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Robotics, Autonomous Systems, and Control - CSM Capabilities

Kevin L. MooreG.A. Dobelman Distinguished Chair and Professor of Engineering Director, Center for Automation, Robotics, and Distributed IntelligenceDivision of EngineeringColorado School of MinesGolden, Colorado


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Outline

  • Introduction

  • Robotics

  • Other Control-Related Research

  • Sensor Networks

  • Renewable Energy-Related Control Research


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  • CARDI

  • 14 faculty, interdisciplinary

  • Electrical, Mechanical, Civil

  • Computer Science, Math

  • Bio-medicine, Bio-mechanics

Colorado School

of Mines

Located in Golden, Colorado, USA

10 miles West of Denver

CSM sits in the foothills of the Rocky Mountains

  • CSM has about 300 faculty and 4000 students

  • CSM is a public research institution devoted to engineering and applied science, especially:

    • Discovery and recovery of resources

    • Conversion of resources to materials and energy

    • Utilization in advanced processes and products

    • Economic and social systems necessary to ensure

    • prudent and provident use of resources in a

    • sustainable global society


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Degrees at CSM

(Grad and Undergrad)

  • Chemistry

  • Chemical Eng

  • Economics/Business

  • Engineering

  • Environmental Science/Eng

  • Geochemistry

  • Geology and Geological Eng

  • Geophysics and Geophysical Eng

  • Math/Computer Science

  • Material Science

  • Mining and Earth Systems Eng

  • Metallurgical and Materials Eng

  • Petroleum Engineering

  • Physics


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CSM Engineering Division

  • B.S. in Engineering with Specialties in

    • Civil

    • Electrical

    • Environmental

    • Mechanical

  • M.S/Ph.D. in Engineering Systems

    • Civil

    • Electrical

    • Environmental

    • Mechanical

  • Bioengineering and Life Sciences Minor

    • Includes biomedical engineering, biophysics

    • Pre-Medical & Life Sciences

  • 5-year Programs (BS+MS)

    • Engineering Physics

    • Engineering Systems

    • Environmental Science

  • Humanitarian Engineering Minor

    • The application of math, science, and engineering to improve the wellbeing of under-served populations


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CSM Research (Control-Oriented view)

  • Materials

    • Nuclear

    • Welding

  • Energy

    • “Traditional” (e.g., Petroleum Institute)

    • Combustion

    • Renewable

      • Colorado Fuel Cell Center

      • Power Electronics for Hybrid Renewable System

      • Solar (PV materials, thermal, systems)

      • Wind

  • Center for Space Resources

    • Insitu resource utilization

    • Lunar, Martian exploration

  • Geo-Sciences/Mining

  • Environmental Sciences/Hydrology

  • “Intelligent” Geosystems

  • EE and CARDI Activities


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Power

Systems

Signal and Image Processing

Renewable Energy

Power

Electronics

Robotics

Control Systems

Humanitarian Engineering

EE Research Areas and Applications

Wireless

Communications


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EE Research Areas and CSM’s Mission

  • Robotic welding

  • Welding process control

  • Control of plasma processes

  • PV manufacturing process control

  • EARTH’S REOURCES

    • Discovery and

    • recovery

  • MATERIALS

    • Utilization in advanced

    • processes and products

  • Robotics for mining

  • - Image processing

  • Mine safety

  • - Control systems

  • - Sensor networks

  • ENERGY

    • Generation, conversion, and distribution

  • Power transmission and distribution

  • Renewable energy

  • - Wind power

  • - Fuel cell control

  • - Hybrid power system coordination

  • ENVIRONMENT

    • Economic and social systems necessary to ensure prudent and provident use of resources in a sustainable global society

  • Humanitarian engineering

  • Robotics for security applications

  • Biomedical engineering

  • - Image processing


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Center for Robotics, Automation, and Distributed Intelligence (CARDI)

  • CSM research center focused on

    • Control systems, robotics, sensing (especially vision) and communication networks, machine learning and intelligence, ad hoc mobile networks, sensor networks

