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					          International Federation
            of Automatic Control
            Rotterdam            August, 2003
The goal of the on-going Emerging Areas project is to identify
recent significant trends that are likely to continue within the
automatic control field. The 2003 outcome of the project was
a Panel Session. Presentations from that Session follow,
• Introduction to Emerging Areas Project               Slide 7
• Integrated / Embedded Control                        Slide 17
• Distributed Control (over Communication Networks)    Slide 24
• Collaborative Control                                Slide 30
• Hybrid/Discrete Event Systems/Networks               Slide 36
• Autonomous Systems                                   Slide 43
Closing Comments                                       Slide 48
               IFAC NEWSLETTER
    IFAC Technical Board Identifies Emerging Areas
The goal of IFAC is to “promote (in both theory and applications) science and technology of control in all
    systems, whether engineering, physical, biological, social or economic.” In support of this goal, the IFAC
    Technical Board maintains on-going efforts to identify trends and forecast emerging areas within our
    field. The Technical Board’s most recent formal activity regarding this thrust was a Workshop and Panel
    Session held in Rotterdam, The Netherlands, in conjunction with the IFAC Symposium on System
    Identification (SYSID).

The goal of the 2003 Emerging Areas Workshop / Panel was,

    Identify emerging trends within the control system and automation field
    Forecast tomorrow’s most significant applications which will achieve higher performance, increased
     efficiency, lower cost, or other benefits
    Identify the likely control methodologies and implementations that will enable such future improvements.

WORKSHOP Participants in the Workshop portion of the meeting were members of the IFAC Technical
  Board and selected Invited Guests from Dutch industries invited by the Dutch NMO. Each participant
  was asked to suggest trends/developments/needs within their respective areas of competence. As a result,
  over 50 suggestions were presented and considered during the afternoon Workshop. (A complete
  inventory of all these suggestions is available at the IFAC web-site as described below.)
After presentation and discussion of the various suggestions by each participant, several of the related
    suggestions were combined, and a final list was then prioritized to identify the following major trends
    believed to be especially significant:

    Increased Development of Theoretical Techniques and Practical Application of Hybrid / Discrete Event
    Increased Development and use of Distributed Control Techniques (Especially for Applications using
    Wireless communication Technology)
    Continued Theoretical Development and Applications for Nonlinear Control; to Overcome Limitations
    with Linear Representations / Models
    Increased use and Development of Innovative, Ubiquitous Sensors and Actuators; MEMS will Enable
    many New Sensors
    More Effective Subsystems Operating at Optimal levels will be Integrated and Embedded to yield
    Improved Overall Systems
    Interest in Learning Control Systems will Intensify; the Name “Adaptive Control” may Not be Used, but
    the Concepts will Continue
    Autonomous Robots and Autonomous Vehicle Development will Continue as Enabling Technologies
    Fault Detection / Isolation and Predictive Maintenance Techniques will greatly Improve operation of
    Highly Complex Systems
    Collaborative Robots will assist and collaborate with Humans in Complex and/or Difficult Work
    Tools that Facilitate Collaborative Human-to-Human Work and Activities (e.g. E-Work and collaborative
    robotic systems) will Develop
    New Hard and Soft Sensors will be Developed for Biotechnology and Biomedical Applications
    Artificial Intelligence and Agent-Based Models will become more Useful for Controlling and Improving
    Economic Systems
    Dramatic Automotive Control Advancements will Continue to Improve Safety, Operation, and Vehicle
    Autonomous Systems will Become Practical for Complex Operating Environments
    Control Technologies will enable Realization and Deployment of next-generation high-performance Nano
    and Micro Systems; future Controllers will benefit.
PANEL SESSION The above trends were further reviewed and several were selected and refined for presentation
   in an evening Panel Session, attended by many of the SYSID Symposium attendees and members of the Dutch
   NMO. The allowable time for the Panel Session was of course limited, so only five trends were selected for the
   Panel Session. The highlights of these presentations are,

Integrated / Embedded Control
Significant developments over the last decade within several different technologies now enable practical
    implementation of new control architectures. These advancements include innovative sensors & actuators
    (many based on MEMS techniques), more powerful computers & Digital Signal Processors, and exciting
    breakthroughs in communications & network technology. As a result, two distinct trends are now gaining
    momentum within control. The first trend is integration such that perception (measurement, sensing) can now
    be embedded with control (controller, actuator) so that these previously separate functions are now
    transparent; in fact, single components may someday sense, determine what to do, and then carry out the
    desired actions. The second trend is distributed control over wireless (and conventional wire-based)
    communication networks to connect embedded controllers into an overall closed loop operation. Such
    integrated/embedded controllers will enable improved medical technologies, increase energy efficiency, advance
    vehicle control, and enable many new consumer products.

