My Research Experiences: From IIT to ISU

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My Research Experiences From IIT to ISU

• D. Subbaram Naidu, PhD, PE, Fellow IEEE
• Professor, Electrical Engineering
• Director, Measurement and Control Engineering
  Research Center (MCERC)
• Associate Dean, College of Engineering
• Idaho State University
• Pocatello, ID, USA
• http//www.isu.edu/naiduds

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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, USA
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• Universities of South Western Australia

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Where is Idaho State Univ. and Idaho?
DesinenISUbbaram NaIDu
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Idaho State University Facts Sheet

• Idaho State University (ISU) was founded in 1901
• Now ISU has 7 Colleges
• Arts Sciences Business Education
  Engineering Health Professions Pharmacy
  Technology
• ISU campuses in Pocatello, Idaho Falls (CHE),
  Boise, Twin Falls
• ISU has over 13,500 students (including 3,000 at
  IF CHE Campus)
• 10 Research Centers
• Center for Ecological Research and Education
• Center for Archeological Materials and Applied
  Spectroscopy
• Family Medicine Clinical Research Center
• GIS Teaching and Research Center
• Idaho Accelerator Center
• Informatics Research Institute
• Institute of Rural Health (IRH)
• Institute of Nuclear Science Engineering (INSE)
  
• ISU Biomedical Research Institute (IBRI)
• Measurement Control Engineering Research Center
  (MCERC)

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ISU College of Engineering

• 1902 Two of the first four graduates of the
  Academy of Idaho "Civil Engineers"
• 1964 BS in Engineering and MS in Nuclear Sci.
  Engr
• 1968 College of Engineering was established
• 1989 MS in Measurement and Control Engr.
• 1993 Measurement Control Engr. Research Center
  one of the 4 at ISU recognized by SBOE
• Now ISU Engineering has
• 5 BS programs in CE, CS, EE, ME, NE ABET
  accredited
• 1 Post BS Certificate program in Applied Nuclear
  Energy
• 6 MS programs in CE, ENVE, ESM, MCE, ME, NE
• 2 PhD programs in Nuclear Sci. Engr (NSE) and
• Engr. Appl. Science (EAS)

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Biography

• Born in Seshapuram, near Tirupati, India
  farmers family
• PhD, Indian Institute of Technology (IIT),
  Kharagpur (1977)
• NASA Langley Research Center, Hampton, VA
  (1985-90)
• Idaho State University, USA (1990-present)
• US Air Force Research Laboratory, WPAFB, OH
  (1998-99)
• Norwegian University of Science and Technology
  (1994)
• Swiss Federal Institute of Technology (ETH),
  Zurich (1995)
• Nantong University, Nantong, China (2007)
• University of Western Australia, Perth (Spring
  2008)
• University of South Australia, Adelaide (Spring
  2008)
• Publications Over 200 including 5 books
• Fellow IEEE USA (1995)

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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, USA
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• Universities of South Western Australia

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20th Century's Greatest Engineering Achievements
13 of them belong to IEEE (1,5,6,8,9,10,12,13,14,
15,16,18,19)
9
21st Century - Globalization

• Before Earth was round and World was round
• Now Earth is still round,
• but World is flat
• Death of Distance brought by Internet -
  Equalization of Field

April 2005
10
Globalization Who is Responsible?
Man of the Millennium
Johannes Gutenberg
Born _at_ 1400 Invented Printing led to
Information Technology (IT)
DARPA, the ARPANET Information Technology
Revolution
4-node ARPANET between UCLA, SRI, UCSB, U of U
The first 2 nodes on the ARPANET UCLA and SRI
Oct. 29, 1969
Defense Advanced Research Projects Agency (DARPA)
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China India - CHINDIA

• Chindia is a portmanteau that refers to China
  (Dragons) and India (Bengal Tigers) together in
  general, and their economies in particular
  Indian economist and politician Jairam Ramesh.
• China is a manufacturing technology country,
  and India is a knowledge or, Information
  technology country.
• Ref Aug. 22/29, 2005

