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TOPIC LIST FOR 2026

1. ALL ABOUT INSTRUMENTION ENGINEERING - JAN 26

2.ALL ABOUT ELECTICAL ENGINEERING - FEB 26

3.ALL ABOUT MECHANICAL ENGINEERING -MARCH 26

4.ALL ABOUT ROBOTICS ENGINEERING -APRIL 26

5.ALL ABOUT INDUSTRIAL ENGINEERING -MAY 26.

6.ALL ABOUT INDUSTRIAL DCS PROGRAMMING OF Yokogawa CENTUM VP 3000,ABB DCS 800 Ax. Schneider DCS Unity Pro , Fobrbes Marshall Cosys & SCADA/ Graphics: Intouch, RS View32, , Win CC V7.Panel builder ,Yokogawa Graphics builder, CitectSCADA, Wonderware InduSoft Web Studio -
JUNE 26.

2022-08-02T07:46:00.006-07:00

CHAPTER 1.2 allen bradley DL3500-DH+/DH485 CABLE WIRING

2022-08-02T07:36:00.000-07:00

chapter 2.0 specification for RS 232 RS423 RS 422 RS 485

2022-08-02T07:28:00.004-07:00

chapter 1.1 plc cable allen bradley (ab cp10 1784

2022-08-02T07:20:00.002-07:00

chapter 1 plc cable allen bradley (ab pm02 1761)

2022-08-02T07:07:00.002-07:00

it is bike wiring basic automotive .

2022-08-02T06:58:00.002-07:00

today, i am starting from car wiring about automotive basic .

2021-06-08T23:46:00.005-07:00

After 4 years Gap ... I AM BACK FOR INTRODUCED TO YOU ENGINEERING BASIC ..COMING SOON

WEIGHT CALCULATOR :

2017-12-29T10:29:00.000-08:00

WEIGHT CALCULATOR :

Standard conversion factors

INCH * 25.4 = MILLIMETRE

FOOT * 0.3048 = METRE

YARD * 0.9144 = METRE

MILE * 1.6093 = KILOMETER

ACRE * 0.4047 = HECTARE

POUND * 0.4536 = KILOGRAM

DEGREE FARENHEIT * 5/9 - 32 = DEGREE CELSIUS

MILLIMETRE * 0.394 = INCH

METRE * 3.2808 = FOOT

METRE * 1.0936 = YARD

1)MILD STEEL (MS)

SHEET

WEIGHT (KGS) = LENGTH (MM) * WIDTH (MM) * 0. 00000785 * THICKNESS

EXAMPLE = THE WEIGHT OF MS SHEET OF THICKNESS 1 MM AND SIZE 1250 MM * 2500 MM SHALL BE

2500MM * 1250 MM * 0.00000785 * 1 = 24=53 KGS/ SHEET

2.ROLLED STEEL CHANNELS

Designation Weight / Metre Depth of Section Width of Flange

Kg mm mm

ISMC 75 7.14 75 40

ISMC 100 9.56 100 50

ISMC 125 13.1 125 65

ISMC 150 16.8 150 75

ISMC 175 19.6 175 75

ISMC 200 22.3 200 75

ISMC 225 26.1 225 80

ISMC 250 34.2 250 80

ISMC 300 36.3 300 90

ISMC 350 42.7 350 100

ISMC 400 50.1 400 100

3.ROLLED STEEL BEAMS

DESIGNATION WEIGHT / METRE DEPTH OF SECTION WIDTH OF FLANGE

ISMB 100 11.5 100 75

ISMB 125 13.2 125 75

ISMB 150 15.0 150 80

ISMB 175 19.5 175 90

ISMB 200 25.9 200 100

ISMB 225 38.1 225 110

ISMB 250 37.3 250 125

ISMB 300 45.1 300 140

ISMB 350 52.9 350 140

ISMB 400 62.6 400 140

ISMB 500 87.7 500 180

4.MS SQUARE

WEIGHT (KGS ) = WIDTH * WIDTH * 0.00000785 * LENGTH.

Example : A Square of size 25mm and length 1 metre then the weight shall be.

25 * 25 * .00000785 * 1000mm = 4.90 kgs / metre

5.MS ROUND

WEIGHT (KGS ) = 3.14 * 0.00000785 * ((diameter / 2)*( diameter / 2)) * LENGTH.

Example : A Round of 20mm diameter and length 1 metre then the weight shall be.

3.14 * 0.00000785 * ((20/2) * ( 20/2)) * 1000 mm = 2.46 kgs / metre

6.SS ROUND

DIA (mm) * DIA (mm) * 0.00623 = WEIGHT PER METRE

7. SS / MS Pipe

OD ( mm) - W.Tthick(mm) * W.Thick (mm) * 0.0248 = Weight Per Metre

OD ( mm) - W.Tthick(mm) * W.Thick (mm) * 0.00756 = Weight Per Foot

8.SS / MS CIRCLE

DIA(mm) * DIA (mm) * THICK(mm) * 0.0000063 = Kg Per Piece

9.SS sheet

Length (Mtr) * Width (Mtr) * Thick(mm) * 8 = Weight Per Piece

Length (ft) * Width (ft) * Thick(inch) * 3 /4 = Weight Per Piece

10S.S HEXAGONAL BAR

DIA (mm) * DIA (mm) * 0.00680 = WT. PER Mtr

Dia (mm) * Dia (mm) * 0.002072 = Wt. Per foot.