  • Applications to problems of concern at CSM, including:

    • Environment, energy, natural resources, materials, transportation, structures, geotechnical, information, communications, networking, medicine, and data mining

  • Problems requiring multi-disciplinary systems approach to integrate technologies from the different disciplines

    • 14 faculty

    • Electrical, mechanical, civil, computer science, mathematics


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Biomedical Intelligence (CARDI)

Environment

3D Stereo Mapping

Medical Imaging

Sensor Networks

Control

Stereo-Vision for Welding Automation

Wind Turbine Control

Reconfigurable Wireless Nodes

Activity Identification

Data Mining

Automation

Distributed Intelligence

CARDI Research Areas and Applications

Robotics

Mobile Ad-hoc Networks

Communications

Control of Plasma Processes

Manufacturing


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CSM Control Systems-Related Research Intelligence (CARDI)

  • CSM EE/ME/CE/CARDI faculty conduct both theoretical and applied research in control systems:

    • Fault detection and identification (Vincent)

    • Control of material processing (Moore, Vincent)

    • Autonomous systems and robot control (mobile, arms, and mobile arms) (Moore, Steele, Vincent, Hoff)

    • Coordinated control for robotics and UAVs (Moore)

    • Vision-based navigation and control (Moore, Vincent, Hoff)

    • Augmented reality (Hoff, Vincent)

    • Intelligent sensing for geo-systems applications (Mooney)

    • Sensor networks (Moore, Weiss, Colagrosso)

    • Welding control (Hoff, Moore, Steele, Vincent)

    • Learning control, intelligent control (Moore, Simoes)

    • Adaptive control (Johnson)

    • Wind energy applications (Johnson)

    • Distributed coordination/control of renewable energy (Johnson, Simoes)

    • Power electronics for hybrid energy control (Simoes)

    • Fuel cell system controllers (Moore, Simoes)

    • System engineering (Moore, Steele)


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Outline Intelligence (CARDI)

  • Introduction

  • Robotics

  • Other Control-Related Research

  • Sensor Networks

  • Renewable Energy-Related Control Research


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CSM Robotics Intelligence (CARDI)

  • CSM has a long legacy of robotics-related activity

  • CSM faculty and staff have significant robotics-related expertise

    • Mechanism Design

    • Robotic Manipulators

    • Mobile Robots

    • Cooperative robotics

    • UAVs

    • Vision-based robotics; Augmented reality

    • User Interfaces

    • System engineering

    • Applications: mining and lunar exploration

    • Commercialization


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Martin Marietta BatMobile Intelligence (CARDI)

NASA Contest

SAE Walking Machine

NSF REU Arm

CSM Robots

Concept design for

In-situ resource

utilization


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Weederbot III Intelligence (CARDI)

2005 Senior Design 2006

(supervised by John Steele)

Autonomous Mower Project


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  • Based on the Intelligence (CARDI)

    ODIS Platform

    used in theatre

Mobile Manipulators (Mobile ARMS)

  • Human-robot interaction

  • Autonomous Pick-and-Place

  • Visual Servoing


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3D Models for Navigation and Manipulation Intelligence (CARDI)

Robotics can be used to automate load/haul/dump vehicles

Automation of Load/Haul/Dump

• Remove miners from operating area

Stereo vision is used for

• Guidance

• Map building

• Collision avoidance

50m Long Mine Model

(green from laser ranger, yellow from stereo)

Faculty: Steele and Vincent


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Autonomous Robots built by Kevin Moore’s Team at Utah State

T1 -1998

ODIS I -2000

T2 -1998

T4 -2003

T3 -1999

(Hydraulic drive/steer)


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Autonomous Tractors and Unique Mobility Robots built by Kevin Moore’s Team at Utah State

Automated Tractor Projects(CSOIS Spin-Off, Autonomous Solutions, Inc.)