Distributed Control (Over Communication Networks)
Recent developments within both control theory and hardware & tools now enable distributed control to become a
    practical reality. Numerous subsystems, each with their respective level of autonomy (but not co-located), can
    be integrated to control highly complex systems. As distributed control has progressed, it is common for large
    numbers of different types of components to exchange information through dispersed communication
    networks; furthermore, recent developments of wireless communication offer yet another tool for this field.
    Although control, information theory, and communications are mature disciplines, theoretical issues in
    information theory and its effect upon performance of distributed control (conflict resolution, resource
    allocation, avoidance of deadlocks, etc.) are not well understood. Future control theory will address the impact
    of communication channel delays, quantization errors, transmission noise, random loss of information, as well
    as data handling and safety & reliability. Attention will also be given to practical design of encoders, decoders,
    estimators, filters, and other communication elements to achieve improved performance, efficiency, and
    decisions made by large numbers of distributed controllers.
Collaborative Control
Distributed systems are typically composed of numerous lower-level sub-systems with their individual control tasks
    and responsibilities. Collaboration among such interrelated systems is clearly essential in order to benefit from
    the respective strengths of the several “partners”. Fortunately, collaborative control trends are apparent for
    all system types. Machine-Machine: Cooperation of smart robotic teams (including micro- and nano- as well as
    “routine” robots) will improve as new collaborative control techniques are developed; as faults, errors, and
    interactions are better managed; and as protocols for fault-tolerant operation are developed. Human-Machine:
    Better understanding of how to “share tasks” will improve operation and will come from improved software,
    more incorporation of human factors, continued adaptation (learning) by the machine, better displays, new
    types of feedback, and new sensors & actuators better tailored for human users. Human-Human: Human
    “team” performance will also improve as enterprise software integrates and aids team decisions, as new
    methods (e.g. internet-conferencing) improve team coordination (even when remotely located with different
    databases, culture, or knowledge disciplines), and as task optimization methods enable multiple workers to
    share work and reduce local overloads.

Hybrid / Discrete Event Systems / Networks
Continuous (and discrete) Time systems and Discrete Event systems have essentially been developed independently
   of each other. However both phenomena frequently appear in the same process. Examples include
   manufacturing, process control (start-up/shut-down), autonomous, and distributed control systems. Radar
   processing provides a specific example which requires dynamic estimation of whether or not a target is present,
   what type target, whether or not it is maneuvering, forecasted track movements, etc. Typical solutions are
   “sequential” which involves detection, then classification, estimation, etc. Such approaches are clearly sub-
   optimal. Combined solutions for such Hybrid systems will no doubt develop in the future. New controllers will
   be driven by the need for higher performance from such systems, as well as the need to make better use of
   resources and an increased use of embedded/integrated systems. Theoretical developments are already being
   addressed and, as proven performance improves and reliability & autonomy increase, the number of
   applications will grow. Controllers for such systems will probably be more complex than earlier solutions, and
   development of such methods will require merging of heretofore different fields and different designer
   approaches (sometimes even with different methods and solution languages).
Autonomous Systems
Today’s automotive industry offers numerous innovations including driver assistance (ABS, ESP, Distance
    Detection), suspension control (passive), self-diagnostics, improved comfort (climate control, lighting, seats,
    entertainment), and more precise engine and driveline control. Emerging developments include drive-by-wire,
    brake-by-wire, parking assistance, collision warning, pedestrian detection, active suspension control, noise &
    vibration control, and a host of telematics (navigation, on-board e-services, etc.). These developments will
    improve vehicle safety and, when coupled with infrastructure improvements, will yield intelligent traffic control.
    These developments will also leverage developments in autonomous unmanned vehicles for situations such as
    operation in hostile environments. Such vehicles will plan their own operations, as well as control the vehicle,
    to achieve these goals and develop alternate strategies when failures or unexpected hindrances are encountered.
    These “autonomous” concepts will also be extended to other applications such as unmanned factories and
    processing plants.