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Hot, Flat, and Crowded

• Bring climate and energy issues to Main Street
• ET (Energy Technology)
• GT (Green Technology)

September 2008
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9/11/2001
9/11 Changed America and the World
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Actions in Four Broad Areas

• K-12 Science Mathematics Education
• Science Engineering Research
• Science Engineering Higher Education
• Incentives for Innovation

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Rising Above the Gathering Storm Two Years
Later Accelerating Progress Toward a Brighter
Economic Future - April 29, 2008

• America Creating Opportunities to Meaningfully
  Promote Excellence in Technology, Education, and
  Science Act, or the America COMPETES Act Aug.
  2007
• The America COMPETES Act authorized expenditures
  and programs in research and in education
• A number of significant events have taken place
  since the Gathering Storm report was released,
  said Norman Augustine (former Chairman of
  Lockheed-Martin), who chaired the committee that
  wrote the report. Unfortunately, most of those
  positive events have occurred in other
  countries.
• Anyone in the audience from the United States
  who says that the Chinese or Indians are not
  entrepreneurial, not creative, that they dont
  want to rival the United States in business
  startups, has not been to India or China, said
  Craig Barrett (Chairman, Intel)

The National Academies Washington DC, 2009
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Is America Falling Off the Flat Earth?Norman R.
Augustine The National Academies (2007)

• The Death of Distance How the Communications
  Revolution Will Change Our Lives -Frances
  Cairncross
• US needs to compete not within its borders but
  the world without borders highly motivated,
  well-educated and willing to work for a fraction
  of US salaries.

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Re-Engineering Engineering

• Other Nations will absorb routine engineering
  tasks
• Americas Engineers must be superbly trained,
  innovative and entrepreneurial.
• 21st Century needs cant be met with 4-year
  degree
• Increased emphasis on, and rewards for, teaching.
  Research is an important aspect of teaching, it
  is the balanced combination of teaching and
  research that has made Americas research
  universities great.
• You can always count on the Americans to do the
  right thing after they have tried everything
  else Winston Churchill (1874-1965)

Norman Augustine ASEE Prism Feb 2009
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Engineer of 2020

• Attributes needed for the graduates of 2020
• Strong analytical skills,
• Creativity (thinking out of the box),
• Ingenuity,
• Professionalism, and
• Leadership.
• Source Engineer of 2020, Nat. Acad. Press-2004

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Moores Law Transistors/Chip
Source Harbor Research, Inc., August 2008
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Network Devices In Everyday Life
Source Harbor Research, Inc., August 2008
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Any Thing On a Network Can Communicate With
Other Things Across Global Venues
Source Harbor Research, Inc., August 2008
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Global Device Networking Market Growth is
Exponential
Source Harbor Research, Inc., August 2008
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Revolutionary Forces
Basic Advancements in Science Technology Come
About Twice a Century and Lead to Massive Wealth
Creation - about 30 years for a new technology to
gain wide acceptance, lasting additional 60
years.
Source Normal Poire, Merrill Lynch in Red
Herring, page 76, May 2002
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Basis for Presentation
1985
1987
2/E
1994
2003
2003
2010
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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, USA
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• Universities of South Western Australia

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Research at IIT-KGP

• Singular Perturbations and Time Scales (SPaTS)
  in Control Theory and Applications
• Continuous Systems Naidu, PhD (IIT, 1977)
• Discrete Systems Rao, PhD (IIT, 1982)
• Applications of SPaTS to ecology biology
• Publications 2 books and several journal
  articles

1985
1987
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Order Reduction Techniques

• Order reduction is important for on-line
  implementation and to get physical feel for
  solutions.
• Several techniques just discard certain order
  without using any info from the discarded system.
• These create problems if discarded dynamics and
  bound. cond. are important.
• SPaTS does use the neglected dynamics and
  satisfies fully the bound. Conditions.