Unique Mobility Robots


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“Putting Robots in Harm’s Way So People Aren’t” Kevin Moore’s Team at Utah State

ODIS – the Omni-Directional Inspection System

An ODV Application: Physical Security


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From Intelligent Behavior to Kevin Moore’s Team at Utah StateCooperative Autonomy…

  • Seek a single machine that can do both of the following tasks via semantic (verbal) instruction from a (human) supervisor:

Load a trailer

Cooperatively weld a pipe

  • Humans can do this!

  • How do we make a group of robots that can also do this?


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Mote-Based Distributed Robots Kevin Moore’s Team at Utah State

Prototype

plume-tracking

testbed developed

by Moore at USU

Robotic wireless networks for remote video streaming - Weiss


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Wireless 802.11g Video Streaming through a Robot MANET Kevin Moore’s Team at Utah State

Laptop and Starting Position

Robot Monitoring Software on Laptop

(video feed from lead robot on upper right)

Stopping positions of robots

(blue dots)

Lead Robot with Video Camera

Faculty: Weiss


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Outline Kevin Moore’s Team at Utah State

  • Introduction

  • Robotics

  • Other Control-Related Research

  • Sensor Networks

  • Renewable Energy-Related Control Research


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Other Control-Related Research Kevin Moore’s Team at Utah State

  • Faculty conduct both theoretical and applied research in areas related to robotics and control systems:

    • Welding Control (Moore, Vincent, Steele)

    • Material Processing (Moore, Vincent)

    • Intelligent Sensing and Control (Mooney, Steele)

    • Computer Vision (Hoff, Vincent)

    • Wireless system design (Weiss)

    • Sensor networks (Colagrosso, Moore, Weiss)


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Robotic Welding Kevin Moore’s Team at Utah State

Rectified Stereo Image Pair

Faculty: Steele, Vincent, and Hoff

Derived surface of weld pool


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Welding Control and Control of Material Processing Kevin Moore’s Team at Utah State

  • Control of Materials Processing

    • Foundry Cupola

    • Gas Metal Arc Welding

    • PV Material Manufacturing


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Smart Bit Technology: Force Sensing for Manipulation (Steele)

Sensory Goals

  • In-Situ measurements

  • Bit wear indicator

  • Horizon detection

  • Performance indicators

  • Improve Mind-Machine link

(20-mile Longwall)

  • Equipment Application

  • Radial borers

  • Continuous miners

  • Longwall shearers

(Continuous Miner)


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Mike Mooney (Steele)

Intelligent Soil Compaction

(funded by NSF & NCHRP)

Forward

accelerometer

eccentric

V = 2-4 m/s

200-300 mm soil

Layers of previously compacted soil; possible near surface bedrock

Objectives:(1) Develop the relationships between vibration properties of roller compactor and underlying soil properties relevant to design

(2) Improve our understanding of how feedback control might improve soil compaction

(3) Improving parameter estimation via geolocation data, multiple passes, etc.


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Current Trial's (Steele)

Input

Current Trial's

Output

Plant

Next Trial's

Input

Iterative

Learning

Controller

Desired

Output

Iterative Learning Control (Moore)

  • Paradigm for systems that operate repetitively


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Iterative Learning Control Applications (Steele)

  • Iterative Learning Control

    • Paradigm for controlling systems that repeat the same operation over and over

  • New applications

    • Develop new approach called multi-pass ILC

    • Vision-based ILC (also for multi-pass problems)

    • nD ILC (e.g., irrigation control)


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Vision/User Interface; Augmented Reality (Steele)(Hoff)

A system to recognize gestures, for the purpose of robot control

Constructing scene models from stereo vision

Augmented reality system developed at CSM

Registration of range data


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Activity Identification and Visualization (Hoff) (Steele)

Problem: Detect and identify unusual or suspicious activities in surveillance data

Cars and bicycles are labeled green and yellow

Statistical measures (eg, chi-square) signal how unusual a track is from the rest of the scene, and compare two scenes

Interactive visualization tools enable analyst to pick salient features for machine learning

Person handing out flyers is labeled red

Faculty: Hoff and Lee


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Outline (Steele)