Post Session Comments
Various comments that have been submitted since the Panel Session begin at Slide 48 in this file. If you would like
    to add your comments, please send them to m.masten@ieee.org

Mike Masten, Chair, Technical Board

        AUGUST, 2003


       Presenter: Mike Masten
• Introduction to IFAC
  – Goals
  – Activities
• Goals of IFAC Emerging Areas Project
• Emerging Areas Process
• Panel Session
  – Panelists Presentations
  – Industrial Guest Evaluation & Feedback
  – Audience Comments & Questions
• Goal: Promote science and technology of
  control in the broadest sense in all
  systems, whether, for example,
  engineering, physical, biological, social or
  economic, in both theory and application.
  Also concerned with the impact of control
  technology on society.
• Activities: Organize technical meetings,
  publications, and any other activities
  consistent with IFAC constitution which
  enhances the interchange and circulation
  of information on automatic control
             IFAC MEETINGS
    – Major IFAC event, Held every Three (3) years
    – Recent & Forthcoming Congresses:
           2002 Barcelona     2005 Prague   2008 Seoul

    – Long Term Events on Master Plan, usually Held Triennially
    – Technical Events, not Necessarily Part of a Series
    – Smaller Events, less Formal

Approximately 50 Meetings per Year (Except for Congress Year)
   – Current IFAC News Information and Up-to-Date Announcements of
     Forthcoming Events
   – Papers on Original Theoretical and Experimental Research and
     Development, Involving all facets of Control Theory and Applications
   – Papers which Illustrate Applications of Control Theory and its Supporting
     Tools; Emphasizes Practical Results
   – Best IFAC papers Presented at Meetings, re-written, and Broadened (or
     Commissioned Reviews in Emerging Research areas)
   – Papers Relating to all Aspects of Chemical Process Control
   – Papers Relating to Intelligent Real-Time Automation
   – Usually associated with a Technical Committee; List Available from IFAC
THEORY                                   APPLICATIONS
                                         Manufacturing Plant Control
Control Design                           Management & Control
Modeling                                 Enterprize Integration & Networking
                                         Large Scale Complex Systems
                                         Chemical Process Control
Signal Processing                        Mining, Mineral, & Metal Processing
Adaptive Control         TECHNOLOGY      Power Plants; Power Systems
Learning Systems         Computers       Automotive Control
Discrete Event Systems                   Marine Systems
Hybrid Systems           Telematics      Transportation Systems
Stochastic Systems       Components
                                         Intelligent Autonomous Vehicles
                                         Control in Agriculture
Linear Control
                         Instruments     Biomedical Systems
Nonlinear Control                        Environmental Systems
                         Mechatronics    Biotechnological Systems
Optimal Control                          Economic & Business Systems
Robust Control                           Social Impact of Automation
                         Cost Oriented   Developing Countries / International
                         Automation      Stability
                                         Control Education
• Identify the Major Emerging Trends within the Control
  System and Automation Field
• Forecast Tomorrow’s Most Significant Applications
  which will Achieve Higher Performance, Increased
  Efficiency, Lower Cost, or Other Benefits
• Identify Likely Control Methodologies and
  Implementations that will Enable Future Improvements
• Workshop
  – Consideration: Potential Significant Trends/Forecasts
  – Selection: Most Significant Trends/Forecasts
  – Preparation: Breakouts to Prepare for Panel
• Panel Session
  – Presentation: Workshop Conclusions
  – Evaluation: Industrial Guest Feedback
  – Discussion: Audience Questions & Comments
• IFAC Technical Board Members
  Tohru Katayama          Ruth Bars       Robert Babuska
  Anibal Ollero           Shimon Nof      Denis Dochain
  Philipp Nenninger       Keith Godfrey   Talha Dinibutun
  Sirkka-Liisa Jamsa-Jounela              Alberto Isidori
  Dongil Cho
• Industrial Guests
  Herman Van der Auweraer (Lueven Measurement Systems)
  Fred Abbink (National Aerospace Lab NLR)
  Ton Backx (IPCOS Technology)
  Hans Driessen (Thales)
  Alex van Delft (DSM)
Adaptive Control MEMS Driving Assistance Smart Drugs
  Robotics Manufacturing         Artificial Intelligence Radar
Optimization       Navigation         Speaking Animals & Plants
   Telepresence      Distributed Systems                 Wireless
 Software Agents        Switching Control          Learning Control
Ubiquitous Sensors & Actuators             Perception Systems
     Stochastic        Agriculture and Crops         BioTechnology
   Economics & Business Airports/Aerospace
Transportation Systems         E-Work        Hybrid Systems
        Bio-Informatics              PDE Systems
Water/Waste Management Computers & Control
         Infinite Dimensional Systems
Intelligent Systems Modeling & Identification

