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KKKR3713 Dynamic & Process Control, Plant Operation - Coggle Diagram
KKKR3713 Dynamic & Process Control
Controlled Variables
Process Control Variable
5 COs
1.Design feedback controller for chemical and biochemical processes
Use MATLAB software to solve design of
feedback control
Learn the design of controllers for integrated complex chemical processes.
Able to develop a chemical and biochemical processes model as per requirement to control system design.
Able to analyze the characteristics stability of feedback control system using frequency response technique.
3 tests
11 Topics
Topic 3: Dynamic Behavior
Ramp Input
often experience "drifting disturbances" that is relatively slow changes up for some period of time
Example: ramp a set point to a new value, feed composition
Rectangular Pulse Input
Represents a brief, sudden change in a process variable
Example: Reactor feed is shut off for 1 hour, the fuel gas supply to a furnace is briefly interrupted
Step Input
Sudden change in a process variable can be approximated by a step change of magnitude, M
Example: reactor feedstock is suddenly switched from one supply to another, causing sudden changes in feed concentration, flow, etc.
Sinusoidal Input
Processes are also subject to periodic, or cyclic, disturbances
Examples
24 hour variations in cooling water temperature
60-Hz electrical noise
Impulse Input
Represents a short, transient disturbance
Example: -->Electrical noise spike in themo-couple reading,
-->Injection of tracer dye
KK2
Order of a Transfer Function Model
Definition: Order of denominator polynomial
Types / Order
Higher order system
First-order system
Example: Thermometer, liquid level process
Second-order system
Example: Inherent system, system in series, process installed with controllers
Topic 2: Dynamic Model of Process (KK1)
Degree of Freedom
Laplace Transform
Constant function
Step function
Exponential function
Linearization
Nonlinear
Taylor series Expansion
introduce deviation variables
Transfer Function
Properties
Order of a TF Model
Additive
Multiplicative
Steady-State Gain
Representation of linear, dynamic model
Modeling
Activities leading to the construction of model
Mathematical Model Usage
Design
Evaluate alternate process and control structures and strategies
Sizing and arrangement of process equipment
Simulating start-up, shutdown and emergency simulations and procedures.
Topic 7: Stability(KK6)
Stability by charateristic equation
G1 = 10*(0.5s+1) / s [PI Controller]
G2 = 1 / (2s + 1) [Stirred tank ]
Procedure for Routh Test
Write characteristic equation in form
Routh Array
Stability of a system is defined as the property for which the output response is bounded for all bounded inputs.
Stability Criterion
To make the stability definition into a more simple criterion, that can be used to find the control systems stability.
linear control system
unstable if any roots of its characteristic equation are on, or to the right of, the imaginary axis
otherwise, the system is stable
KK6
Routh Test
A purely algebraic method to determine the stability of linear control system
Topic 8: Performance Criteria and Controller Tuning (KK7)
SIMULINK
Open Loop using Cohen-Coon Method
Design of controllers
Decision of which type of controller.
Performance Criteria
Controller tuning.
Closed Loop using Ziegler-Nichols Method
Criteria of good control
Integral of the square of the error(ISE)
Integral of the absolute value of error (IAE)
Integral of time-weighted absolute error (ITAE)
Topic 6: Transient Response of Simple Control System (
KK5
)
Proportional control for set point change (servo)
Overall transfer function
may be rearranged in the form of a first-order lag
Proportional-integral control for load change
TF may be written in standard form of 2nd-order system
Proportional control for load change (regulator)
may be arranged in the first-order system
Proportional-integral control for set point change
eg: Proportional-integral
control of stirred-tank heater
Proportional Control of System with
Measurement Lag
Effect of controller gain and measuring lag on system response for unit-step change in set point
Topic 4: Components of Control System (KK3)
Development of block diagram
Process
Measuring element
Controller
Final Controller
Conventional Controller
Proportional controller (P)
Proportional Integral (PI)
Proportional-Derivative (PD)
Proportional-Integral-Derivative (PID)
Controller type
Parallel
Parallel with derivative filter
Series
Parallel with proportion and derivative weighting
Series with derivative filter
Expanded
Controller feature
Proportional mode
Controller parameter is controller gain and proportional band
Integral mode
Controller parameter is integral time, reset rate, integral mode
Derivative mode
Controller parameter is derivative time, mode
and filter parameter
Control interval
Topic 1: Introduction to Process Control
KK8
Topic 9: Frequency Response
FIRST ORDER SYSTEM:
AR
∅ =
SECOND ORDER SYSTEM:
Bode diagram
Important parameters
Low frequency asymptote
Corner frequency
High-frequency asymptote
True curve
2 graphs
log AR vs log 𝛚
phase ∅ vs log 𝛚
DEAD TIME :
SYSTEM IN SERIES
Overall,
Topic 10 : Control Design System by Frequency Response
Ziegler-Nichols Tuning Method
Gain Margin
Phase Margin
M<1 close loop STABLE
M>1 close loop UNSTABLE
Bode plot
Crossover frequancy
AR = 1
KK9
Frequency response technique can be used to
study stability of closed loop system using bode diagrams
choose suitable parameters: tuning for controllers
Topic 5: Block Diagram Reduction (KK4)
Definition
H(s) – Feedback transfer function
G(s)H(s) – Open‐loop transfer function
G(s) – Direct/ Forward transfer function
Single block diagram representation
R(s) which is input -->Transfer function G(s)--> C(s) which is output
Characteristic equation definition
is defined as an equation obtained by setting
the denominator polynomial of the transfer function to zero
Topic 11 : Advance Process Control (APC)
SISO - Single-input-single output
Cascade Control
2 measured variables
1 manipulated variable
Slow Dynamics
temperature
level
Humidity
composition
Primary loop (Outer loop)
Secondary loop (Inner loop)
inner fater than outer (beneficial)
Ratio control
2 variables measured
Set at one ratio
For flow ratio control
2 Streams measured
Controlled stream
'Wild' stream
Feedforward control (FCC)
Measure disturbance/ load variables & perform corrective action before upset/ disrupt process
Example : measure disturbance which is the steam flow rate and adjust feedwater flow rate
MIMO - Multiple-input-multiple-output
Adaptive control
Adjusting controller parameters - to compensate for variation in the characteristics of the process
Al based control
AI (Artificial Intelligence)
Making computer to do human like task
Fuzzy logic
Artificial Neural Network
KK10
Manipulated variables
IP
Disturbance Variables
Importance of studying process control
Safety
Economics
To ensure of:
Good Process Operation
Process Safety
Product Quality
Minimization of Environmental Impact
For plant stability
Plant Operation
Optimizing plant operation
Troubleshooting and processing problems
Aiding in start-up and operator training
Cheaper, safer and faster