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Singular Perturbations

• Control theory Modeling, Analysis and Design
  (MAD)
• Most physical systems are of high order
• A system where neglecting a small parameter
  changes the order of the system
• Small parameter e is often mass, moment of
  inertia, time constant, stiffness, inductance,
  Mach number, Reynolds number

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Boundary Layer

• Rapid variation of solutions
• Boundary layer
• Loss of one (x0) of the boundary conditions

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Slow and Fast Time Scales

• The system has widely separated eigenvalues
• Contributes to slow and fast phenomena
• Numerical difficulties

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SPaTS State Space Form
Original System
Degenerate System
e?0
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SPaTS Degenerate System

• Degeneration (process of e 0) reduces the
  system order.
• Some of the boundary conditions are lost and
  hence cannot satisfy all the boundary conditions
  of the original system.
• Need for improvement to take care of the lost
  boundary conditions the low order solution.
• Many use this system for analysis design, but
  not a sing. pert. technique.

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SPaTS Basic Features

• Boundary layer
• Slow and fast dynamics
• Numerical stiffness
• Degenerate solution close to original solution
• Tichnov Theorem
• Loss of bound. cond.

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SPaTS Methodology

• Since some bound. cond. are buried in the
  boundary layer (near t0 or tf), it is logical to
  dig out that layer by stretching it.

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SPaTS Methodology-Cont.

• Use a perturbation method
• Theorem for asymptotic series expansion

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SPaTS Methodology cont2.

• Slow solution x(0)(t) requires no correction
• Degenerate solution z(0)(t) requires stable
  boundary layer correction with initial value z(0)
  z(0)(0) to resurrect the lost boundary
  condition z(0).
• Zeroth-order solution

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SPaTS Methodology Implementation

• For example, use a simple state feedback or
  optimal control
• Design feedback coefficients Ks and Kf separately
  for slow and fast subsystems

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SPaTS Features

• Original system is stiff and high order (HO)
• curse of dimensionality
• SPaTS decouples the HO system into low-order slow
  and fast subsystems
• order reduction and stiffness relief
• The SPaTS technique incorporates the neglected
  fast dynamics and recovers the lost boundary
  conditions.
• All control techniques are applied to low-order
  subsystems.

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Control Applications of SPaTS

• Continuous, Discrete, Unified Naidu et al.
• Deterministic Stochastic Naidu et al.
• Observers
• State feedback Naidu et al.
• Optimal Naidu et al.
• Adaptive
• Robust Naidu et al.
• Nonlinear Naidu et al.
• Intelligent Naidu et al., in progress

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Industrial Appl. of SPaTS

• Aerospace Naidu et al.
• Fluid Mechanics and Flight Mechanics
• Electrical circuits, power, etc. Naidu et al.
• Structures
• Robotics Naidu et al.
• Chemical Nuclear Naidu, et al.
• Soil Mechanics
• Oceanography
• Ecology Biology Naidu, et al.
• Etc.

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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, USA
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• Universities of South Western Australia

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Research at NASA Langley

• Order Reduction Singular Perturbations and Time
  Scales Continued
• SPaTS for Digital Flight Control Systems
• Aeroassisted (aerobraking) Orbital Transfer
  Vehicles
• Guidance and Control of Aerospace Vehicles
• D. S. Naidu, Aeroassisted Orbital Transfer
  Guidance and Control Strategies, Lecture Notes
  (Research Monograph) in Control and Information
  Sciences, Vol.188, Springer-Verlag, London, UK,
  1994.