13BRASS SHEET

WEIGHT (KGS) = LENGTH (MM) * BREADTH (MM) * 0. 0000085 * THICKNESS

EXAMPLE = THE WEIGHT OF BRASS SHEET OF THICKNESS 1 MM , LENGTH 1220 MM AND BREADTH 355 MM SHALL BE

1220 * 355 * 0.0000085 * 1 = 3.68 Kgs / Sheet

14COPPER SHEET

WEIGHT (KGS) = LENGTH (MM) * BREADTH (MM) * 0. 0000087 * THICKNESS

EXAMPLE = THE WEIGHT OF BRASS SHEET OF THICKNESS 1 MM , LENGTH 1220 MM AND BREADTH 355 MM SHALL BE

1220 * 355 * 0.0000087 * 1 = 3.76 Kgs / Sheet

15.BRASS / COPPER PIPE

OD (mm) - THICK (mm) * THICK(mm) * 0.0260 = WEIGHT PER METRE

ALUMINIUM SHEET

WEIGHT (KGS) = LENGTH (MM) * BREADTH (MM) * 0. 00000026 * THICKNESS

EXAMPLE = THE WEIGHT OF ALUMINIUM SHEET OF THICKNESS 1 MM , LENGTH 2500 MM AND BREADTH 1250 MM SHALL BE

2500 * 1250 * 0.0000026 * 1 = 8.12 Kgs / Sheet

ALUMINIUM PIPE

OD (mm) - THICK(mm) * THICK(mm) *0.0083 = WEIGHT PER METRE

Bolt name and its type

2017-01-18T22:02:00.000-08:00

Really helpful for engineering persons

Allen Bradley plc analog scaling

2015-08-17T09:31:00.003-07:00

SCL INSTRUCTION

FOR ANALOG INPUT:-

In case of Micrologix -1000 A for current signal (4 to 20 mA),

Max Value for i/p = 31230 (Approx.)

So min value at 4 mA = 31230*4/20 = 6246 (Approx.)

Let the range of RTD is 0 to 400 degree C.

To calculate the value of rate & offset please use following formula.

1). Rate = (scaled max. - scaled min.) * 10000 / (input max. - input min.)

= (400 – 0) * 10000 / (31230-6246)

Rate = 160

2). Offset = scaled minimum - (input minimum x rate)

= 0 – (6246 * .0160)

Offset = -100

FOR ANALOG OUTPUT

In case of Micrologix -1000 A for current signal (4 to 20 mA),

To use the AI double click on I/O Configuration & then I/O Setup.

Select the o/p mode (may be current or voltage, which you want to use).

If you want to provide 0 to 10 V signal on o/p then the value at O:0.4 should be 0 to 31230 (Approx.).

Remote IOS of Allen-Bradley

2015-08-17T09:10:00.000-07:00

change the ip address of local and remote IOS of Allen-Bradley

start stop logic in rs logix 5000 by using emote IOS of Allen-Bradley

Allen-Bradley plc remote ios communication with intouch ad rs view scada

2015-08-17T08:02:00.001-07:00

Allen-Bradley compact logic 1769 BY using Ethernet adopter

connected to remote ios and communication to Review32 and
Intouch scada

abb positioner (tzidc) for control valve calibration procedure

2015-08-15T21:44:00.001-07:00

Abb positioner manual checking and opening of control valve:

A.Press Mode key for 3 sec untill parameter

1.3 MAN_SENS

then release the Mode key

B.now showing SENS_POS which is -25 degree or any other reading.this is zero or 0 % close postion of the control valve.

C.For 100% opening press both keys: 1^st up errow key with 2^nd errow dowen key untill valve not open 100 %.then release the both key.

Note: alwayes keep the control valve at zero position befor exit SENS_POS parameter.

Abb positioner Auto caliberation of control valve:

A.Press Mode key for 5 sec untill parameter

ADJ_LIN

then release the Mode key

B.auto caliberation working 10 to 100 % Run

c. end of caliberation .

PID Control

2015-05-05T07:36:00.002-07:00

PID ControlOverall Course Objectives

• Develop the skills necessary to function as an industrial process control engineer.

– Skills

• Tuning loops

• Control loop design

• Control loop troubleshooting

• Command of the terminology

– Fundamental understanding

• Process dynamics

• Feedback control

PID Controls

• Most common controller in the CPI.

• Came into use in 1930’s with the introduction of pneumatic controllers.

• Extremely flexible and powerful control algorithm when applied properly.

General Feedback Control Loop Closed Loop Transfer Functions

• From the general feedback control loop and using the properties of transfer functions, the following expressions can be derived:

Characteristic Equation

• Since setpoint tracking and disturbance rejection have the same denominator for their closed loop transfer functions, this indicates that both setpoint tracking and disturbance rejection have the same general dynamic behavior.

• The roots of the denominator determine the dynamic characteristics of the closed loop process.

• The characteristic equation is given by:

Feedback Control Analysis

• The loop gain (K_cK_aK_pK_s) should be positive for stable feedback control.

