Detailed
description of topics:
Recent developments in the field of control
engineering. The role of robustness in stability theory and in performance assessment of
control systems. Model uncertainty, uncertainty modelling in control theory considered
from the points of view of physical system modelling and system identification. Model
based control, predictive control, relationships with classical LQ and LQG approaches. The
role of an observer (state estimating filter) in predictive control and in Internal Model
Control (IMC). Developments in process control applications. The desire in model
predictive control to handle nonlinear process models for prediction and control
computations. The fundamental role of feedback versus feedforward control and trajectory
design.
The design of control systems with two and with three
degrees of freedom. Control along a prescribed trajectory, time-dependent process models.
Control of batch processes.
Implementation environments and structures for control
algorithms: PLC, DCS-system, advanced control, optimal process operation, safety and
alarming systems. Distinction of goals, tasks, opportunities. Interconnection of
continuous-time systems, switching systems, and discrete event systems. Nonlinear control,
status of the formal theory of feedback linearization. Role of nonlinear nonminimum phase
behaviour. Achievements of nonlinear control system design versus approaches from
approximation theory (neural networks) and heuristics (fuzzy control). High-gain feedback
in mechanical servomechanisms, sliding mode control. Suppression of chatter and
limitations in steady state behaviour. Learning and repetitive approaches.
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References
from literature:
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[1] ISBN: [0-13-006305-3] Lin,Ching-Fang, Advanced
Control Systems Design, Prentice Hall, Inc., Englewood Cliffs, NJ, 1994.
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[2] ISBN: [0-19-509119-1] Ogunnaike,B.A. Ray,W.H.,
Process Dynamics, Modeling, and Control, Oxford University Press, Inc., New York, NY, USA
1994.
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[3] ISBN: [0-13-280645-2] Dahleh,M.A.
Diaz-Bobillo,I.J., Control of Uncertain Systems. A Linear Programming Approach Prentice
Hall, Inc., Englewood Cliffs, NJ, 1995.
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[4] ISBN: [4-431-70109-5] Hirota,K. (Ed.), Industrial
Applications of Fuzzy Technology, Springer Verlag, Tokyo, Japan 1993.
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[5] ISBN: [3-486-22287-2] Lunze,J., Kuenstliche
Intelligenz fuer Ingenieure Bd.I: Methodische Grundlagen und Softwaretechnologie
R.Oldenbourg Verlag, München, BRD, 1994.
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[6] ISBN: [3-540-19707-9] Moore,K.L., Iterative
Learning Control for Deterministic Systems, Springer Verlag, London, UK, 1993.
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