1994
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AEROASSISTED ORBITAL TRANSFER
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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, OH, USA
• (The birth place of Aviation)
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• Universities of South Western Australia

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GUIDANCE AND CONTROL STRATEGIES FOR HYPERSONIC
VEHICLES

• D. Subbaram Naidu, PhD
• Idaho State University
• Pocatello, Idaho
• and
• Senior National Research Council Fellow
• Center of Excellence for Control Theory
• Air Force Research Laboratory
• Wright-Patterson Air Force Base, OH, USA
• 1998-99

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Research at AFRL

• Guidance and Control of Hypersonic Vehicles
• Resurrection of Hypersonics
• H2 and H8 Optimal Control
• Unified Approach
• Unmanned Combat Aerial Vehicles (UCAVs)

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GNC Configuration
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CFD Simulation of HYPER-X
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Hypersonic Vehicle X-33
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Vehicles Comparison
X-33
SHUTTLE
SSTO/RLV Target
285K LB 69 FT N/A N/A 2 XRS2200 AEROSPIKES
WEIGHT LENGTH PAYLOAD (100 NM) / 28.58) BAY
SIZE PROPULSION
2.6M LB 140 FT 55,000 LB 15 x 45 FT 8 RS2200
AEROSPIKES
4.5M LB 184 FT 51,000 LB 15 x 60 FT 3 SSME
2 SOLIDS
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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, OH, USA
• (The birth place of Aviation)
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• Universities of South Western Australia

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Advanced Control of Gas Metal Arc Welding (GMAW)
Mr. Robert Yender Mr. Justin Tyler, (MS ISU,
1997) Selahattin Ozcelik, PhD (Postdoc) And Facu
lty Advisors D. Subbaram Naidu, PhD Kevin L.
Moore, PhD
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Gas Metal Arc Welding Schematic
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Direct Model Reference Adaptive Control (DMRAC)
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GMAW Experimental Setup
2003
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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, OH, USA
• (The birth place of Aviation)
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• Universities of South Western Australia

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Measurement Control Engineering Research Center
(MCERC)

• Established in 1993
• Renovated Building in 2007 09 on 1030, 2nd St.
• Several Research Laboratories
• Measurement Control
• Wind Tunnel
• Structures
• Robotics
• Biomedical Engineering
• Alternate Energy Systems
• Other labs proposed Computer Science, and
  Infrastructure

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Measurement and Control?
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Research at MCERC

• Order Reduction Sing. Pert. Time Scales
  (SPaTS)
• Unified Approach to Optimal and SP systems
• Model Ref. Adaptive Control for Gas Metal Arc
  Welding
• Fusion of Soft and Hard Control for Uninhabited
  Combat Aerial Vehicles (UCAVs)
• Advanced Control Strategies for Heating,
  Ventilation and Air Conditioning (HVAC)
• Hybrid Control Strategies for Biomedical
  Engineering (BME)
• Advanced Control Strategies for Alternate Energy
  Systems

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Unified Approach for Optimal Control
Yoshiko Imura, (PhD Idaho State University
2007) and Faculty Advisor D. Subbaram Naidu,
PhD
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Research on Unified Approach for Optimal Control
- Basis

• Euler-Lagrange Equation, ACC, Denver, CO 2003
• Euler-Lagrange Equation.., Optimal Control
  Applications Methods, 25, pp 279293, Nov.
  2004
• Open-Loop Opt. Control, IFAC, St. Petersburg,
  2004
• Open-Loop Optimal Control, Optimal Control
  Applications Methods, 28, pp 59-75, March 2007
• Closed-Loop Optimal Control , IEEE Intl. Conf.
  on Control Aut., Guangzhou, CHINA, May-June,
  2007
• Closed-Loop Optimal Control , Intl. J. on Inf.
  and Systems Sciences (IJISS), Vol.1, pp 118,
  Jan. 2010

65
Introduction

• The continuous-time (CT) and discrete-time (DT)
  approaches, in spite of some similarities, are
  treated separately for control systems, in
  general.
• The open-loop formulation leads to a two-point,
  boundary value problem (TPBVP) in state and
  costate equations.
• The closed-loop formulation leads to matrix
  differential or algebraic Riccati equation.
• The unified approach provides a new methodology
  that is simultaneously applicable to both CT and
  DT systems.

