AFOSR/ARO/NSF/ONR/ESF Jointly Sponsored Workshop on Autonomic Structural Systems for Threat Mitigation Preliminary report of Group 2 SYSTEM DYNAMICS, CONTROL AND MECHARONICS Background review and analysis of System Dynamics, Control and Mechatronics - PowerPoint PPT Presentation

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AFOSR/ARO/NSF/ONR/ESF Jointly Sponsored Workshop on Autonomic Structural Systems for Threat Mitigation Preliminary report of Group 2 SYSTEM DYNAMICS, CONTROL AND MECHARONICS Background review and analysis of System Dynamics, Control and Mechatronics

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Title: AFOSR/ARO/NSF/ONR/ESF Jointly Sponsored Workshop on Autonomic Structural Systems for Threat Mitigation Preliminary report of Group 2 SYSTEM DYNAMICS, CONTROL AND MECHARONICS Background review and analysis of System Dynamics, Control and Mechatronics


1
AFOSR/ARO/NSF/ONR/ESF Jointly Sponsored Workshop
on Autonomic Structural Systems for Threat
Mitigation Preliminary report of Group 2 SYSTEM
DYNAMICS, CONTROL AND MECHARONICS Background
review and analysis of System Dynamics, Control
and Mechatronics
  • Group 2- SYSTEM DYNAMICS, CONTROL, AND
    MECHATRONICS
  • Participants
  • Asada, Harry asada_at_mit.edu
  • Becker, Jürgen juergen.becker.external_at_eads.com,
    Co-Chair
  • Bergman, Larry lbergman_at_uiuc.edu
  • Hansen, Mark Markcocteau_at_stat.ucla.edu
  • Krommer, Michael krommer_at_mechatronik.uni-linz.ac.a
    t
  • Luber, Wolfgang Wolfgang.Luber_at_eads.com
  • Percival, Donald dbp_at_apl.washington.edu
  • Rodellar, Jose Jose.rodellar_at_upc.es
  • Simpson, John john.simpson_at_eads.com
  • Syrmakezis, Costa isaasyr_at_central.ntua.gr
  • Masayoshito, Tomizuka tomizuka_at_me.berkeley.edu,
    Co-Chair

2
Preliminary report of Group 2 Table of Contents
1. INTRODUCTION 2.DESCRIPTION OF DYNAMIC
THREATS 3. THREAT MITIGATION OF STRUCTURAL
SYSTEMS UNDER DYNAMIC LOAD CONDITIONS 4. THREAT
MITIGATION OF CONTROLLED STRUCTURAL SYSTEMS
UNDER DYNAMIC LOAD CONDITIONS 5. THREAT
MITIGATION BY AUTONOMIC STRUCTURAL SYSTEMS UNDER
DYNAMIC LOAD CONDITIONS 6. STATE OF THE ART
TECHNOLOGIES (Dyn Systems Control) 6.1 Modeling
and Identification 6.2 Control System Design
Methodologies Control Theories 6.3 Control
System Design Technologies Control Theories 6.4
Sensors/Actuators and Component Technologies
3
Preliminary report of Group 2 Table of Contents
(continues)
  • 6.5 Applications and Mechatronics
  • 6.6 Robotics and Automation e.g. mobile ME as
    on-board ancillary system "R2-D2"
  • 6.7 ME(mechatronic elements) Catagories
  • 6.8 System subordination expendable(sacrificial)
  • 7. ROLE OF SYSTEM DYNAMICS, CONTROL
    MECHATRONICS IN SMART AUTONOMIC STRUCTURES
    SYSTEMS
  • 8. SHORT-TERM LONG-TERM GOALS APPLICTION
    AREAS OF TECHNOLOGIES IN SYSTEM DYNAMICS, CONTROL
    MECHATRONICS
  • 9. TECHNOLOGICAL BARRIERS TO REACH THE IDENTIFIED
    GOALS
  • RECOMMENDATIONS FOR ACHIEVING THE GOALS AND
    POTETIAL JOINT/COLLABORATIVE PROJECT ROAD MAP
  • 11. REFERENCES