• An open-loop unstable process can be made stable by applying the proper level of feedback control.

Characteristic Equation Example

• Consider the dynamic behavior of a P-only controller applied to a CST thermal mixer (K_p=1; t_p=60 sec) where the temperature sensor has a t_s=20 sec and t_a is assumed small. Note that G_c(s)=K_c.

Example Continued- Analysis of the Closed Loop Poles

• When K_c =0, poles are -0.05 and -0.0167 which correspond to the inverse of t_p and t_s.

• As K_c is increased from zero, the values of the poles begin to approach one another.

• Critically damped behavior occurs when the poles are equal.

• Underdamped behavior results when K_c is increased further due to the imaginary components in the poles.

In-Class Exercise

• Determine the dynamic behavior of a P-only controller with K_c equal to 1 applied to a first-order process in which the process gain is equal to 2 and the time constant is equal to 22. Assume that G_s(s) is equal to one and G_a(s) behaves as a first-order process with a time constant of 5.

PID Control Algorithm

Definition of Terms

• e(t)- the error from setpoint [e(t)=y_sp-y_s].

• K_c- the controller gain is a tuning parameter and largely determines the controller aggressiveness.

• t_I- the reset time is a tuning parameter and determines the amount of integral action.

• t_D- the derivative time is a tuning parameter and determines the amount of derivative action.

Transfer Function for a PID Controller

Example for a First Order Process with a PI Controller

Example of a PI Controller Applied to a Second Order Process

Properties of Proportional Action

• Closed loop transfer function base on a P-only controller applied to a first order process.

• Properties of P control

– Does not change order of process

_–Closed loop time constant is smaller than open loop t_p

_–Does not eliminate offset.

Offset Resulting from P-only Control Proportional Action for the Response of a PI ControllerProportional Action

• The primary benefit of proportional action is that it speedup the response of the process. Properties of Integral Action

• Based on applying an I-only controller to a first order process

• Properties of I control

– Offset is eliminated

– Increases the order by 1

– As integral action is increased, the process becomes faster, but at the expense of more sustained oscillations

Integral Action for the Response of a PI Controller Integral Action

• The primary benefit of integral action is that it removes offset from setpoint.

• In addition, for a PI controller all the steady-state change in the controller output results from integral action.

Properties of Derivative Action

• Closed loop transfer function for derivative-only control applied to a second order process.

• Properties of derivative control:

– Does not change the order of the process

– Does not eliminate offset

– Reduces the oscillatory nature of the feedback response

Derivative Action for the Response of a PID Controller Derivative Action

• The primary benefit of derivative action is that it reduces the oscillatory nature of the closed-loop response.

Position Form of the PID AlgorithmProportional Band

• Another way to express the controller gain.

• K_c in this formula is dimensionless. That is, the controller output is scaled 0-100% and the error from setpoint is scaled 0-100%.

• In more frequent use 10-15 years ago, but it still appears as an option on DCS’s Conversion from PB to K_c

• Proportional band is equal to 200%.

• The range of the error from setpoint is 200 psi.

• The controller output range is 0 to 100%.

Conversion from K_cto PB

• Controller gain is equal to 15 %/ºF

• The range of the error from setpoint is 25 ºF.

• The controller output range is 0 to 100%.\

Digital Equivalent of PID Controller

• The trapezoidal approximation of the integral.

• Backward difference approximation of the first derivative

Digital Version of PID Control Algorithm Velocity Form of PID Controller

• Note the difference in proportional, integral, and derivative terms from the position form.

• Velocity form is the form implemented on DCSs.

Correction for Derivative Kick

• Derivative kick occurs when a setpoint change is applied that causes a spike in the derivative of the error from setpoint.

• Derivative kick can be eliminated by replacing the approximation of the derivative based on the error from setpoint with the negative of the approximation of the derivative based on the measured value of the controlled variable, i.e.,

Correction for Aggressive Setpoint Tracking

• For certain process, tuning the controller for good disturbance rejection performance results in excessively aggressive action for setpoint changes.

• This problem can be corrected by removing the setpoint from the proportional term. Then setpoint tracking is accomplished by integral action only.

The Three Versions of the PID Algorithm Offered on DCS’s

• (1) The original form in which the proportional, integral, and derivative terms are based on the error from setpoint

Guidelines for Selecting Direct and Reverse Acting PID’s

• Consider a direct acting final control element to be positive and reverse to be negative.

• If the sign of the product of the final control element and the process gain is positive, use the reverse acting PID algorithm.

• If the sign of the product is negative, use the direct acting PID algorithm

• If control signal goes to a control valve with a valve positioner, the actuator is considered direct acting.

Level Control Example

• Process gain is negative because when flow out is increased, the level decreases.

• If the final control element is direct acting, use direct acting PID.

• For reverse acting final control element, use reverse acting PID.

In-Class Exercise

• Write the position form of the PID algorithm for Example 3.4, and assume that the control valve on the feed line to the mixer has an air-to-close actuator. Use the form that is not susceptible to derivative kick. Specify whether the controller is a direct-acting or reverse-acting controller.

