Pid Control Basics

PID Tuning Training Course

Day-1

Day-2

1

PID Control Basics

2

Tuning Tutorial in Centum VP

3

Tune VP Application

4

Tuning using Tune VP in Centum VP

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Page 1

PID Control Basics

1. PID Control Evolution 2. PID Algorithm and its Implementation 3. Process Models 4. PID Controller Tuning Methods 5. PID Tuning Guidelines 6. Regulatory Control Strategies 7. PID Tuning Tutorial

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PID Controller Evolution

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On-Off Control

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On-Off with Dead Band Control

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Proportional Control (TI = 5000 & D =0)

K = 2.4

DMV = K* DE

K = 1.8

K = 1.0

Proportional Control will always have offset Copyright © Yokogawa Electric International Pte Ltd

PI Control (D =0)

K = 1.6 TI = 50

DMV = K* DE + E/TI

K = 1.8 TI = 70

K = 1.0 TI = 300

Adding Integral will eliminate offset Copyright © Yokogawa Electric International Pte Ltd

PID Control Algorithm and Implementation

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PID Basics PID controller PV Process variable

PV

SV

Cold water

DV

SV Setpoint value

MV Manipulated output value

Hot water

MV

Steam

DV Disturbance variable

Steam heating temperature control system Copyright © Yokogawa Electric International Pte Ltd

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PID Algorithm  Tune PID controller parameter (PB, TI, TD) to achieve a satisfied performance

Yokogawa PID

PB  (0-1000) TI  (0.1-10000) TD  (0-10000)

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Control action  Control action  Control action 

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vice versa

Page 10

PID Algorithm - Implementation

PID - Proportional - Integral - Derivative PID Controller – The most widely applied controller in industrial processes DV Proportional

SV

-

PV

+

E

Integral

MV

+

Controlled process Gp

PV

+

+

Derivative

Control system block diagram E=PV-SV (Yokogawa DCS) PV-Process Variable, SV-Set-point Variable, MV-Manipulated Variable, DV-Disturbance Variable Copyright © Yokogawa Electric International Pte Ltd

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PID Algorithm - Implementation Discrete form DMV = K* DE + E/TI + D* DE/ DT

SP

E DE

PV

DMV MV

Current time Copyright © Yokogawa Electric International Pte Ltd

PI Controller – Impact of P & I values

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Process Models

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Dynamic Model of a Level in a Tank

Fin

LT

L Fout

dL  Ac  Fin  Fout dt

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Stirred-Tank Heating Process

V C

dT  wC Ti  T   Q dt

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(2-36)

System: Gas Surge Drum with volume V, inlet and outlet flow rates qi and qo respectively.

Transfer Function of First order system

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Step Response of First Order System

445

84

440

82

435

Engineering Units

80 430 78 425 76 420 74 415

72

410 INPUT OUTPUT 405

70 1

11

21

31

41

51

61

71 Time

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81

91

101

111

121

131

141

Second Order System

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Step Response of Second Order System

445

84

40.00 Input Output

2009.00

440

82

35.00 2007.00

435 80

425

with x  t1/2*t2 > 1 Over-damped

420

415

76

74

2005.00 25.00 2003.00

20.00 2001.00

with x  t1/2*t2 < 1 Under-damped

1999.00 72

410

1997.00

INPUT OUTPUT 405

70 1

11

21

31

41

51

61

71

81

91

Time

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101

111

121

131

141

1995.00 1

6

11

16

21

26

31

36

41

46

51 Time

56

61

66

71

76

81

86

91

96

15.00

10.00

5.00 101

Output - Engineering Units

78

Input - Engineering Units

Engineering Units

30.00 430

Second Order - Zero Gain

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Second Order - Beta

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PID Controller Tuning Methods

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Tuning Methods

1. Open Loop Method 1. Ziegler Nichols 2. Cohen-Coon technique

2. Closed Loop Method 3. Model based Methods 1. Internal Model Control (IMC) Method 2. ISE, IAE & IATE based Methods

4. Manual Tuning - Trial and Error method Copyright © Yokogawa Electric International Pte Ltd

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Ziegler Nichols - Open Loop Method Gp is the process gain the change in measured value (%) divided by the change in output (%)