4
  • 1. INTRODUCTION
  •  
  • Autonomic Structural Systems Systems that can
    withstand undesirable dynamic excitations and
    inputs and has capability of self-xxxx including
    self-healing and self-sustainable.
  • Challenges realization of smart and
    multi-functional dynamic load bearing composite
    material structures for and their integration in
    civil, aerospace, surface transportation and a
    variety of defence systems.
  • Problem areas include structures or electronic
    subsystems under uncertain and stochastic natural
    hazardous excitations the sensing and diagnosis
    of dynamic threats, penetration prevention, load
    capacity preservation, and functionality
    restoration.

5
  • INTRODUCTION (cont.)
  • The field of dynamic systems and control deals
    with the modeling, design, analysis and
    synthesis of functioning systems by integrating
    various components.
  • The feedback principle is applied either
    explicitly or implicitly in these processes.
  • Mechatronics considerations are important in the
    field of dynamic systems and control.
  • The Intelligent Civil and Mechanical Systems
    Cluster of the CMS (Civil and Mechanical Systems
    Division), National Science Foundation has three
    programs relevant to this workshop
  • Dynamic systems (Dr. Eduardo Misawa)
  • Sensor Technologies for Civil and Mechanical
    Systems (Dr. S.C. Liu)
  • Control Systems (Dr. Mario Rotea)

6
Mechatronics
Synergistic integration of physical systems with
electronics/information technology and
complex-decision making in the design and
construction of functioning systems.
Modern Mechatronic Systems
7
Mechatronics
  • Synergy in terms of
  • Dealing with complexity
  • Performance
  • Physical dimension, weight
  • Time for development
  • Cost
  • Reliability
  • Power efficiency ..

Synergy cannot be obtained via traditional
approach Material scientists come up with
materials Mechanical engineers design
mechananisms Control engineers design
controller..
8
2.      DESCRIPTION OF DYNAMIC THREATS (to civil
and manned/unmanned military aircraft,
helicopters and spacecraft) Dynamic
excitations causing dynamic response of the total
structural system (vehicle, air-vehicle) may be
distinguished between external and internal
excitations. Internal excitations may result
from systems and smart systems interactions
causing dynamic loads due to servo-elastic or
aero-servo-elastic phenomena. The detection of
dynamic excitations causing threats by sensor
systems is essential for controlled system
dynamics for autonomic systems.  
2.0 Dynamic Threat definition        
behavioural (pilot)         operationalmission
maintenance (engine, avionics,
quality)         Airframe body/payload,
Multibody, Multi aircraft dynamics
9
2.1      Gust penetration Maximum gust
velocities defined by civil and military
specifications might be exceeded in reality
2.2      Stochastic excitation through air
turbulence Maximum rms velocities and power
spectral densities defined by civil and military
specifications might be exceeded in reality
2.3      Stochastic excitation through flow
separation on structural components of
air-vehicles Predicted buffet induced dynamic
loads acting on air vehicle components might be
exceeded
10
2.      DESCRIPTION OF DYNAMIC THREATS
2.4      Wake penetration of civil and military
aircraft The wake penetration of civil or
military aircraft by another civil or military
aircraft can lead to dynamic loads exceeding the
dynamic structural design loads
2.5      Dynamic Impact loads           Firing
gun firing impact, missile impact         Bird
strike structure/engine intake         Rough
runway, damaged runway         Landing
impact         Ice particle impact        
Store jettison        Noise etc  
11
2.6 ASE (Aeroservoelastic)/ CASE
(Computer ASE hazard)  Loss of control
surfaces   impaired servoelastic
control  designed in hazard aeroelastic/servo-
dynamics -- optimal effectiveness could be
severer mechanism in threat case
2.7 Flight Dynamics ballistically optimal EM
reflection by trajectory field of view (FOV)
2.8 Dynamic load excitance of EM
functionality 2.9 Dynamic loads HUMS (health
usage monitoring systems) interaction