In-Class Exercise

• Write the velocity form of the PID algorithm for Example 3.1, and assume that the control valve on the feed line to the mixer has an air-to-open actuator. Use the form that is not susceptible to derivative kick or proportional kick. Specify whether the controller is a direct-acting or reverse-acting controller.

Filtering the Process Measurement

• Filtering reduces the effect of sensor noise by approximating a running average.

• Filtering adds lag when the filtered measurement is used for control.

• Normally, use the minimum amount of filtering necessary.

• f- filter factor (0-1)

Feedback Loop with Sensor Filtering

Effect of Filtering on Closed Loop Dynamics

Analysis of Example

• t_f is equal to Dt (1/f-1) as f becomes small, t_f becomes large.

• As t_f is increased, t_p’ will increase.

• Critical issue is relative magnitude of t_f compare to t_p.

Effect of the Amount of Filtering on the Open Loop Response

Effect of a Noisy Sensor on Controlled Variable without Filtering

Effect of a Noisy Sensor on Controlled Variable with Filtering

An Example of Too Much and Too Little Filtering

Relationship between Filter Factor (f), the Resulting Repeatability Reduction Ratio (R) and the Filter Time Constant (t_f)

Key Issues for Sensor Filtering

• To reduce the effect of noise (i.e., R is increased), f must be reduced, which increases the value of t_f. Filtering slows the closed-loop response significantly as t_fbecomes larger than 10% of t_p.

• The effect of filtering on the closed-loop response can be reduced by increasing the frequency with which the filter is applied, i.e., reducing Dt_f.

PID Controller Design Issues

• Over 90% of control loops use PI controller.

• P-only: used for fast responding processes that do not require offset free operation (e.g., certain level and pressure controllers)

• PI: used for fast responding processes that require offset free operation (e.g., certain flow, level, pressure, temperature, and composition controllers)

Integrating Processes

• For integrating processes, P-only control provides offset-free operation. In fact, if as integral action is added to such a case, the control performance degrades.

• Therefore, for integrating processes, P-only control is all that is usually required.

PID Controller Design Issues

• PID: use for sluggish processes (i.e., a process with large deadtime to time constant ratios) or processes that exhibit severe ringing for PI controllers. PID controllers are applied to certain temperature and composition control loops. Use derivative action when:

Comparison between PI and PID for a Low q_p/t_p Ratio

Analysis of Several Commonly Encountered Control Loops

• Flow control loops

• Level control loops

• Pressure control loops

• Temperature control loops

• Composition control loops

• DO control loop

• Biomass controller

Flow Control Loop

• Since the flow sensor and the process (changes in flow rate for a change in the valve position) are so fast, the dynamics of the flow control loop is controlled by the dynamics of the control valve.

• Almost always use PI controller.

Deadband of a Control Valve

• Deadband of industrial valves is between ±10%-±25%.

• As a result, small changes in the air pressure applied to the valve do not change the flow rate.

Deadband of Flow Control Loop

• A control valve (deadband of ±10-25%) in a flow control loop or with a positioner typically has a deadband for the average flow rate of less than ±0.5% due to the high frequency opening and closing of the valve around the specified flow rate.

Level Control Loop

• Dynamics of the sensor and actuator are fast compared to the process.

• Use P-only controller if it is an integrating process.

Pressure Control Process

• The sensor is generally faster than the actuator, which is faster than the process.

• Use P-only controller if it is an integrating process otherwise use a PI controller.

Temperature Control Loop

• The dynamics of the process and sensor are usually slower than the actuator.

• Use a PI controller unless the process is sufficiently sluggish to warrant a PID controller.

Analysis of PI Controller Applied to Typical Temperature Loop

Further Analysis of Dynamic of a Typical Temperature Control Loop

• Note that as the controller gain is increased, i.e., K_cK_p increase, the closed loop time constant becomes smaller.

• Also, note that as the controller gain is increased, the value of z decreases.

Composition Control Loop

• The process is usually the slowest element followed by the sensor with the actuator being the fastest.

• Use a PI controller unless the process is sufficiently sluggish to warrant a PID controller.

DO Control Loop

• The process and the sensor have approximately the same dynamic response.

• This is a fast responding process for which offset-free operation is desired. Therefore, PI controller should be used.

Biomass Controller

• The process for this system is the slowest element.

• Because the process is a high-order sluggish process, a PID controller is required.

Overview

• The characteristic equation determines the dynamic behavior of a closed loop system

• Proportional, integral, and derivative action each have unique characteristics.

• There are a number of different ways to apply a PID controller.

• Use a PI controller unless offset is not important or if the process is sluggish.

• When analyzing the dynamics of a loop, consider the dynamics of the actuator, the process, and the sensor separately.

Engineering books

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Control Loop Hardware and Troubleshooting

2010-07-11T00:11:00.000-07:00

Chapter

Control Loop Hardware and Troubleshooting

Overall Course Objectives

• Develop the skills necessary to function as an industrial process control engineer.