         AUGUST, 2003


        Presenter: Anibal Ollero
     Panel Session Presentation
   “Embedded Control”
                 A. Ollero (Univ. Sevilla, Spain),
R. Babuska (Delft University of Technology, The Netherlands) and
             H. Vander Auwerarer (IMS, Belgium)
Control System            Embedded controllers

                 Embedded control separates control into subsystems
                 of the overall system, e.g. Hands, Arms, Feet, Wheel
           Enabling technologies
 Sensors and actuators with embedded intelligence.
 MEMS as supporting technology.
 Computer developments: embedded systems with
  increasing powers.
 Communications/Networks.
              Forecast/trends in control
 Medical technologies, health care: surgical devices, medical
 Communication technologies: network control, wireless
 Advanced vehicle control.
      New cars, vehicles and transportation technologies.
 Technology for energy savings:
        mixed energy sources, small scale energy systems.
 Consumer products, instruments, MEMS.

          Performance, reliability, cost, easy to use and maintain.
        Most significant technological
Two poles:
 Integration
Embedded control systems integrating perception and control functions that can
be used, eventually, in a transparent way.
Reasons: Technological developments (Hardware integration, MEMS, ……) and
new applications (vehicles, autonomous systems, consumer products, biomedical
systems, ……)
 Distribution
Distributed control systems with wire and wireless connections between
components and embedded controllers.
Reasons: Communications technology and new applications (Tele- applications,
distributed manufacturing, protection of people and environment, home
automation, ….)
        The single trend/forecast

Integration of control and perception components in
embedded systems that could be networked using
wire or wireless technologies.

         AUGUST, 2003


      Presenter: Philipp Nenninger
Control of systems distributed
over communication networks

   R.Bars, A.Isidori, P. Nenninger, A.Ollero
• More and more systems are becoming distributed,
  consisting of a large number of components of a
  very different nature, which exchange information
  through wire/wireless networks (“Wireless
  communications in the loop”)
• While control, information theory &
  communication are mature disciplines, little effort
  has been put so far in understanding how issues in
  information theory affects the performance of a
  distributed control system
       Theoretical Challenges
• Design of
  – Encoders
  – Decoders
  – Communication channels
  – Controllers / estimators
  To achieve prescribed performances with
    minimum loss, high efficiency and with
    decisions made by a large number of users
            Theoretical Challenges
• Quantitative analysis of how the performance of
  the system is affected by
    –   Bandwidth
    –   Delays
    –   Quantization errors
    –   Transmission noise, loss of information
•   Data handling / control of data flow
•   Safety / reliability issues
•   Conflict resolution / avoidance of deadlocks
•   Resource allocation
    Emerging Application Areas
 Technologies for safety critical and hostile environments
 Remote control and coordination of unmanned vehicles
  (UAV, UGV, AUVs)
 Telepresence
 Remote laboratory
 Remote surgery
 Distributed manufacturing
 Home automation
 Ubiquitous sensors

         AUGUST, 2003


        Presenter: Shimon Nof
    Trends in Collaboration

              Presented by

            Shimon Y. Nof
      Purdue University, USA

           Stephen Kahne
   Embry Riddle University, USA

For the IFAC Technical Board Meeting
      Rotterdam, Holland, August 2003
                        Machine – Machine
Overall Trend: Smart robotic teams (normal, micro, nano robots) will
  be able to interact even better than human teams
Trend 1. Collaborative Coordination Control Theory
    • Safety is critical
   • Enable unmanned manufacturing and maintenance
Trend 2. Control Methods to Manage faults, errors, conflicts,
       and interactions
    • Save money
   • Improve product uniformity
Trend 3. Control Protocols for fault-tolerant, time-out
               integration of information signals
    • Future collaborative machines will depend on cheaper, redundant
       arrays/networks (e.g., FTTP)
                          Human -- Human
Overall Trend: Smart tools and collaboration will enable
     significantly better complex system performance
Trend 1. Interoperability of software for enterprise applications
      • Integration of team decision support,
               e.g. air traffic control, ERP, supply networks
Trend 2. Coordination of team members’ interactions
     • Geographic remoteness of collaborating members
      • Members have different databases, culture, knowledge
Trend 3. Optimization of parallelism among resources
      • Two (or more) heads are better than one
      • Overcome overload of tasks
                         Human -- Machine
Overall Trend: Better understanding of how to share tasks
Trend 1. Impedance matching
      • Software
      • Human factors -- information usability
      • Process goals adjustment-adaptation (learning)
Trend 2. Performance monitoring
      • Better displays
      • New forms of feedback
Trend 3. New sensors and actuators
      • Fly by “everything” e.g. , by wire , light
      • Understand who is the human customer/partner/user