12
  • 3. THREAT MITIGATION OF STRUCTURAL SYSTEMS UNDER
    DYNAMIC LOAD CONDITIONS
  • Threat mitigation can be achieved to a certain
    degree by a conventional design of the structure
    system (not including active autonomic systems
    for mitigation) by using maximum definitions of
    dynamic excitations.
  • The classical design is based on system dynamics
    modelling and experimental identification.
  • System safety and system certification is
    achieved by a validated model.
  • This classical approach might also include a
    process considering locally damaged structural
    parts for the final purpose of safe landing

13
  • 4. THREAT MITIGATION OF CONTROLLED STRUCTURAL
    SYSTEMS UNDER DYNAMIC LOAD CONDITIONS
  • Threat mitigation can be achieved to a certain
    degree by a conventional design of the
    controlled structure system (including active
    gust load alleviation closed and open loop
    systems, vibration alleviation systems, general
    dynamic load suppression systems, but not
    including active autonomic systems for
    mitigation) by using maximum definitions of
    dynamic excitations.
  • The classical design including the alleviation
    systems is based on a coupled structural system /
    control system /sensor /actuator - dynamics
    modelling and experimental identification. System
    safety and system certification is achieved by a
    validated model trough on ground and in flight
    system identification tests.

14
  • 5. THREAT MITIGATION BY AUTONOMIC STRUCTURAL
    SYSTEMS UNDER DYNAMIC LOAD CONDITIONS
  • Threat mitigation can be achieved by autonomic
    systems using as basis the conventional design
    of the controlled structure system (including for
    example active gust load alleviation closed and
    open loop systems, vibration alleviation systems,
    general dynamic load suppression systems) by
    application of novel excitation detection
    systems, health usage monitoring -, damage
    monitoring- system capabilities and integrated
    antenna systems.

15
  • 6. STATE OF THE ART TECHNOLOGIES
  • Five Subfields
  • Modeling and Identification (include FDI, Failure
    Detection and Identification)
  • Control System Design Methodologies Control
    Theories
  • Linear robust control/Nonlinear Control/Adaptive
    and learning control
  • Actuators/Sensors and Component Technologies
  • For Group 2, important issues include signal
    processing, noise filtering, sensor and actuator
    placement,
  • Applications and Mechatronics
  • Robotics and Automation
  • Concept design drivers
  • with rigid plant assumption
  • with flexible plant assumption
  • with variable system design attitude

16
  • 6.1 Modeling and Identification
  • Michael Krommer
  • Smart composite structures can be characterized
    as those that incorporate materials into the
    structure with both sensing and actuation
    capabilities. These materials are load bearing
    hence, they need to be incorporated into the
    modeling.
  • This clearly gives raise to the necessity of a
    multi-field modeling approach, because many
    different fields of different physical nature
    will be involved. As one example the well studied
    piezoelectric composite structures may be
    mentioned.

17
  • 6.1 Modeling and Identification (Larry Bergman)
  • Identification methods developed for linear
    systems generally fail when applied to damaged
    structures. The underlying systems will be
    strongly nonlinear and nonstationary with unknown
    models.
  • The Hilbert-Huang transform (HHT) is the basis
    for a fully nonparametric identification method.
    It precisely determines the most appropriate
    adaptive basis through the Empirical Mode
    Decomposition (EMD) to provide the Intrinsic Mode
    Functions (IMF) of the system.
  • Success of the method hinges on the recently
    observed relationship between the slow flows of
    the system, obtained from complexification and
    averaging (CxA), and the IMFs.

18
Figure 1 Response y(t) of oscillator (1) (a)
Comparison between exact (numerical) and
slow-flow models (b) Leading-order IMFs and
their instantaneous amplitudes.
19
Figure 2 Comparisons of the results of the CxA
___________ and HHT ----------- methods for the
response y(t).
20
  • 6.1 Modeling and Identification
  • Jose Rodellar
  • In smart stucture and mechatronic systems (thus
    in the new smart autonomic system), it is
    expected to have materials and devices exhibiting
    complex nonlinear dynamics with coupling. Two
    modeling approaches are physical and
    phenomenological.
  • Physical models are based on first principles and
    constitutive relations. They support the
    knowledge, design and prediction of behaviors.
  • Phenomenological models are approximations but
    useful for control system design. An example is
    the Bouc-Wen model which is often used for
    describing MR dampers piezoelectric actuators,
    base isolation devices for building, strctural
    joints,