– Skills

• Tuning loops

• Control loop design

• Control loop troubleshooting

• Command of the terminology

– Fundamental understanding

• Process dynamics

• Feedback control

Control Relevant Aspects of Control Loop Hardware

• Necessary for control loop troubleshooting:

– To determine if each subsystem (control computer, actuator system, and sensor system) is functioning properly

– To understand the proper design and operation of all the components that make-up each of the subsystems of a control loop

Control Diagram of a Typical Control Loop

Components and Signals of a Typical Control Loop

Controllers/Control Computers

• Pneumatic controllers

• Electronic analog controllers

• Supervisory control computers

• Distributed Control Systems (DCS)

• Fieldbus technology

Pneumatic Controllers - Phase I

• Introduced in the 1920’s

• Installed in the field next to the valve

• Use bellows, baffles, and nozzles with an air supply to implement PID action.

• Provided automatic control and replaced manual control for many loops

Pneumatic Controllers - Phase II

• Transmitter type pneumatic controllers began to replace field mounted controllers in the late 1930’s.

• Controller located in control room with pneumatic transmission from sensors to control room and back to the valve.

• Allowed operators to address a number of controllers from a centralized control room.

Pneumatic Controller Installation

Electronic Analog Controllers

• Became available in the late 1950’s.

• Replaced the pneumatic tubing with wires.

• Used resistors, capacitors, and transistors based amplifiers to implement PID action.

• Out sold pneumatic controllers by 1970.

• Allowed for advanced PID control: ratio, feedforward, etc.

Electronic Controller Installation

Computer Control System

• Based upon a mainframe digital computer.

• Offered the ability to use data storage and retrieval, alarm functions, and process optimization.

• First installed on a refinery in 1959.

• Had reliability limitations.

Supervisory Control Computer

Distributed Control System- DCS

• Introduced in the late 1970’s.

• Based upon redundant microprocessors for performing control functions for a part of the plant. SUPERIOR RELIABILITY

• Less expensive per loop for large plants.

• Less expensive to expand.

• Facilitates the use of advanced control.

DCS Architecture

DCS and Troubleshooting

• The data storage and trending capability of a DCS greatly facilitate troubleshooting control problems. That is, the sources of process upsets can many times be tracked down through the process by trending a group of process measurements until the source of the process upset is located.

Control Relevant Aspects of a DCS

• The most important control aspect of a DCS is the cycle time for controller calls. The shortest cycles times are typically around 0.2 seconds while most loops can be executed every 0.5 to 1.0 seconds. These cycle times affect flow control loops and other fast control loops.

PLCs

• PLCs can withstand has industrial enviroments.

• PLCs are used for discrete and continuous control.

• Discrete control is used for startup and shutdown and batch sequencing operations.

• Ladder logic is used to program PLCs.

PLCs vs. DCSs

• Advantage of PLCs:

– Better to withstand harsh operating enviroments, faster cycle time are possible, easier to maintain due to modular nature and lower cost for small and medium sized applications.

• Advantage of DCSs:

– Lower cost per loop for applications involving a large number of control loops.

PLC Architecture

Fieldbus Technology

• Based upon smart valves, smart sensors and controllers installed in the field.

• Uses data highway to replace wires from sensor to DCS and to the control valves.

• Less expensive installations and better reliability.

• Can mix different sources (vendors) of sensors, transmitters, and control valves.

• Now commercially available and should begin to replace DCSs.

Fieldbus Architecture

Actuator System

• Control Valve

– Valve body

– Valve actuator

• I/P converter

• Instrument air system

Typical Globe Control Valve

Cross-section of a Globe Valve

Types of Globe Valves

• Quick Opening- used for safety by-pass applications where quick opening is desired

• Equal Percentage- used for about 90% of control valve applications since it results in the most linear installed characteristics

• Linear- used when a relatively constant pressure drop is maintained across the valve

Inherent Valve Characteristics

Use of the Valve Flow Equation

Typical Flow System

Pressure Drop vs. Flow Rate

Installed Flow Characteristic

Slope of Installed Characteristic

Effect of Linearity in the Installed Valve Characteristics

• Highly nonlinear installed characteristics can lead to unstable flow control or a sluggish performance for the flow controller.

Flow System with Relatively Constant Valve Pressure Drop

Pressure Drop vs. Flow Rate

Installed Valve Characteristics

Analysis of These Examples

• Note the linear installed valve characteristics over a wide range of stem positions.

• If the ratio of pressure drop across the control valve for the lowest flow rate to the value for the highest flow rate is greater than 5, an equal percentage control valve is recommended.

Control Valve Design Procedure

• Evaluate C_v at the maximum and minimum flow rate using the flow equation for a valve (Eq 2.3.3).

• Determine which valves can effectively provide the max and min flow rate remembering that, in general, the valve position should be greater than about 15% open for the minimum flow rate and less than 85% open for the maximum flow rate.

• Choose the smallest valve that meets the above criterion for the minimum capital investment or choose the largest valve to allow for future throughput expansion.

Additional Information Required to Size a Control Valve

• C_V versus % open for different valve sizes.

• Available pressure drop across the valve versus flow rate for each valve. Note that the effect of flow on the upstream and downstream pressure must be known.

Valve Sizing Example

• Size a control valve for max 150 GPM of water and min of 50 GPM.

Determine C_V at Max and Min F_V

_•Use the valve flow equation (Equation 2.3.3) to calculate C_v

• For DP, use pressure drop versus flow rate (e.g., Table on page 82)

Valve Position for Max and Min Flows for Different Sized Valves

Analysis of Results

• 2-inch valve appears to be best overall choice: least expensive capital and it can provide up to a 50% increase in throughput.

