IT 435 Digital Instrumentation and Controls

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IT 435 Digital Instrumentation and Controls

• Lecture 6
• Chapter 13

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Closed Loop Control

• Control - adjustment of parameters to achieve and
  maintain a desired condition

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Criteria for Control

• Objective of Control system
• Maintain controlled variable exactly equal to set
  point at all times
• Control criteria answers the question
• How good is it?
• Stability and damping are parameters of merit

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Stability and damping
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Stability and damping

• Step change - typical test of dynamic control
  system
• Reference for How well does the control system
  follow this?
• Critically damped - output gradually rises with
  time and achieves desired value without overshoot
• Over damped - more gradual
• Desired could be achieved more quickly

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Stability and damping

• Under damped - Desired achieved more quickly than
  critically damped
• Some overshoot occurs
• Steady state oscillatory error
• Stable but in- exact
• Sometimes acceptable
• Increasing amplitude response
• Divergent
• Unacceptable

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Stability and damping

• Which is the best?
• None of the above
• Quarter amplitude decay

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Quarter amplitude decay
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Objectives of Control

• Minimize the maximum value of error
• Minimize the settling time
• Minimize the residual error

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Types of Controls

• On-Off
• Proportional
• Integral
• Derivative
• PID
• Fuzzy Logic
• Adaptive

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On-Off Control

• BANG BANG - Two position - On or Off
• Uses a threshold to trigger
• Deadband lies between the on/off threshold
• Usually an acceptable error exists

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On-Off Control
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Proportional Control

• Correction action (control authority) is
  proportional to the error magnitude
• Error doubles then control output doubles
• Doesnt have to be linear
• Squared, cubed, logarithmic, etc

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Proportional Control
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Proportional Control

• Important parameters
• Max error for full on
• Min error for full off
• Offset - crossing point of Y axis
• Non-zero allows easier/quicker adjustment of
  process variable
• Always a signal because of zero error crossing
• Usually an acceptable error exists
• Where control command offsets disturbance
  influence

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Integral Control

• On-Off and Proportional
• Error must be tolerated
• Integral drives the error to zero
• Rate of change (slope) of control output is
  proportional to the error magnitude

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Integral Control
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Integral Control

• At first, regardless of the error, no control
  authority
• As the error persists over time, the control
  authority grows (error x delta time)
• As the error decreases, the increase in control
  authority declines
• When the error reaches zero, the control
  authority remains at the value where zero was
  reached

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Integral Control
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Integral Control

• RESULTS IN ZERO ERROR
• SLOW TO RESPOND

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Proportional - Integral Control

• Combination speeds up response and assures zero
  error eventually

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Proportional - Integral Control
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Derivative Control

• Needed - Exaggerated initial correction to
  overcome resistance to change during first
  instant
• Derivative control command responds only to the
  change in the error signal (slope)
• If the error is constant, derivative command is
  inactive

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Derivative Control
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Proportional - Integral - Derivative (PID)
Control

• Parallel combination of three approaches
• Provides
• QUICK INITIAL RESPONSE
• REASONABLE ERROR CLOSURE RATE
• EVENTUAL ZERO ERROR

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PID Control
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PID Control
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PID Control

• Each parallel control block requires optimization
• Assures stability (proper damping)
• Process of optimization called GAIN selection
• Logical process to achieve best system
• Still somewhat black art

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Fuzzy Logic

• Technique of control based on using empirical
  data (observation) to establish desired response
• Clothes washers
• Automobile transmissions
• Difficult and expensive to implement
• Requires many observations

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Neural Nets

• Mathematical strategy to adapt external sensorial
  inputs as influence coefficients for control
  authority
• Assumed to mimic human brain activity

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Adaptive Control

• Practical method of altering PID and Fuzzy logic
  gains based on observed data
• The results of control influence gains which
  adjust control during the next operation
• In use in some applications
• Complex and potential problems
• Sometimes associated with Safety and Failure Mode
  Effects and Analysis (FMEA)