1. Electronic Control Systems II Week 10 – Final Review
EET273
Electronic Control Systems II
Week 10 – Final Review

2. Control Terminology
Process/Plant – the physical system we wish to monitor and control
Process Variable (PV) – output variable to be controlled
Setpoint (SP) – input to the system, the desired value of the PV
Controller – module that processes system error and drives the plant
Final Control Element (FCE) – actuator that is acting on the process
Manipulated Variable (MV) or Output – Controller output variable that manipulates the plant
Open Loop – no feedback from output to input
Closed Loop – with feedback from output to input

3. Ladder Logic
Circuits are connected between 2 “rails”, and listed from top to bottom in “rungs”, resembling a ladder.
L1 – “hot” AC wire, L2 – “neutral” or grounded wire
All electrically common points are numbered with the same number (and preferably the same color wire, though not always practical)
Fuses are connected to the left rail
Ground fault to center wire causes fuse to blow
Switches are placed on the left rail of the diagram
Loads are placed on the right rail of the diagram (grounded side)
In case of a ground fault, both sides of the load are grounded

4. PLCs Why PLCs? Convenient alternative to relays
Instead of re-wiring a circuit, just load a new PLC program
May be programmed using a ladder logic diagram
Makes existing hardware more versatile:
Have a NO switch, but need a NC switch? Just switch the behavior of X1 in the PLC
“Virtual switches” in the PLC allow a physical switch to used multiple times in different rungs of the PLC ladder logic
Real-time remote monitoring and control via software

5. Proximity Switches
Because proximity switches are active, they typically do not have simple switch terminals like a passive switch would. Instead they either source or sink current
Sinking – sensor sinks current from circuit, NPN type, “low-side”
Source – sensor sourcing current to circuit, PNP type, “high-side”
Notice that emitter is always connected to power rail – common emitter config

6. Switching Example
LED in this circuit will turn on if the liquid level rises above 14 inches AND the pressure falls below 22 PSI AND either the flow is less than 3 gallons per minute OR the temperature is greater than 125°F.
22 psi sensor (NC) is detecting a LOW pressure state, which is the normal state, but not the desired (or typical) state
Similarly, the 3 GPM sensor (also NC) is detecting LOW flow

7. On-delay & Off-delay Relays
On delay relays: delay occurs when coil is energized, no delay when coil is de-energized
Off delay relays: delay occurs when coil is de-energized, no delay when coil is energized
Arrow in symbol represents when delay occurs
Up: energized
Down: de-energized
Can be either NO or NC

8. On-delay & Off-delay Relays
Normally open, timed-close Normally open, timed-open

9. 4–20mA signaling
Most popular form of signal transmission in modern industrial systems
An analog signaling standard
An analog signal is “mapped” to a current range of 4mA – 20mA
4mA
lowest possible signal level
0% of scale
20mA
highest signal level
100% of scale

10. Voltage vs. Current signaling

11. 4–20mA signaling Mapping a 50 - 250°C temperature scale to 4 – 20mA
50°C  4mA
250°C  20mA

12. 4–20mA signaling example

13. Solving using a linear equation
Use y = mx + b  calculate slope, calculate y-intercept
For input: GPM output: 4-20 mA

14. Calibration Errors
Zero shift 
 Span shift

15. Calibration Errors – Linearity errors
The response of an instruments function is no longer a straight line
Cannot be fixed by a zero/span correction, because the response is no longer a linear function
Some instruments offer a “linearity” adjustment, which must be carefully adjusted according to the manufacturer instructions
Often the best you can do is “split the error”, finding a happy medium between error high and low extremes

16. Calibration Errors – Hysteresis errors
Instrument responds differently to an increasing input compared to a decreasing input
This type of error can be detected by testing the instrument going up through the range, then down through the range
Typically caused by mechanical friction
Cannot be rectified through calibration, typically must replace the deflective component

17. Design Criteria
Some control systems have very tight requirements for their outputs, and some are much more loose.
Which controller design you choose is typically based on the output requirements.
Systems with tight requirements:
Drone/quadcopter
Car cruise controller
Systems with more loose requirements:
Liquid buffer tank
Home heating system / thermostat

18. System Performance
What constitutes “good performance” in a system is application specific, and often subjective
3 ways to quantify “good performance” are:
Rise Time
5% - 95% - How quickly does the output go from 5% of the SP to 95% of the SP
Settling Time
Time it takes for output to settle within a certain percentage of the steady state value
Overshoot
More much more than the SP the output reaches on it’s initial overshoot

19. System Performance Rise time
How quickly does the output go from x% of the SP to y% of the SP
Typically 10% - 90% or 5% - 95%