  • Introduction

  • Robotics

  • Other Control-Related Research

  • Sensor Networks

  • Renewable Energy-Related Control Research


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Research in telecommunications focuses on mobile computing and networking

  • Research areas:

    • How to connect mobile computers (laptops, palmtops, etc) to the Internet

    • How to create ad hoc networks on demand

      • one unit may be connected to some wired network

      • how to create and maintain network connectivity

      • previous infrastructure is demolished or non-existent

    • Quality of service

Faculty: Camp, Navidi, Colagrosso, Liu



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Legend and networking: Flows of people, material Flow of information

Flows of air Fixed radio node

Toxic gas Mobile radio node

Autonomously Reconfigurable Systems

  • Consider an underground mine


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Legend and networking: Flows of people, material Flow of information

Flows of air Fixed radio node

Toxic gas Mobile radio node

Add sensors and flows of people, material, and air


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Legend and networking: Flows of people, material Flow of information

Flows of air Fixed radio node

Toxic gas Mobile radio node

Suppose a hazardous gas develops


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Legend and networking: Flows of people, material Flow of information

Flows of air Fixed radio node

Toxic gas Mobile radio node

The system should autonomously-reconfigure to redirect flows of people, material, and air


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Sensor node and networking

VDSL node

Phone cable

See live demo at

http://ore.mines.edu/~mcolagro/edgarmine/


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Outline and networking

  • Introduction

  • Robotics

  • Other Control-Related Research

  • Sensor Networks

  • Renewable Energy-Related Control Research


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Control-Related Energy Research at CSM and networking

  • The Electrical Engineering group at CSM is involved in three main areas of electrical energy research

    • Distribution and transmission

    • Control and coordination

    • Power electronics

  • Other faculty in the Engineering Division and other CSM departments are also involved in electrical energy generation research.


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The future of electrical energy and networking

  • Energy will be introduced to the grid from a variety of sources

  • Distributed generation with non-traditional resources is less predictable and more difficult to control

  • Could eventually see emergence of the “smart grid” or “Enernet” (energy network)

Figure courtesy of Ben Kroposki (National Renewable Energy Laboratory), and Janet Ginsburg (“Reinventing the Power Grid” in Business Week, February 26, 2001 pp.106-107).


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CSM Electrical Faculty Energy Research Interests and networking

  • A key factor for clean, efficient energy is management and control

  • Specific CSM EE area of interests include:

    • Control of distributed and conventional generation sources and associated manufacturing processes

      • Turbine control in wind; balance-of-plant control in fuel cells; combined thermal/power management systems in concentrating solar power; PV manufacturing

    • Control of power flow in hybrid energy systems

      • Coordination of turbines in a wind farm; “smart” inverters/converters

    • Control of power flow into and out of the grid

      • Anti-islanding/ prevention of cascading failures/“robust grid”; power quality/reliability; grid synchronization

    • Economically-driven grid/resource management

      • “Smart grid”; “Ener-net” = Energy + Network


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Photovoltaic Solar Collector Field and networking

The “Grid”

PV Field

Sensor Network

and Controller

Switching/Inverter

Substation & Power Conditioning

Thermal Solar Energy

Collector Field

Auxiliary

Storage

Power Plant

(Steam or Direct-to-H2)

Integrated Roof w/

Thermal/PV Solar Energy

Load

Balancing

Fuel Cells

SCADA System

Smart Data Bus

Wind and Other Non-Solar

Renewable Energy Generation

.

.

.

.

.

.

Control Room


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Photovoltaic Solar Collector Field and networking

Fuel Cells

Wind and Other Non-Solar

Renewable Energy Generation

.

.

.

.

.

.

  • PV Manufacturing

    • Tyrone Vincent

    • Bob Kee

  • Fuel Cell Control

    • Marcelo Simoes

    • Kevin Moore

  • Wind Turbine/Wind Farm Control

    • Katie Johnson

    • Marcelo Simoes

    • Kevin Moore


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  • Auxiliary Units-to-Substation Transmission

    • P.K. Sen

    • Sid Suryanarayanan


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Switching/Inverter and networking

Substation & Power Conditioning

.

