notes_2_simulatn - Fall 2004 ICE Topics: Process Control by...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Fall 2004 ICE Topics: Process Control by Design 10.492 Lecture Notes 2: Simulating the Shower Process revised 2004 Dec 16 Dr. Barry S. Johnston, Copyright 2004. 1 the shower process is simple enough that we can simulate its operation Over the past decade our tools for simulating processes have greatly improved. In particular, we can predict how the process will behave under dynamic conditions: startup, disturbance, and shutdown. Dynamic simulation can aid in specifying the control scheme and may catch potential operating problems. For the shower, we do not need a complex computer code we can derive and solve a decent equation set by hand. We will do this simulation to illustrate a simple control algorithm how the process behavior was indicated by the RGA and DC tools Simulation thus allows us to check the efficacy of our screening tools. first we need to talk some more about process control Recall how we defined feedback control: measurement of CV used to motivate a change in MV to keep CV at set point. To put this into practice, we must assert some control algorithm, that is, a way to calculate how much to move MV. We begin by defining error: ) t ( CV SP ) t ( = (2-1) Error is the difference between the desired value of CV, called the set point SP, and CV. Of course, CV might wander around with passing time, and so error would, as well. If CV is at the set point, the error is zero; should CV be disturbed, the error might be positive or negative. The error is the input to the control algorithm. the simple Proportional algorithm for a controller An intuitively appealing algorithm is to make the response proportional to the error. ) t ( K B ) t ( MV C C + = (2-2) MV the manipulated variable, which may vary in time B C the value of MV when error is zero; known as the bias K C adjustable controller gain (+ or -) we apply the proportional controller to our process Start with flow control. Call the set point F sp . Then the error in the flow is ' ' sp r r sp sp F F F F F F F F F = + = = (2-3) By introducing our reference value F r into the definition, we see that the error is also the difference between two deviation variables. In many cases, of course, we would take the set point value F sp to be the same as our reference value, so that F sp is identically zero. However, Fall 2004 ICE Topics: Process Control by Design 10.492 Lecture Notes 2: Simulating the Shower Process revised 2004 Dec 16 2 distinguishing F sp from F r allows us to easily describe set point changes that is, moving the process from one condition to another under the supervision of the controller. the error can be scaled When we divide the error by the operating range for flow, we obtain a dimensionless error....
View Full Document

This note was uploaded on 11/27/2011 for the course CHEMICAL E 20.410j taught by Professor Rogerd.kamm during the Spring '03 term at MIT.

Page1 / 9

notes_2_simulatn - Fall 2004 ICE Topics: Process Control by...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online