21
  • 6.2 Control System Design Methodologies Control
    Theories
  • Michael Krommer
  • CONTROL OF DISTRIBUTED PARAMETER SYSTEMS
  • Modal-space control methods have become popular
  • Powerful methods of modern control theory for
    distributed parameter systems are available
    nowadays.
  • Tomizuka
  • Fault Tolerant Control Methodologies such as
    simultaneous stabilization (Vidyasagger) are
    relevant.
  • If nonlinear dynamic models are linear with
    respect to parameters, the adaptive control
    theory may be rigorously applied (e.g. robotics).
  • Sensing and Precognition ? Preview control?
  • Networked Sensing/Control.

22
  • 6.2 Control System Design Methodologies Control
    Theories
  • Costas Syromakezis
  • Incorporation of passive control elements into
    the (civil) load-bearing systems (two case
    studies)
  • A probabilistic approach on structural
    vulnerability
  • Note added by MT Three basic approaches are 1)
    passive control (dampers), 2) active control
    (actuation) and 3) Semi-active control
    (controllable dampers, etc)

23
Fragility curves for the structure, with dampers
(continuous line) and without dampers (dashed
line)
24
  • 6.2 Control System Design Methodologies Control
    Theories
  • Harry Asada
  • Distributed, stochastic control and broadcast
    feedback
  • Control an ensemble of cellular units
    stochastically based on broadcast feedback
    information.
  • Scalable to the order of thousands and millions
    of units, very robust, fault tolerant, etc.

25
Control an ensemble of cellular units
stochastically
Broadcast Feedback
Aggregate error signal alone is broadcasted.
Each cellular unit makes a probabilistic decision.
State transition probability is modulated with
the error signal.
Aggregate Output is fed back
26
  • 6.3 Sensors/Actuators and Component Technologies
  • Michael Krommer
  • DISTRIBUTED SENSORS/ACTUATORS AND DENSE SENSOR
    NETWORKS
  • In the last decade, a large number of research
    studies have been devoted to continuously
    distributed sensors for measuring overall
    structural entities, such as natural frequencies
    and modal amplitudes e.g. piezoelectric sensors
    can be used for that purpose .
  • Similar to piezoelectric sensors, optical fibers
    can measure a weighted integral over the strains
    they are suffering throughout their extension,
    and thus can be applied in structural control.

27
The typical strategy for the design of such
networks is based on the optimization of
performance indices based on modal and system
observability. These methods directly target at
their application in the control of vibrations,
but may not necessarily be used for detecting
localized damage or controlling local structural
entities. The corresponding methods are not yet
developed far enough to be applied to highly
redundant structures to be encountered in
sensitive facilities of civil and mechanical
engineering for the case of dense sensor
networks such methods are not available.
Similar to distributed sensors spatially
distributed actuators are widely used as modal
actuators.
28
  • 6.3 Sensors/Actuators and Component Technologies
    (Harry Asada)
  • BINARY STRUCTURES
  • Construct a structure with a collection of
    elements with binary (ON-OFF) actuators having
    bi-stable characteristics.
  • CELLULAR ACTUATORS
  • Divide smart structure actuator materials into a
    vast number of small segments, control individual
    segments (cells) as finite state machines, and
    coordinate the cells to control the aggregate
    behavior of the entire cells.
  • Biologically inspired architecture, robust,
    making a smart material, a linear stepping motor

