3 Industrial Automation
Transcript of 3 Industrial Automation
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NON - AUTOMATEDINDUSTRY
Small production
A lot of defective units
Dangerous, repetitive tasks, etc.Non - competitive
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Automation
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Why Automation?
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Why Learn Automation?
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Human in Automation
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Why its Fun?
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Measurement technologies
Sensor technologies
Signal processing
-Sampling
-Application of digital filters
Data handling
-Data validationConnected to supervision
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Communication
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Control
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Supervision
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Modelling and simulation
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Planning and optimization
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Applications of Automation
Car Industry
Paper process
Bleaching Process
Pharmaceutical Industry
Food Industry Micro surgery
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adaptive control designs are able to provideadaptation mechanisms to adjust controller
parameters in the presence of parametric,structural and environmental uncertainties.Nonsmooth nonlinearities such as backlash, dead-zone, component failure, friction, hysteresis,
saturation and time delays are common inindustrial control systems. Such nonlinearities areusually poorly known and may vary with time, andthey often limit system performance
Robust control theory is a method to measure theperformance changes of a control system withchanging system parameters.
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The Neural network is composed of a large
number of highly interconnected processing
elements (neurons) working in parallel to solve a
specific problem. Neural networks process
information in a similar way the human brain does.
The disadvantage is that because the networkfinds out how to solve the problem by itself, its
operation can be unpredictable.
Fuzzy logic is a superset of conventional
(Boolean) logic that has been extended to handlethe concept of partial truth -- truth values between
"completely true" and "completely false".
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