• 3-inch and 4-inch valve will work, but not recommended because they will cost more to purchase. The 2-inch valve will provide more than enough extra capacity (i.e., something else will limit capacity for it)

Valve Deadband

• It is the maximum change in instrument air pressure to a valve that does not cause a change in the flow rate through the valve.

• Deadband determines the degree of precision that a control valve or flow controller can provide.

• Deadband is primarily affected by the friction between the valve stem and the packing.

For Large Diameter Lines (>6”), Use a Butterfly Valve

Valve Actuator Selection

• Choose an air-to-open for applications for which it is desired to have the valve fail closed.

• Choose an air-to-close for applications for which it is desired to have the valve fail open.

Cross-section of a Globe Valve

Optional Equipment

• Valve positioner- a controller that adjusts the instrument air in order to maintain the stem position at the specified position. Greatly reduces the deadband of the valve. Positioners are almost always used on valves serviced by a DCS.

• Booster relay- provides high capacity air flow to the actuator of a valve. Can significantly increase the speed of large valves.

Photo of a Valve Positioner

Adjustable Speed Pumps

• Used extensively in the bio-processing industries (better to maintain sterile conditions and relatively low flow rates).

• Fast and precise.

• Do require an instrument air system (i.e., 4-20 mA signal goes directly to pump).

• Much higher capital costs than control valves for large flow rate applications.

Control Relevant Aspects of Actuator Systems

• The key factors are the deadband of the actuator and the dynamic response as indicated by the time constant of the valve.

• Control valve by itself- deadband 10-25% and a time constant of 3-15 seconds.

• Control valve with a valve positioner or in a flow control loop- deadband 0.1-0.5% and a time constant of 0.5-2 seconds.

Chapter

Control Loop Hardware and Troubleshooting

Overall Course Objectives

• Develop the skills necessary to function as an industrial process control engineer.

– Skills

• Tuning loops

• Control loop design

• Control loop troubleshooting

• Command of the terminology

– Fundamental understanding

• Process dynamics

• Feedback control

Control Relevant Aspects of Control Loop Hardware

• Necessary for control loop troubleshooting:

– To determine if each subsystem (control computer, actuator system, and sensor system) is functioning properly

– To understand the proper design and operation of all the components that make-up each of the subsystems of a control loop

Control Diagram of a Typical Control Loop

Components and Signals of a Typical Control Loop

Controllers/Control Computers

• Pneumatic controllers

• Electronic analog controllers

• Supervisory control computers

• Distributed Control Systems (DCS)

• Fieldbus technology

Pneumatic Controllers - Phase I

• Introduced in the 1920’s

• Installed in the field next to the valve

• Use bellows, baffles, and nozzles with an air supply to implement PID action.

• Provided automatic control and replaced manual control for many loops

Pneumatic Controllers - Phase II

• Transmitter type pneumatic controllers began to replace field mounted controllers in the late 1930’s.

• Controller located in control room with pneumatic transmission from sensors to control room and back to the valve.

• Allowed operators to address a number of controllers from a centralized control room.

Pneumatic Controller Installation

Electronic Analog Controllers

• Became available in the late 1950’s.

• Replaced the pneumatic tubing with wires.

• Used resistors, capacitors, and transistors based amplifiers to implement PID action.

• Out sold pneumatic controllers by 1970.

• Allowed for advanced PID control: ratio, feedforward, etc.

Electronic Controller Installation

Computer Control System

• Based upon a mainframe digital computer.

• Offered the ability to use data storage and retrieval, alarm functions, and process optimization.

• First installed on a refinery in 1959.

• Had reliability limitations.

Supervisory Control Computer

Distributed Control System- DCS

• Introduced in the late 1970’s.

• Based upon redundant microprocessors for performing control functions for a part of the plant. SUPERIOR RELIABILITY

• Less expensive per loop for large plants.

• Less expensive to expand.

• Facilitates the use of advanced control.

DCS Architecture

DCS and Troubleshooting

• The data storage and trending capability of a DCS greatly facilitate troubleshooting control problems. That is, the sources of process upsets can many times be tracked down through the process by trending a group of process measurements until the source of the process upset is located.

Control Relevant Aspects of a DCS

• The most important control aspect of a DCS is the cycle time for controller calls. The shortest cycles times are typically around 0.2 seconds while most loops can be executed every 0.5 to 1.0 seconds. These cycle times affect flow control loops and other fast control loops.

PLCs

• PLCs can withstand has industrial enviroments.

• PLCs are used for discrete and continuous control.

• Discrete control is used for startup and shutdown and batch sequencing operations.

• Ladder logic is used to program PLCs.

PLCs vs. DCSs

• Advantage of PLCs:

– Better to withstand harsh operating enviroments, faster cycle time are possible, easier to maintain due to modular nature and lower cost for small and medium sized applications.

• Advantage of DCSs:

– Lower cost per loop for applications involving a large number of control loops.

PLC Architecture

Fieldbus Technology

• Based upon smart valves, smart sensors and controllers installed in the field.