29
Bulk control of a smart material is difficult due
to hysteresis and nonlinearity.
Segment the actuator material into many tiny cells
Apply simple ON-OFF binary control ? Stepping
Motor, robust and simple
30
Cellular Muscle Actuators Biologically Inspired,
building an actuator as an ensemble of many
cellular units.
Artificial Sarcomeres
Sarcomere
Spence, A.P., Basic Human Anatomy, 3-rd
Edition, Benjamin Cummings, 1990.
31
  • 6.5 Applications and Mechatronics
  • contribution of J. S.
  • Applications have been demonstrated by industry
    and show state of the art (see J. Becker, J.
    Simpson, K. Dittrich The future role of smart
    structure systems in modern aircraft Smart
    Structures and Systems, Vol. 1, No.2
    (2005)describing electromagnetic structures
    Structure integrated distributed Antennas (SIA)
    health monitoring systems and vibration
    alleviation
  • K. P. Kress Overview on the AMOS project,
    International workshop on Structural Health
    Monitoring, Stanford, Sept. 2003) describing
    Structural health monitoring integrated antenna
    manufacture monitoring
  • Individual Load Monitoring, Testing,
    Diagnostics and Prognosis

32
  • 6.6 Robotics and Automation
  • Harry Asada
  • Modular robots
  • Build a reconfigurable structure or an active
    structure by combinations of (small) modular
    robots. They are reconfigurable, repairable,
    flexible, robust, adaptable, distributed, etc.
  • 6.7 ME ( mechatronic elements) Catagories
  • -non-mobile -mobile (multi-body ME) -distributed
  • 6.8 System subordination
  • expendable (sacrificial)
  • endurance element

33
Robotics and Automation
Reconfigurable modular robots
  • Build a variety of structures with many modules
    self assembly
  • Each module capable of sensing, actuation,
    communication, and control

Reconfigurable, Repairable, Robust, Adaptable and
Distributed Applications to Space Mission,
Medical Robots
34
  • 8. SHORT-TERM LONG-TERM GOALS APPLICATION
    AREAS OF TECHNOLOGIES IN SYSTEM DYNAMICS, CONTROL
    MECHATRONICS. (Michael Krommer)
  • SHORT-TERM GOALS
  • Advancement of existing methods
  • system dynamics multi-field modeling, inverse
    problems of dynamics for sensor and actuator
    distribution and placement
  • control control theory of infinite-dimensional
    systems
  • mechatronics (controlled system dynamics)
    integrated design and simulation of structural
    systems, including direct and inverse coupled
    multi-field problems, sensors and actuators as
    well as control systems
  • Application of available technology
  • Technology transfer from fields, in which smart
    material technology is accepted and already
    successfully implemented to other fields e.g. to
    civil engineering not only for monitoring, but
    also for active control.
  • Application of available sensors/actuators for
    the measurement/control of physical entities not
    directly measured/controlled e.g. use of
    strain-type sensors/actuators for the
    measurement/control of stress.
  •  

35
  • 8. (M.K. inpust cont.)

LONG-TERM GOALS Novel multi-functional
materials Self-healing structures Development
of advanced methods of system dynamics for the
modeling and analysis of the overall dynamic
behavior of future self-healing structures in
combination with incorporating local dynamic
healing processes. Inverse problems of combined
overall and local dynamics for sensor and
actuator distribution and placement in
self-healing structures. Control system design
for self-healing structures -Taking into account
combined overall and local dynamics -Possible
need for localized control actively supporting
self-healing process.
36
9. TECHNOLOGICAL BARRIERS TO REACH THE IDENTIFIED
GOALS . Technological challenge (Jose
Rodellar)   Develop phenomenological models for
complex behaviours able to capture essential
physical properties while keeping enough
simplicity for input-output characterization and
for enabling the design of controllers which can
be implemented in real time with the available
technology.  
37
  • RECOMMENDATIONS FOR ACHIEVING THE GOALS AND
    POTENTIAL JOINT/COLLABORATIVE PROJECT
  • M. K. proposes some recommendations for future
    EDUCATION and RESEARCH in MECHATRONICS
  • An important goal would be the implementation of
    new mechatronics curricula at universities in the
    U.S. and in Europe.
  • From a European point of view these new
    mechatronics curricula need to be implemented in
    the framework of the ongoing Bologna process
    including undergraduate, graduate and Ph.D.
    degrees.