20. System Performance Settling time
Time it takes for output to settle within a certain percentage of the steady state value
Typically defined as 2% or 5% of steady state value

21. System Performance Overshoot
Magnitude of the initial PV overshoot above the SP
Usually defined as a percentage
Ex:
SP = 1V
PV peaks at 1.2V
1.2V – 1V = 0.2V
0.2V / 1V = 20% overshoot

22. Controllers
A controller acts on the error signal (e), to modify the input to the plant
A controller design can be
Simple – on/off control, proportional control
Complex – PID control

23. Controllers
We can simplify this system, using the same formula: TF = G / (1 + GH)
Except now, G is actually K*G
So, the simplification of this system is: TF = KG / (1+ KGH)

24. Controllers
Error is: the different between the system input (SP) and output (PV)
The purpose of feedback is to reduce system error
The purpose of a controller to process the system error in such a way that it reduces error quickly and efficiently
Proportional controllers work by multiplying the error by some scaling constant 𝐾 𝑃 , this is fairly effective but has limitations (creates offset and/or overshoot)

25. On/Off Control
Controller output is binary – either 100% ON or 100% OFF
Very simple control algorithm, switches input on or off based on relationship between process variable (PV) and setpoint (SP)
If PV > USP then
Controller = “OFF”
If PV < LSP then
Controller = “ON”
Some applications this may be fine
Ex. Water level in a buffer tank
Ex. Heating system in your home
Others may require more precise control
Ex. Car cruise control system

26. Proportional Control
Rather than simply comparing the error to a value and making a binary (ON/OFF) decision, we can design a controller to respond to the magnitude of the error
Large error  Large error correction
Small error  Small error correction
A proportional controller simply takes the error, and multiplies it by some scaling factor (gain), commonly known as 𝐾 𝑃
Tuning a proportional controller simply means adjusting or tuning 𝐾 𝑃

27. PID Control P – Proportional I – Integral D – Derivative
A controller can consist of 1 or more of these elements together, depending on the type of system/performance required
P controller
PI controller
PD controller
PID controller
We can use multiple types of controllers in parallel, and sum the outputs of each controller

28. Integral Controllers
For our purposes, the word “integral” can be used interchangeably with “accumulated sum”
An integral controller accumulates the error over time
If there is any steady state error in a system, the integral controller will continue to accumulate this error, and eventually drive it to zero
Because integral controllers only operate on accumulated changes in error, they are slower to respond to error than a proportional or derivative controller

29. Derivative Controller
While a proportional (P) controller is looking at the actual value of the system error, a derivative controller is looking at the slope of the error
Error is increasing quickly  lots of derivative control
Error is stable  very little derivative control
The amount of derivative control is set by the constant 𝐾 𝐷 , (or 𝜏 𝑑 )

30. Derivative Controller
Differential controllers are often used to respond to quick changes in error, and prevent the error from changing too quickly
This can help reduce overshoot coming from the P or I controller
Since the D controller is “keeping an eye out” for sudden changes, we can “get away with” more P and I than we could otherwise (and still avoid overshoot)
Since D controllers respond to the error’s rate of change, they are more susceptible to high frequency noise – so be careful when implementing them!

31. PID Control Proportional: Integral: Derivatives:
Reacts to error in the present
Good for performing the bulk of error reduction
Results in “proportional-only offset”, which can reduced, but never eliminated with proportional only control
Integral:
Reacts to error in the past
Excellent at removing steady state errors
Slow to respond due to time needed to accumulate error
Derivatives:
Reacts to error in the future (anticipates error by looking at slope)
Starts working when error is changing quickly
Stops working when error is constant
Not good at eliminating steady state errors – if error is constant, D controller doesn’t care

32. PID Control

33. PID controllers – different configurations
P: Removes bulk of error, will always have offset (in a loaded system)
I: Completely removes offset (eventually), slower response
PI: Removes error quickly, and eliminates offset, may overshoot
PD: Removes bulk of error, D corrects for overshoot, will have offset
PID: Completely removes offset, responds quickly, D corrects for overshoot

34. Final Exam The Final – Monday 6/10 – 8pm: Two pages of notes allowed
60%: Closed loop control, On/Off Control, PID control
Look at SP/PV graphs, design a basic control strategy, use On/Off, P, PI, or PID?
Look at SP/PV graphs, determine which P/I/D constants might need tuning
Identify control elements, PV, SP, MV, etc.
20%: Signaling/calibration
20%: Ladder logic, relays, switching/sensors
Two pages of notes allowed
You may use a calculator
You should study:
HW’s, quizzes, midterm, final review sheet

35. Notes Highly recommend playing with the Matlab/Octave PID simulator
Final review sheet is posted online under HW section – you do not need to turn this in