Gain

Reset

Derivative

P

L/GpD

—

—

PI

0.9 L/GpD 3.33D

—

PID

1.2 L/GpD 2.0D

0.5D

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Cohen-Coon technique - Open Loop Method

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Ziegler Nichols – Closed Loop Method

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IMC(Internal Model Control) Tuning Relations

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ISE, IAE & ITAE Tuning Rules (for non Integrating process)

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PID Tuning Guidelines

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Manual Tuning – Some guide lines(..1) 1.

2. 3. 4.

5.

6.

Before starting the tuning, set the output limits to narrow range around current operating point (MH/ML limits) to clamp the control valve opening limits. If offset is observed, first increase the Gain and then decrease the Integral time. If oscillation is observed high, the increase the TI. If this is not making much impact, then reduce the gain. If the process has dead time, then give TD, but start with small value first. Before giving TD, ensure that PV signal is noise free by using appropriate filter. If it is cascade loop, tune the slave loop first and then tune the master loop. In case of cascade loop, the slave loop should be tuned for faster response.

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Manual Tuning – Some guide lines (..2) Flow Control Loop 1. 2. 3.

Flow is usually controlled using a PI controller. The Signal from the flow sensor is noisy due to turbulent flow so that a large proportional band is used. A small integral time is used for good set point tracking.

Level Control Loop 1. 2.

3. 4.

Most liquid levels provide surge capacity for filtering outflow disturbance. In order to filter outflow disturbances, the level should be controlled loosely. P controller is sufficient, but PI also used for level control. Small Proportional band (PB), Large integral time (I) is used for level controller.

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Manual Tuning – Some guide lines (..3) Pressure Control Loop 1. 2. 3.

The dynamics of pressure in a pressure control loop can be very fast (Flow like) or slow (Level like) depending on the process system. PI controllers are used for pressure loops with a small proportional band and integral time (10 to 250 Sec) for tight pressure control. Tight pressure control is usually desired in most processing situations.

Temperature Control Loop 1. 2. 3. 4. 5.

Moderately slow due to sensor lags and Heat transfer lags. PI and PID Controllers often used. Small Proportional band and medium integral time and small derivative time. Ex: PID controller used for Furnace temp Ex: PI controller used for stripper tray temp

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Manual Tuning – Some guide lines (..4)

Sl No Loop Type Scenario

1

Flow

Integral Action

Derivative Action

Less

More

Nill

Need to control within desired range. P Controller is sufficient but some times PI Controller also used

More

Less

Nill

Generally PI is used

More

Medium Nill

Fast Response (Good SP Tracking, as operator change flow loop set point regularly) Since PV is noisy, we need less proportional PV is generally Noisy action. PI Controller is sufficient

3

Tight control not Level required Tight control Pressure required.

4

Sensor and Heat Transfer Lags. Some Temperat times process will ure have delay

2

Proportional Action

What is required?

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Generally PID Controller is used. But some times PI also sufficient if there is not much delay in the process. These loops generally require very tight control More

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Medium Less

Regulatory Control Strategies

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Simple Feed Back Control

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Cascade Control

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Cascade Control (Terminologies)

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Constraint Handling in PID Controller

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Ratio Control

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Ratio and Feed Back

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Feed Forward and Feed Back

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Split Range Control

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PID Algorithm types

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PID Tuning – Exercise 1. 2.

Tune the given process loop using the following four methods** Record the PID tuning values and Total Absolute Error(TAS) observed

Sl No Tuning Method 1

Trial and Error Method

2

Ziegler Nichols Open Loop Method

3

Ziegler Nichols Closed Loop Method

4

IAE Model Based Method

Controller Gain (K)

Integral Constant (t)

Derivative Constant (d)

Total Absolute Error

3. Which method gives the minimum TAS? 4. In your opinion which method gives best tuning values? And why you think so? **Use the spread sheet provided for each method for finding the tuning value Copyright © Yokogawa Electric International Pte Ltd