38
  • RECOMMENDATIONS FOR ACHIEVING THE GOALS AND
    POTETIAL JOINT/COLLABORATIVE PROJECT (by Jose
    Rodellar)

   Develop joint projects with developers
of materials, sensors and actuators together with
a mix of theoretically/engineering oriented
researchers in dynamics and control. These
projects should emphasize on the integration of
disciplines and mutual approaches. For example,
simplified models for control purposes would be
better based if supervised by material developers
and by experts in complex numerical modeling in
conjunction with system concepts. Design of
sensors and actuators can benefit if
modeling/control people is cooperating at early
stages. For specific applications, experts-end
users are fundamental.
39
  • Challenges
  •     Education concerning inter-disciplinary
    system design and mechatronics at Universities
  •      Autonomic structural systems for threat
    mitigation shall remain low weight,
    manufacturable, cost-effective, environmentally
    robust and sustainable (dynamic/static load
    carrying).
  •     Autonomic structural systems shall be
    compatible with the overall vehicle  system
    structural requirements and all total system
    control and other control system requirements
  •     Integration of autonomic structural systems
    into total systems
  •     Modeling of excitations for example
     turbulence , wake penetration including wake
    turbulence
  •     Sensing of local damage, sensing of gusts,
    turbulence and wakes etc.  flow field detection
    systems
  •   

40
  • Challenges     Interdisciplinary approach for
    dynamic modeling and design of the local
    multilayer structures and total dynamic systems
    including autonomic threat mitigation
    systems (physical and phenomenological modeling)
    (for instance elastic, servo-elastic,
    aero-elastic, aero-servo-elastic modeling of
    vehicles/air-vehicles, especially modeling of
    stationary and unsteady aerodynamics at transonic
    and at high incidence via elastic/aero-elastic
    simulations using CFD (Navier- Stokes)
    methods/predictions modeling including rigid
    total vehicle/air-vehicle dynamics/ flight
    mechanics).
  •     Validation of local structural and total
    structural system modeling through dynamic
    experiments
  •     Procedures and processes for system dynamic
    qualification and certification for different
    damage scenarios other challenges are t. b. d.
    during discussion

41
  • Technological Barriers
  •     Autonomic structural load/dynamic load
    carrying, low weight /small volume systems
    compared to non autonomic systems
  •     Autonomic structural load carrying, low
    weight , self heeling  systems
  •     Affordable control systems for carefree
    handling of systems and damaged structures,
    damaged actuators and sensor systems (cycle times
    of computers) other barriers t. b. d. during
    discussion

42
  • Enablers
  •     Joint projects with developers of materials,
    sensor and actuator and systems together with a
    mix of theoretically/engineering oriented
    researchers in dynamic and control  expert end
    users are fundamental
  •       Joint research projects of EU/US
    Universities and industry (dynamic system
    modeling, system design and operation, system
    strategies and technologies, parameter
    identification, fault diagnostics and
    identification and novel sensor technologies
    etc.)           Joint projects of Universities
    and industry (dynamic smart and total system
    modeling, system design and operation, smart
    system  integration into  vehicle/air-vehicle and
    or equipment systems, validation)

43
  • Enablers For example - Conduction of joint
    Univ/Industry research in the field of
  • Autonomic systems for local structural damage ,
    partial destroyed integrated antennas or health
    monitoring systems (phased array radar,
    ultrasonic systems)
  • Autonomic flight control systems for partially
    damaged structure, actuators , control surfaces
    and sensors other enablers are t. b. d. during
    discussion
  • Restrainers t. b. d.

44
  • Required Facilities Resources
  • Facilities Computer software for dynamic
    simulation of coupled elastic structure with
    control systems (including embedded or other
    sensors and electronic equipments and actuators
    and  without motion (vehicles) and with/without
    motion induced  and external excitation
    aerodynamics. Test equipments for dynamic testing
    of local multilayer and total structure systems
    (shakers, ground resonance test facilities and
    structural coupling test facilities on ground and
    in flight) Resources
  • Funding through - EU framework research
    programs - US research programs - industry
    other are t. b. d. during discussion
  • Milestones - Short term goals t. b. d.
  • - Long term goals t. b. d.
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