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Basic Relations
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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, OH, USA
• (The birth place of Aviation)
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• Universities of South Western Australia

70
Applications of SPaTS to Flexible Beam Systems
and Gantry Cranes

• Center of Excellence for Ships and Ocean
  Structures (CESOS)
• Norwegian University of Science and Technology
  (NTNU)
• Trondheim, Norway
• (May -August, 2004)

22nd IFIP Conf. on System Modelling
Optimization Turin, Italy, July 18-22, 2005 To
appear in International Journal of Systems
Science, 2010
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Singular Perturbation Analysis of a Flexible
Beam Used in Underwater Exploration
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Control of a Flexible Beam
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Research on Fusion of Soft and Hard Control
Strategies
Faculty Advisor D. Subbaram Naidu, PhD Vidya
Nandikolla (PhD ISU 2006) Cheng-Hung Chen
(PhD, ISU 2009)
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Biological Neural Networks
2 Billion neurons in human brain with intense
interconnectivity and high nonlinear
functionality
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Neural Networks (NN)

• Neural networks (NN) are massively connected
  networks of computational neurons inspired by
  biological neurons of human brain.
• By adjusting a set of weighting parameters of a
  NN, it may be trained to emulate any function
  that can be used for identification and control
  involving parameter changes and modeling
  uncertainties

76
Fuzzy Logic (FL)

• In fuzzy logic, the knowledge base is represented
  by if-then rules of fuzzy descriptors
  represented by a membership function.
• Fuzzy Logic is useful in systems modeling,
  identification, control, filtering, and
  estimation.

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Genetic Algorithms (GAs)

• Genetic algorithms are derivative-free
  optimization techniques.
• GA are evolutionary algorithms that simulate
  Darwins survival of the fittest principle (1859)
  using ideas of natural selection and evolution.

Charles Darwin 1809 1882
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Soft Computing/Control Techniques

• Synergetic architecture with NN, FL, and GA
• A NN learning fuzzy rules and membership
  functions
• B Fuzzifying neural net training set
• C fuzzy crossover
• D Tuning FL membership functions
• E Global optimization for supervised training

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Soft Computing Features

• Biologically inspired computing elements
  methods
• Neural networks for model free learning and
  adaptation
• Human knowledge in the form of fuzzy IF-THEN
  rules
• New optimization techniques with Genetic
  Algorithms
• New application domains for soft computing

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Fusion of Soft Computing and Hard Computing

• Soft Computing consisting of Neural Network (NN),
  Fuzzy Logic (FL) and Genetic Algorithms (GA),
  etc.
• Hard Computing consisting of Optimal, Adaptive,
  or Robust Control

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Soft Hard Computing Features

• Fuzzy logic of SC can be used at upper levels of
  the overall mission where human involvement and
  decision making is of primary importance, whereas
  the HC can be used at lower levels for accuracy,
  precision, optimality and robustness.
• SC-based GA can be used for tuning PID controller
  for better performance and robustness.
• The SC and HC are potentially complementary
  methodologies.
• The fusion could solve problems that cannot be
  solved satisfactorily by using either methodology
  alone.
• Novel synergetic combinations of SC and HC lead
  to new cost-effective applications.

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Basic Evolutionary System
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Unmanned Combat Aerial Vehicle (UCAV)
Faculty Advisors D. Subbaram Naidu, PhD Marco
P. Schoen, PhD Mr. Andy Hoover (MS Idaho State
Univ. 2006)
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Unmanned Combat Aerial Vehicle (UCAV)
Black Widow (USA)
Future Micro Aerial Vehicles (MAVs) Black Widow
(USA)
Firebird 2001 (Israel)
Predator (USA)
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Intelligent Control System - UCAV
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UCAV Movie Simulation
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Advanced Control Strategies for Heating,
Ventilation, Air-Conditioning (HVAC)
Dr. Craig Rieger, (PhD Idaho State Univ.
2007) Faculty Advisor D. Subbaram Naidu, PhD
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Advanced Control Strategies for Heating,
Ventilation, Air-Conditioning
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Advanced Energy Systems