 Collaboration in distributed operational systems
  is critical

 Collaboration must be optimized to benefit from
  respective strengths of the partners

 Control theory and applications must be
  developed and verified to enable this new
  control environment trend

          AUGUST, 2003


        Presenter: Hans Driessen
      IFAC Emerging Areas
    Panel Session Presentation

Hybrid/Discrete Event Systems/Networks
    Hans Driessen
    Thales, The Netherlands

    Pedro Albertos
    Universidad Politecnica de Valencia, Spain
   Hybrid/Discrete Event Systems/Networks
Continuous (and discrete) time systems at one hand and discrete
event systems on the other hand have been studied / developed
independently of each other, but often appear in the same process.
An incomplete list of application areas is:
distributed control systems, autonomous systems, manufacturing,
process control (start-up/shut down), radar processing &

1. What is the forecast?

The forecast is that we will see a combined treatment in the future.
2. Why is this forecast likely to happen?

This is due to the ever higher performance requirements, e.g. a
shorter dead-time. Also better use of the resources, Embedded
systems, and Integrated control design.
 Hybrid/Discrete Event Systems/Networks
3. When is this forecast likely to happen?
Theoretical developments are taking place right now.

Theoretical Challenges
• Integrate the control design and its implementation
• Develop the joint theory for hybrid systems and their control
• Include the delays and randomness of the communication

Applications will appear in coming years.
Hybrid/Discrete Event Systems/Networks

4. What will be the impact when this happens?
Higher performance of systems. Broader spectrum of
applications. Increased reliability and autonomy.
5. Are there any adverse effects of this development?

Increased complexity of the problem /solutions
6. What must happen for this forecast to come true?

Combine different fields, people, even language:
- Control and Real Time SW expertise (difficult)
- Continuous/discrete time control and discrete event systems
(easier to combine)
 Hybrid/Discrete Event Systems/Networks

Some of these ideas can be illustrated with a typical area of
applications: namely, radar systems.

In radar processing we encounter dynamic estimation
problems including both discrete and continuous state
variables. The discrete variables amount to whether an object
is present or not, whether it is maneuvering or not, what type
of object it is from a known class of possible objects. So in
fact there are simultaneous, dynamic, stochastic
detection/estimation/classification problems.

In radar management we encounter both continuous and
discrete parameters to be selected on-line for every
transmission in order to maximize performance. This involves
calculations of expected performance for hybrid systems and
control schemes for obtaining the maximum of performance.
Hybrid/Discrete Event Systems/Networks
            Illustrations … Continued
Up to now most of the simultaneous detection / estimation /
classification problems are treated sequentially, more or less
independent: so we first try to detect, then estimate, and then
classify. This is sub-optimal and leads to all kind of smart and
tricky algorithms. This is not only sub-optimal, but also hard
to reuse from application-to- application. Significant
performance improvements can be obtained by solving the
problems simultaneously, but this induces a computational
problem that cannot be solved with traditional techniques, or
at least very difficult.
Particle filtering, or Sequential Monte Carlo filtering, is a
technique that is very well-suited for solving problems
including discrete variables, nonlinearities, constraints etc.
These algorithms lead to well-understood algorithmic
solutions that are easily re-used, saving considerable
development time and costs.

        AUGUST, 2003


       Presenter: Anibal Ollero
     Panel Session Presentation
“Autonomous Systems”
                 A. Ollero (Univ. Sevilla, Spain),
R. Babuska (Delft University of Technology, The Netherlands) and
             H. Vander Auwerarer (IMS, Belgium)
  Industry Trend: Advanced Vehicle
Increasing role of vehicle electronics.
Current functionality:
   Engine control
   Driver assistance (ABS, ESP, distance detection…)
   Suspension control (mainly semi-active)
   Diagnostics (ABS…)
   Comfort (climate control, lighting, seats…)
   Supported by standards such as CAN bus etc.
 Industry Trend: Advanced Vehicle
Emerging functionality:
  X-by-wire: drive-by-wire, brake-by-wire….
  Driver assistance (parking assistance, speed control,
   dangerous maneuvering…)
  Active safety measures (collision warning, pedestrian
  Active suspension control
  Active noise and vibration control
  Telematics (on-board e-services, navigation and beyond)
                Autonomous systems
 Autonomous vehicles:
   UAV, UGV, AUVs, multiple vehicles
 Autonomous functions in conventional vehicles (cars,
  aircraft, vessels, ..)
   Driver overrule (collision avoidance, lane control, ..)
 Intelligent Traffic Control
 Technologies for safety-critical and hostile environments:
      space, disaster remediation, defense, ..
   Combination of autonomy and Teleoperation.
 Unmanned plants.