.

.

.

.

.

  • Microgrids

    • Marcelo Simoes

    • Sid Suryanarayanan

  • Inverter Power Electronics

    • Marcelo Simoes

Auxiliary

Storage

  • Auxiliary Storage/Load Balancing/Coordination

    • Marcelo Simoes

    • Katie Johnson

    • P.K. Sen

    • Kevin Moore

Load

Balancing


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PV Field and networking

Sensor Network

and Controller

SCADA System

Smart Data Bus

  • Instrumentation and Control: Smart Grids

    • Marcelo Simoes

    • Kathryn Johnson

    • Kevin Moore

    • Tyrone Vincent

    • P.K. Sen

    • Sid Suryanarayanan


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Control applications in PV materials processing (Vincent, Kee)

We have worked with major PV suppliers

• ITN Energy Systems (Littleton, CO)

• Global Solar (Tucson, AZ)

• First Solar (Perrysburg, OH)

• Ascent Solar (Littleton, CO)

• PrimeStar Solar (Golden)

Thin film technologies

• Copper-indium-gallium-diselenide (ITN, Global, Ascent)

• Cadmium-telluride (First Solar, PrimeStar)

Modeling and design capabilities

• Thermal systems

• Chemically reacting flow

• Model-based process control


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Theoretical Basis: Structured Nonlinear System Identification

  • Goal: Identification of components in an interconnected system


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First-Solar’s CdTe process is based on a particle-injection CVD process

Glass substrate


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Modeling and simulation support design and control enhancement of the CIGS process

Plume models

• Direct Simulation Monte Carlo

• Beam shape on web

• Haystacking near nozzles

Transition flow models

• Gas dynamics in nozzles

• Propensity for spit formation

Melt-pool convection

• Buoyancy and surface-tension

• Flow instabilities

Thermal models

• Three-dimensional finite element

• Conduction and radiation

Control strategies

• Model-based control


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Identification and modeling play an important role in developing advanced control architectures


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Turbine Model developing advanced control architectures

Wind Input

Adaptive Controller

Hybrid Power Control for Renewable Energy ( Kathryn Johnson)

  • Wind turbine optimization and control

    • adaptive controller validated both in simulation and field tests

    • annual increase in energy of more than 5%

  • Control of hybrid renewable energy systems

    • solar

    • wind

    • fuel cells

    • batteries

    • hydrogen


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Adaptive Torque Control of Variable Speed Wind Turbines developing advanced control architectures

  • Turbine is stopped when wind is too slow or too fast.

  • Turbine power is limited in moderately high winds.

  • Adaptive control can increase turbine power in lower wind speeds.

Energy capture can be increased by 5 – 6%, leading to a similar decrease in cost of wind energy.

Faculty: Johnson


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Non-trivial interconnection to the distribution grid developing advanced control architectures

Must be fault-tolerant and refrain from contributing to grid faults

Multiple control levels


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Models of Grid and Grid Interconnection, possibly with SCADA Hardware-in-the-Loop using RTDS Dedicated Simulation System

Hardware-in-the-loop

Models of Turbines, Substation and Power Electronics, Storage and Voltage Control, and Control Systems Simulated using Power-Industry Standard Software such as PSCAD and MATLAB

CFD Models of Turbine Blades Simulated for

Realistic Wind Velocity Flow Fields using

Golden Energy Computing Organization’s 10+ teraflop Linux cluster

Grid

Multi-Resolution

Wind Farm

Simulator

Wind Farm

Substation

Storage

Load

SCADA/

Power Electronics


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Power Electronics and Control (Marcelo Simoes) Hardware-in-the-Loop

Research Theme: Intelligent Control for Energy Conversion and Interconnection of Renewable Energy Systems