• Uses data highway to replace wires from sensor to DCS and to the control valves.

• Less expensive installations and better reliability.

• Can mix different sources (vendors) of sensors, transmitters, and control valves.

• Now commercially available and should begin to replace DCSs.

Fieldbus Architecture

Actuator System

• Control Valve

– Valve body

– Valve actuator

• I/P converter

• Instrument air system

Typical Globe Control Valve

Cross-section of a Globe Valve

Types of Globe Valves

• Quick Opening- used for safety by-pass applications where quick opening is desired

• Equal Percentage- used for about 90% of control valve applications since it results in the most linear installed characteristics

• Linear- used when a relatively constant pressure drop is maintained across the valve

Inherent Valve Characteristics

Use of the Valve Flow Equation

Typical Flow System

Pressure Drop vs. Flow Rate

Installed Flow Characteristic

Slope of Installed Characteristic

Effect of Linearity in the Installed Valve Characteristics

• Highly nonlinear installed characteristics can lead to unstable flow control or a sluggish performance for the flow controller.

Flow System with Relatively Constant Valve Pressure Drop

Pressure Drop vs. Flow Rate

Installed Valve Characteristics

Analysis of These Examples

• Note the linear installed valve characteristics over a wide range of stem positions.

• If the ratio of pressure drop across the control valve for the lowest flow rate to the value for the highest flow rate is greater than 5, an equal percentage control valve is recommended.

Control Valve Design Procedure

• Evaluate C_v at the maximum and minimum flow rate using the flow equation for a valve (Eq 2.3.3).

• Determine which valves can effectively provide the max and min flow rate remembering that, in general, the valve position should be greater than about 15% open for the minimum flow rate and less than 85% open for the maximum flow rate.

• Choose the smallest valve that meets the above criterion for the minimum capital investment or choose the largest valve to allow for future throughput expansion.

Additional Information Required to Size a Control Valve

• C_V versus % open for different valve sizes.

• Available pressure drop across the valve versus flow rate for each valve. Note that the effect of flow on the upstream and downstream pressure must be known.

Valve Sizing Example

• Size a control valve for max 150 GPM of water and min of 50 GPM.

Determine C_V at Max and Min F_V

_•Use the valve flow equation (Equation 2.3.3) to calculate C_v

• For DP, use pressure drop versus flow rate (e.g., Table on page 82)

Valve Position for Max and Min Flows for Different Sized Valves

Analysis of Results

• 2-inch valve appears to be best overall choice: least expensive capital and it can provide up to a 50% increase in throughput.

• 3-inch and 4-inch valve will work, but not recommended because they will cost more to purchase. The 2-inch valve will provide more than enough extra capacity (i.e., something else will limit capacity for it)

Valve Deadband

• It is the maximum change in instrument air pressure to a valve that does not cause a change in the flow rate through the valve.

• Deadband determines the degree of precision that a control valve or flow controller can provide.

• Deadband is primarily affected by the friction between the valve stem and the packing.

For Large Diameter Lines (>6”), Use a Butterfly Valve

Valve Actuator Selection

• Choose an air-to-open for applications for which it is desired to have the valve fail closed.

• Choose an air-to-close for applications for which it is desired to have the valve fail open.

Cross-section of a Globe Valve

Optional Equipment

• Valve positioner- a controller that adjusts the instrument air in order to maintain the stem position at the specified position. Greatly reduces the deadband of the valve. Positioners are almost always used on valves serviced by a DCS.

• Booster relay- provides high capacity air flow to the actuator of a valve. Can significantly increase the speed of large valves.

Photo of a Valve Positioner

Adjustable Speed Pumps

• Used extensively in the bio-processing industries (better to maintain sterile conditions and relatively low flow rates).

• Fast and precise.

• Do require an instrument air system (i.e., 4-20 mA signal goes directly to pump).

• Much higher capital costs than control valves for large flow rate applications.

Control Relevant Aspects of Actuator Systems

• The key factors are the deadband of the actuator and the dynamic response as indicated by the time constant of the valve.

• Control valve by itself- deadband 10-25% and a time constant of 3-15 seconds.

• Control valve with a valve positioner or in a flow control loop- deadband 0.1-0.5% and a time constant of 0.5-2 seconds.

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PID Control

• Develop the skills necessary to function as an industrial process control engineer.

– Skills

• Tuning loops

• Control loop design

• Control loop troubleshooting

• Command of the terminology

– Fundamental understanding

• Process dynamics

• Feedback control

PID Controls

• Most common controller in the CPI.

• Came into use in 1930’s with the introduction of pneumatic controllers.

• Extremely flexible and powerful control algorithm when applied properly.

General Feedback Control Loop Closed Loop Transfer Functions

• From the general feedback control loop and using the properties of transfer functions, the following expressions can be derived:

Characteristic Equation

• Since setpoint tracking and disturbance rejection have the same denominator for their closed loop transfer functions, this indicates that both setpoint tracking and disturbance rejection have the same general dynamic behavior.

• The roots of the denominator determine the dynamic characteristics of the closed loop process.

• The characteristic equation is given by:

Feedback Control Analysis

• The loop gain (KcKaKpKs) should be positive for stable feedback control.