Application of learning, uncertainty handling and AI techniques.
Autonomous perception.
Reactivity and planning techniques.
Reliability is a main issue.

     AUGUST, 2003


             Closing Comments
The “comments” on the following slides were received
  after the Workshop and Panel Discussion. These
  comments do not necessarily represent the collective
  opinions of the participants, but rather the individuals
  who submitted them. These comments are provided to
  stimulate further discussion of this important subject.

If you would like to contribute additional comments,
   please sent them to Mike Masten at
   m.masten@ieee.org Comments regarding trends that
   you believe will be highly significant within our field
   are especially welcome. We will periodically update
   this section of this presentation if such comments are
I wrote down some remarks/items on which I will be happy to contribute
The summary discussion highlighted some of the developments (in theory,
  technology and applications) that are linked to our field of research. It
  appeared to me that the audience liked the structured way in which
  Shimon Nof presented the different trends: M-M, H-H, H-M. It was hard
  to find trends (in his and other presentations) that did not imply 'more of
  the same or make things better' (in terms of reliability, working domain,
It should be stated that complexity is the enemy of reliability. Hence,
    understanding complexity and trying to cope with it are key issues in
    theory and technology developments and in the design of applications.
    Trends that host 'the complexity virus' are the drive to increase
    automation, implement intelligent (autonomous) sensor- and actuator
    systems, link/teleconnect systems that are different in nature (causing all
    kinds of unexpected 'dynamics') and that are at a far distance.
I personally disagree that the gap between practical problems and research at
   the university is so big. I think industry is not capable to formulate their
   problems such that these can be worked on by academia and serve as an
   educational podium. Industry and academia have different missions!
I hope these remarks are helpful for further discussion.
 Peter A. Wieringa Man-Machine Systems, Mechanical Engineering
 Faculty of Design & Engineering, Delft University of Technology TU Delft
I am uncomfortable with Peter Wieringa's comments. He more or less
   reduces the sense of urgency to close the gap between academia
   and industrial practice (the well known time-delay), whereas in the
   Panel Discussion we were quite in agreement about the gap and
   the need to overcome it. Remarks made at the end of the session
   about the thoroughness of the meeting clearly suggested that we
   should repeat these kind of sessions and to devote more time to
   this challenge.
Anonymous Comment

I agree the gap between practical problems and university research is
   not that large, but we should not try to identify who is responsible
   for the gap. I believe we have to avoid a formulation where it may
   appear that the problem is in "the other camp". The most fruitful
   approach, which was also the spirit of the panel meeting, is "What
   we can learn from each other", industry by (early) understanding
   the trends in fundamental research (what is possible), academia by
   understanding the (long-term) industrial needs and applications
   (what is needed, where can this be actually used). While the
   missions are indeed different, in the long run, they touch. We both,
   industry and academia, have to look beyond the scope of our
   classical, daily, way of thinking, and this requires efforts from both
   sides. The result is a cross-fertilization of ideas, methods and
   applications that does not follow a simple linear model (such as:
   industry needs -> university develops -> industry uses). I am
   convinced many good examples of such efforts exist and I felt that
   the panel meeting was held in this spirit.
Herman Van der Auweraer
I do not fully agree with the remark of Peter Wieringa saying that
   industry is not capable to formulate their problems such that these
   can be worked on by academia ... etc. I accept it as a personal
   remark and opinion, but we should perhaps be a little careful that
   IFAC is not identified with this (slightly arrogant) view.
                     THANK YOU
• To IFAC Technical Committee and Coordinating
  Committee Chairs
  – Identification of Potential Forecasts/Trends
  – Presentation of Forecasts/Trends for Consideration
  – Participation in Workshop and Panel Session
• To Industrial Guests
  – Identification & Presentation of Potential Forecasts/Trends
  – Participation in Workshop & Panel Session
  – Evaluation/Feedback at End of Panel Session

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