  • Power electronics for efficient energy conversion

  • Intelligent control as applied to energy conversion

  • Modeling and control of microgrids

  • Methods and systems for maximum photovoltaic energy capturing and conditioning

  • Wind turbine variable speed systems

  • Energy storage for renewable energy conditioning

  • Hybrid renewable energy systems

  • Fault tolerant systems for interconnection of renewable energy to the grid


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Transient Storage Compensation of Fuel Cells Response with BatteriesBi-Directional Power Converter:

M. Michon, J.L. Duarte, M. Hendrix and M. Godoy Simões, “A three-port bi-directional converter for hybrid fuel cell systems” 35th IEEE Power Electronics Specialists Conference (PESC), Aachen, Germany, June 20-25, 2004


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Coordinated Balance-of-Plant/ Hybrid Power System Components Control for Fuel-Cell Based Systems

  • Typical application treats the fuel cell, auxiliary components, and load separately:


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Coordinated Balance-of-Plant/ Hybrid Power System Components Control for Fuel-Cell Based Systems

  • Bi-Directional power converter enables coordinated approach:


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Every home Control for Fuel-Cell Based Systems

a micro-grid

Fuel Cell

Fuel Cell

Fuel Cell

Fuel Cell

Fuel Cell

Fuel Cell

Fuel Cell

Fuel Cell

Wind

Wind

Wind

Wind

Wind

Wind

Wind

Wind

Solar

Solar

Solar

Solar

Solar

Solar

Solar

Solar

Power

Gas Gen

Gas Gen

Gas Gen

Gas Gen

Gas Gen

Gas Gen

Gas Gen

Gas Gen

Storage

Storage

Storage

Storage

Storage

Storage

Storage

Storage

Data

Toward the “EnerNet” of the Future

Today’s grid evolves to a large(r)-scale (than today) complex adaptive system

Central

Generation

Cooperative

Generation

Central

Generation


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Credit: Control for Fuel-Cell Based SystemsDamon Dougherty – Industry Manager, Intergraph


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Outline Control for Fuel-Cell Based Systems

  • Introduction

  • Robotics

  • Other Control-Related Research

  • Sensor Networks

  • Renewable Energy-Related Control Research


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New Directions -1 Control for Fuel-Cell Based Systems

Robotic Material Handling and Processes in Mining Applications

  • Processes Characterized by Force Interaction Between Actuators and Materials

  • Automated load-haul-dump (LHD) vehicles

  • Automated shoveling in open-pit mining

  • Downstream operations that are dirty, difficult, dull, or dangerous

    • Material loading to/from rail cars

    • Robotic search and rescue

      • Rubble clearing

      • Airhole boring

Automated LHD system developed at CSM

Robotic Applications in Oil and Gas

  • Robotic roustabout

  • Automated maintenance of oil derricks


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New Directions -2 Control for Fuel-Cell Based Systems

Robotic Welding Systems

  • Mobile (or portable) robotic welding systems

    • Service and repair industry focus

    • Shipbuilding and construction

  • On-line fault detection and diagnostics

  • Focus on infrastucture applications

    • Outdoors

    • Hazardous

    • Heavy industry

  • Robotic pipefitting applications

Robotic welding system at CSM


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New Directions -3 Control for Fuel-Cell Based Systems

Mobile manipulation and mobile robots integrated with building automation infrastructure and other data bases

  • Medical facility and security applications

  • Virtual presense for quarantined patients (idea from National Institues for Medical Infomatics Media Lab (http://www.imedi.org/docs/references/mr.htm)

    • Sterilizing floors (an enhanced Roomba)

    • Delivering lab specimens (like the little robots zipping around the DeathStar in Star Wars)

    • Pulling patients on stretchers to rooms

    • Performing perfect CPR

    • Performing basic aspects of the physical exam (looking at pupils, listening to lungs and heart)

    • Etc.

  • Patient manipulation: RIMAN Robot (Japan)


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Interrogation and characterization of injury Control for Fuel-Cell Based Systems

Therapeutic program specification for rehabilitation robot

New Directions -4

Patient-specific rehabilitation and therapeutic robotics

Model-based patient-specific therapy prescription

Patient specific model


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