• Forms of Energy
• Electrical, Mechanical, Thermal, Chemical,
  Biological,
• Sources of Energy
• Sun Solar cells
• Wind Wind Turbines
• Earth Water (Hydro Power), Coal (Thermal
  Power), Uranium (Nuclear Power), Hydrogen,
  Ethanol,

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20 Wind Energy by 2030 US DoE Report July
2008
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Gain Scheduling Optimal Control for Wind
Energy Systems

• Electrical/Thermal/Nuclear Power Systems
  Regulation of speed, voltage, current, power,
  energy - Well investigated problems
• Wind Energy Systems Gain Scheduling Optimal
  Control Current Research

2007
2008
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Resilient Control Systems2007 - ??

• Intelligent or Networked Control Systems with a
  cyber or non-cyber security wrap to tackle a
  disturbance or a fault due to an intelligent
  adversary
• What is the role of Resilient Control Systems in
  Advanced Energy Systems?

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Outline

• Geography and Biography
• Education Research in Science Engr
• Research at Indian Inst. of Technology (IIT)
• NASA Langley Research Center, USA
• Air Force Research Lab, WPAFB, OH, USA
• (The birth place of Aviation)
• CESOS, NTNU, Norway
• Idaho National Lab, Idaho Falls
• Idaho State University MCERC
• ISU Universities of South Western Australia

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Biomedical Engineering ?

• Biomedical engineering (BME) is a discipline
  that advances knowledge in engineering, biology
  and medicine, and improves human health through
  cross-disciplinary activities that integrate the
  engineering sciences with the biomedical sciences
  and clinical practice.
• Source The Whitaker Foundation www.whitaker.org

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Biologist Takes Helm at MIT Dec. 2004

• Susan Hockfield and Charles Vest
• First women and biologist to lead MIT

• She notes convergence between engineering and
  biological sciences
• Largest single source of funding for MIT is NIH
  not NSF, DARPA, DoD!

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Fusion of Hard and Soft Computing Strategies for
Human Circulation System

Vidya Nandikolla, (PhD ISU 2006) Faculty
Advisors D. Subbaram Naidu, PhD Marco P.
Schoen, PhD
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for Human Circulation System

• Minimizing the energy requirements of the heart
  as the sum of the potential energy stored in the
  tissues and muscles of the heart and that
  required for pumping the blood through the
  circulatory system.

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Optimal Insulin Administration to Diabetic
Patient
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SMART PROSTHETIC HAND TECHNOLOGY Phases I to III

Interdisciplinary Biomedical Engineering Research
D. Subbaram Naidu, PhD, Electrical
Engineering Marco P. Schoen, PhD, Mechanical
Engineering Alba Perez, PhD, Mechanical
Engineering Solomon Leung, PhD, Environmental
Engineering Steve Chiu, Computer Science Jim Lai,
PhD, Pharmaceutical and Biomedical Sciences Alex
Urfer, PhD, Physical and Occupational Therapy
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What is Prosthetics?

• Prosthetics is the surgical and dental
  specialties concerned with artificial replacement
  of missing parts.
• Prosthesis is an artificial leg, arm, or any
  other missing body part.
• Prosthetic relating to prosthetics or prosthesis

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Military to Fund Prosthetics Research

• DoD is embarking on multi-million dollar
  research program to revolutionalize upper-body
  prosthetics after a surge in troops who have lost
  hands and arms in the Iraq and Afghanistan wars.
• Pentagon to spend 35M to develop artificial
  arms feel, look, perform like a real arm guided
  by the central nervous system.