• An open-loop unstable process can be made stable by applying the proper level of feedback control.

Characteristic Equation Example

• Consider the dynamic behavior of a P-only controller applied to a CST thermal mixer (Kp=1; tp=60 sec) where the temperature sensor has a ts=20 sec and ta is assumed small. Note that Gc(s)=Kc.

Example Continued- Analysis of the Closed Loop Poles

• When Kc =0, poles are -0.05 and -0.0167 which correspond to the inverse of tp and ts.

• As Kc is increased from zero, the values of the poles begin to approach one another.

• Critically damped behavior occurs when the poles are equal.

• Underdamped behavior results when Kc is increased further due to the imaginary components in the poles.

In-Class Exercise

• Determine the dynamic behavior of a P-only controller with Kc equal to 1 applied to a first-order process in which the process gain is equal to 2 and the time constant is equal to 22. Assume that Gs(s) is equal to one and Ga(s) behaves as a first-order process with a time constant of 5.

PID Control Algorithm

Definition of Terms

• e(t)- the error from setpoint [e(t)=ysp-ys].

• Kc- the controller gain is a tuning parameter and largely determines the controller aggressiveness.

• tI- the reset time is a tuning parameter and determines the amount of integral action.

• tD- the derivative time is a tuning parameter and determines the amount of derivative action.

Transfer Function for a PID Controller

Example for a First Order Process with a PI Controller

Example of a PI Controller Applied to a Second Order Process

Properties of Proportional Action

• Closed loop transfer function base on a P-only controller applied to a first order process.

• Properties of P control

– Does not change order of process

– Closed loop time constant is smaller than open loop tp

– Does not eliminate offset.

Offset Resulting from P-only Control Proportional Action for the Response of a PI ControllerProportional Action

• The primary benefit of proportional action is that it speedup the response of the process. Properties of Integral Action

• Based on applying an I-only controller to a first order process

• Properties of I control

– Offset is eliminated

– Increases the order by 1

– As integral action is increased, the process becomes faster, but at the expense of more sustained oscillations

Integral Action for the Response of a PI Controller Integral Action

• The primary benefit of integral action is that it removes offset from setpoint.

• In addition, for a PI controller all the steady-state change in the controller output results from integral action.

Properties of Derivative Action

• Closed loop transfer function for derivative-only control applied to a second order process.

• Properties of derivative control:

– Does not change the order of the process

– Does not eliminate offset

– Reduces the oscillatory nature of the feedback response

Derivative Action for the Response of a PID Controller Derivative Action

• The primary benefit of derivative action is that it reduces the oscillatory nature of the closed-loop response.

Position Form of the PID AlgorithmProportional Band

• Another way to express the controller gain.

• Kc in this formula is dimensionless. That is, the controller output is scaled 0-100% and the error from setpoint is scaled 0-100%.

• In more frequent use 10-15 years ago, but it still appears as an option on DCS’s Conversion from PB to Kc

• Proportional band is equal to 200%.

• The range of the error from setpoint is 200 psi.

• The controller output range is 0 to 100%.

• The loop gain (K_cK_aK_pK_s) should be positive for stable feedback control.

• Consider the dynamic behavior of a P-only controller applied to a CST thermal mixer (K_p=1; t_p=60 sec) where the temperature sensor has a t_s=20 sec and t_a is assumed small. Note that G_c(s)=K_c.

• When K_c =0, poles are -0.05 and -0.0167 which correspond to the inverse of t_p and t_s.

• As K_c is increased from zero, the values of the poles begin to approach one another.

• Underdamped behavior results when K_c is increased further due to the imaginary components in the poles.

• Determine the dynamic behavior of a P-only controller with K_c equal to 1 applied to a first-order process in which the process gain is equal to 2 and the time constant is equal to 22. Assume that G_s(s) is equal to one and G_a(s) behaves as a first-order process with a time constant of 5.

• e(t)- the error from setpoint [e(t)=y_sp-y_s].

• K_c- the controller gain is a tuning parameter and largely determines the controller aggressiveness.

• t_I- the reset time is a tuning parameter and determines the amount of integral action.

• t_D- the derivative time is a tuning parameter and determines the amount of derivative action.

_–Closed loop time constant is smaller than open loop t_p

_–Does not eliminate offset.

• K_c in this formula is dimensionless. That is, the controller output is scaled 0-100% and the error from setpoint is scaled 0-100%.

• In more frequent use 10-15 years ago, but it still appears as an option on DCS’s Conversion from PB to K_c

Conversion from K_cto PB

• t_f is equal to Dt (1/f-1) as f becomes small, t_f becomes large.

• As t_f is increased, t_p’ will increase.

• Critical issue is relative magnitude of t_f compare to t_p.

Relationship between Filter Factor (f), the Resulting Repeatability Reduction Ratio (R) and the Filter Time Constant (t_f)

• To reduce the effect of noise (i.e., R is increased), f must be reduced, which increases the value of t_f. Filtering slows the closed-loop response significantly as t_fbecomes larger than 10% of t_p.

• The effect of filtering on the closed-loop response can be reduced by increasing the frequency with which the filter is applied, i.e., reducing Dt_f.

Comparison between PI and PID for a Low q_p/t_p Ratio