Satellite Assistant (PSA)• NASA Ames

• Designed to hover around spacecraft

• Accelerometers, gyros, Video, infrared

• Monitors critical parameters/signals (e.g. air temperature and composition, supplies) ; detect structural/tile flaws

• Assists astronauts with day-to-day tasks, reduce work load, communicates with Mission Control

NASA Jupiter Icy Moons Orbiter (JIMO)• Explore 3 planet-sized moons of Jupiter - Callisto, Ganymede and Europa

– May harbor vast oceans beneath icy surfaces; Date: 2015 or later???

– Galileo spacecraft found evidence that Jupiter's large icy moons appear to have 3 ingredients considered essential for life:

• water, energy, other essential chemical contents

– Evidence suggests melted water on Europa in contact with surface (geologically recent times); might still lie close to surface

• Issues:– Significant mass changes– Flexible structure– Nuclear reactor– Precision pointing

Honeywell Satellite Systems• Glendale, AZ

• Space Integrated Controls Experiment (SPICE)

• Laser Beam Expander (Missile Defense)

• Space Telescope

• Control System Design

– Rapid Slewing and Precision Pointing of Flexible Structrure

Raytheon Missile Systems

• Beford, MA

• Patriot Missile Autopliot Design

• Surface to Air Missile (SAM)

• Skid to turn (STT) Missile

Eglin AFB• Pensacola, FL

• Extended Medium Range Air-to-Air Technology (EMRAAT) Missile Autopilot Design

• Focus on control saturation prevention strategies during endgame

• Missile Defense Systems are Here!

Secret Security Clearance Required

Sikorsky Aircraft

• UH-60 Blackhawk Helicopter Flight Control System Design

• AFCS Design for a Twin Lift Helicopter System (TLHS)

• Sponsors: DOD, Sikorsky, MIT/Princeton

NASA, NSF, Bell Labs

Helicopters: Open Loop Unstable

Data: UH-60A Blackhawk Near Hover

Helicopter Instability:Unstable Backflapping Mode

Twin Lift Helicopter System

Boeing Space and Defense Systems

• Seattle, WA

• Boeing A.D. Welliver Fellowship

- Battle Management

M&S of Two Major Regional Conflicts (MRCs)

Command, Control, Communications (C3)

- Joint Strike Fighter (F-35)

- Unmanned Aerial Vehicles (UAVs)

Tilt-Wing Rotorcraft• Cruises like airplane; Hovers like helicopter

• High-speed Autonomous Rotorcraft Vehicle (HARVEE)

• With Professor Valana Wells (MAE)

Laboratory Test Bed for Hover

Hover Test Bed:Open Loop Pitch & Yaw Test

FAME @ ASU• ROVER (EE/MAE)

– Autonomous Vehicle– Real Time Vision System– On board Pentium Class CPU– Wireless Communication– Suite of Networked Stations (Brain)– search, rescue, reconnaissance, exploration, etc.

FAME @ ASU• ARVID - Robotic Projector

– Track Performers

• 2 DOF Pointing Systems

• Mechanical Bull

• Interactive Media and

Protoyping (IMaP) Laboratory

• Collaboration between EE and Institute for Studies in the Arts (ISA)

Low Power DC-DC Converters• Regulates voltage in presence of line voltage variations and

load variations

• Issues

– high frequency operation – excessive power consumption, sensitivity to finite word length arithmetic

– low frequency operation – lower power consumption, considerable phase lag within loop, design is hard

• Developed direct digital design methodology which takes into account sampled-data nature of problem

• Patent pending

• With Professor David Allee (ASU, EE)

Fishery Management

• World fisheries are over exploited

• Gordon-Schaefer bioeconomic models (Clark, 1970)

• Maximize profit subject to fish biomass constraint

• Maximize fish biomass subject to economic constraint

• Need effective regulatory policies; e.g. taxes, quotas, etc.

• Design of Robust Policies for Uncertain Natural Resource Systems: Application to Classic Gordon-Schaefer Model http://www.intechopen.com/articles/show/title/design-of-robust-policies-for-uncertain-natural-resource-systems-application-to-the-classic-gordon-s/

• Partners: Jeff Dickeson (PhD student)

Marty Anderies (School of Sustainability)

Marco Jansen (School of Sustainability)

Elinor Ostrom (Nobel Prize in Economics, 2009)

Irrigation SystemManagement

• Best Paper Award

Robustness, vulnerability, and adaptive capacity in small-scale social-ecological systems: The Pumpa Irrigation System in Nepal

http://www.ecologyandsociety.org/vol15/iss3/art39/

• Partners: Oguzhan Cifdaloz (former PhD student, Post Doc)

Ashok Regmi (Post Doc)

Marty Anderies (School of Sustainability)

Portfolio Management• Financial Engineering

• Maximize return subject to risk constraint

• Minimize risk subject to minimum return constraint

• Diversification

• Asset/sector allocation based on national/global macro-economic models

Summary

• You MUST get a PhD

• You MUST Become A Professor !

…the Nation needs you

…You will have lots of fun!

… There is so much to do!

Visit: http://aar.faculty.asu.edu/lapdp.html

THANK YOU VERY MUCH !

Result 1 • Problem Solved

– Given an plant P (possibly infinite-dimensional) described by a linear time invariant (LTI) model, how can we approximate it by a finite-dimensional model Pn to ensure that the resulting optimization-based control design Kn stabilizes P and meets an apriori performance tolerance?

• Solution based on convexification of the problem; can exploit convex optimization (e.g. polynomial-time interior point algorithms)

• Applications: Semiconductor processes, flexible structures, aerospace

Result 2

• Problem Solved

– Given a controller K which offers acceptable global performance for external commands, disturbances, and sensor noise, how can we modify it to accommodate actuator control limits and other hard limits?

• Solution exploits ideas from the theory of non-differentiable Lyapunov functions

• Applications: Aircraft, spacecraft, missiles, robotic systems