USA Today October 05, 2005
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DARPA Neuro Prosthetic Arm
Jesse Sullivan became a real life "bionic man
after a terrible electrical accident.
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Electromyographic (EMG) Signal

• A myoelectric signal is a nerve impulse that
  excites a skeletal muscle.
• Can be measured as an electrical voltage
  potential on the skins surface.

Dr. Marco Schoen
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EMG Signal Identification

• Collect Data
• Analyze Data
• Perform System Identification

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Schematic of Prosthetic Technology
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Prosthetics Research Phase I

• United States Army Medical Research and Material
  Command (USAMRMC), Fort Detrick, MD
• Phase I 842K July 23, 07 to July 22, 09
• Identification of EMG Signals Schoen/ME
• Development of Hand Motion Kinematic and Sensing
  System Perez/ME
• Development of Adaptive Prediction Model
  Naidu/EE
• Biomaterials/Biocompatibility Lai/Pharmacy and
  Leung/ENVE
• Physical Therapy Urfer/Health Professions

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Smart Prosthetics Project Team
7 Faculty from 3 Colleges (CoE, Health, Pharmacy)
and 6 depts (CEE, CS, EE, ME, BioMed Sci,
Physical Occupational Therapy). 5 PhD, 6 MS,
and several UG students
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Prosthetics Research Phase II

• Building the Device

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Prosthetics Research Phase III

• Testing and Validation
• This phase addresses the demonstration of the
  smart prosthetic device developed under Phases I
  and II to realistic situations involving combat
  casualties (veterans) and non-veterans
  (civilians)

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Bionic Hand -IEEE Spectrum Oct. 2007
111
ISU Smart Hand
feel, look, and work like a human hand!
112
HYBRID OF HARD CONTROL AND SOFT COMPUTING FOR
FIVE-FINGERED PROSTHETIC HAND

• Cheng-Hung Chen, D. Subbaram Naidu,
• Alba Perez-Gracia and Marco P. Schoen
• Measurement and Control Engineering Research
  Center
• Idaho State University, Pocatello ID 83209, USA
• 2009 IEEE Conference on Decision and Control
  (CDC)
• Shanghai, China, December 16-18, 2009

113
Statement of the Problem

• Hybrid of soft control technique of adaptive
  neuro-fuzzy inference system (ANFIS) and hard
  control technique of finite-time linear quadratic
  optimal control
• A 14 degrees of freedom (DOFs), five-fingered
  smart prosthetic hand.
• In particular, ANFIS is used for inverse
  kinematics, and the optimal control is used for
  feedback linearized dynamics to minimize tracking
  error.
• The simulations of this hybrid controller, when
  compared with the proportional-integral-derivativ
  e (PID) controller showed enhanced performance.

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Five Fingered Hand Global and Local Coordinates
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Block Diagram of Hybrid Optimal Controller
116
Block Diagram of Hybrid PID Controller
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Five-Finger Prosthetic Hand Reaching a
Rectangular Rod
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Five-Fingered Prosthetic Hand with a Rectangular
Rod Work Space
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Tracking Error Joint Angle for PID Optimal
Controllers for Thumb
120
Tracking Error Joint Angle for PID Optimal
Controllers for Index Finger
121
Tracking Error Joint Angle for PID Optimal
Controllers for Middle Finger
122
Tracking Error Joint Angle for PID Optimal
Controllers for Ring Finger
123
Tracking Error Joint Angle for PID Optimal
Controllers for Little Finger
124
Outcomes

• Adaptive Neuro-Fuzzy Inference System (ANFIS) was
  used for inverse kinematics.
• The hybrid optimal controller was used to
  minimize tracking error using feedback linearized
  dynamics.
• The simulations of this hybrid controller, when
  compared with the proportional-integral-derivative
  (PID) controller showed enhanced performance.

125
Hybrid Control for a Two-Fingered Hand
126
Smart Prosthetic Hand Movie Simulation
127
Questions and Comments?