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LCM lädt zum Workshop "From Cybernetics to Systems Biology: The power of the automatic control paradigm" ein.

Ein vom LCM veranstalteter Workshop zum Thema "From Cybernetics to Systems Biology: The power of the automatic control paradigm". Durchgeführt von Herrn Prof. Dr.-Ing. Frank Allgöwer.

Ein sehr allgemeiner Vortrag, der für ein breiteres
Publikum geeignet ist:

Networked Cybernetics: From the Classical Feedback
Loop to the New Cybernetics of the 21st Century

Feedback based automatic control has been a key
enabling technology for many technological advances
over the past 80 years. New application domains,
like autonomous cars driving on automated highways,
energy distribution via smart grids, life in smart
cities or the new production paradigm Industry 4.0
do, however, require a new type of cybernetic
systems and control theory that goes beyond the
classical ideas. Starting from the concepts of
feedback and its significance in nature and
technology, we will present in this talk the
new developments and challenges in connection
to the control of interconnected networks of
complex systems.

2. Forschungsvortrag zum Thema data-based control:

Towards a data-based control theory

While recent years have shown rapid progress of learning-
based methods to effectively utilize data for control
tasks, most existing control theoretic approaches still
require knowledge of an accurate system model. It is worth
asking if this trend towards data-driven approaches
will ultimately lead to an obsolescence of classical
systems and control theory. On the other hand, a key
feature of control theory has always been its ability to
provide rigorous theoretical guarantees – something
that the learning community has only recently begun to
In this talk, we present a novel framework for data-driven
control theory, which does not rely on any model knowledge
but still allows to give desirable theoretical guarantees.
This framework relies on a result from behavioral systems
theory, where it was proven that the vector space of all
input-output trajectories of a linear time-invariant
system is spanned by time-shifts of a single measured
trajectory, given that the respective input signal is
persistently exciting. We show how this result can be
utilized to develop a mathematically sound approach to
data-driven system analysis, with the possibility to
verify input-output properties (e.g., dissipation
inequalities) of unknown systems.
Moreover, we propose a novel purely data-driven model
predictive control scheme and we present theoretical
results on closed-loop stability and robustness.
Finally, the presented framework allows us to design
state-feedback controllers with performance guarantees,
even if the data are affected by noise.

3. Ein Forschungsvortrag zum Gebiet MPC:

Industry 4.0: Challenges and Opportunities for
Optimization-based Control

With the vision of the Smart Factory of the future, the
process and manufacturing industries are currently
undergoing a fundamental new Orientation on the basis
of the Cyber-Physical Systems and Internet of Things
and Services paradigms. All parts along the production
chain are nowadays equipped with embedded computing,
communication and networking capabilities and are
expected to interact in an optimal way towards the
goal of an energy and resource efficient, save and
reliable production process. Through decentralized
optimal decision-making and an appropriate
communication among the networked individual parts,
the whole production process of the future is
expected to operate optimally.

After a short introduction to the goals and
principles of Industry 4.0 its challenges and
opportunities for the field of manufacturing and
process control are discussed. We will in particular
investigate the potential impact of the field of
optimization-based control for the fourth industrial
revolution and will present two promising approaches,
namely economic model predictive control and distributed,
cooperative optimization and control.

Economic model predictive control (MPC) is a control
technique which is based on the repeated online solution
of an optimal control problem. Contrary to classical MPC,
the employed cost function can be some general
performance measure, possibly connected to the economics
of the considered process. This allows to also consider
control objectives different from the classical ones of
stabilization or tracking, which makes economic MPC well
suited as a tool to achieve the goals of Industry 4.0.
In this talk, we examine conditions to classify the
optimal operational regime for a system, and propose
economic MPC schemes which allow for closed-loop average
performance guarantees and satisfaction of (standard
pointwise-in-time as well as averaged) constraints.

4. Ein Uebersichtsvortrag aus dem Gebiet Systembiologie
in dem die Anwendungs von regelungstechnischem Wissen
in der Biologie thematisiert wird:

Live & let die – How control theory may contribute
to the cure of cancer

Systems biology is an interdisciplinary approach aimed
towards a better understanding of the physical basis of
life. In this talk the role of systems and control theory
for systems biology will be explored and an introduction
to the field will be given. We will discuss achievements,
potential and problems by exemplarily looking at one
particular approach to cancer treatment that is based on
apoptosis inducing targeted protein therapeutics. We will
show that systems theoretic methods and tools, like for
example passivity-based ensemble control, can play a
valuable role for the understanding of the underlying
dynamical mechanisms.