CHE 185 – PROCESS CONTROL AND DYNAMICS PID ENHANCEMENTS.

CHE 185 – PROCESS CONTROL AND DYNAMICS

PID ENHANCEMENTS

LIMITATIONS OF CONVENTIAL PID CONTROLLERS

• THE PERFORMANCE OF PID CONTROLLERS CAN BE SUBSTANTIALLY LIMITED BY:– PROCESS NONLINEARITY– MEASUREMENT DEADTIME– PROCESS CONSTRAINTS

• THERE ARE SEVERAL APPROACHES FOR PID CONTROLLERS TO HANDLE EACH OF THESE PROBLEMS

INFERENTIAL CONTROL

• USES EASILY MEASURED PROCESS VARIABLES (T, P, F) TO INFER MORE DIFFICULT TO MEASURE QUANTITIES SUCH AS COMPOSITIONS AND MOLECULAR WEIGHT.

• CAN SUBSTANTIALLY REDUCE ANALYZER DELAY.

• CAN BE MUCH LESS EXPENSIVE IN TERMS OF CAPITAL AND OPERATING COSTS.

• CAN PROVIDE MEASUREMENTS THAT ARE NOT AVAILABLE ANY OTHER WAY

INFERENTIAL CONTROL

• EXAMPLES OF VARIABLES THAT ARE NOT EASY TO MEASURE DIRECTLY– DENSITY– VAPOR PRESSURE– MELT INDEX– GAS COMPOSITION– MOLECULAR WEIGHT

INFERENTIAL CONTROL

• SECONDARY MEASUREMENTS ARE USED WITH THE FOLLOWING FOR INFERENTIAL CONTROL– PROCESS MODEL EQUATIONS – THERMODYNAMIC RELATIONSHIPS, I.E. LINKING

TEMPERATURE TO CONCENTRATION– EMPIRICAL MODELING– ISOTHERMAL VISCOSITY VERSUS LIQUID

COMPOSITION

INFERENTIAL CONTROL

• MEASURES A VARIABLE USING AN INDIRECT METHOD

• USED WHEN– IT IS NOT PRACTICAL TO MEASURE THE TARGET

VARIABLE– EXCESSIVE COST FOR CONTROL EQUIPMENT

TO DIRECTLY MEASURE THE VARIABLE– EXCESSIVE DOWNTIME IN A TARGET VARIABLE

SENSOR– THERE IS AN INFERENTIAL VARIABLE AVAILABLE

INFERENTIAL CONTROL

• CHARACTERISTICS OF THE INFERENTIAL VARIABLE

• IT MUST BE CLOSELY RELATED TO THE TARGET VARIABLE

• IT MUST NOT BE AFFECTED BY CHANGES IN THE PROCESS CONDITIONS

• DYNAMICS ARE ADEQUATE FOR FEEDBACK CONTROL

INFERENTIAL CONTROL

• CORRECTIONS TO INFERENTIAL CONTROL VARIABLE

• CAN USE A CASCADE CONTROL SOURCE• CAN BE MANUALLY ADJUSTED

INFERENTIAL CONTROL

• EXAMPLE USING TEMPERATURE TO CONTROL COMPOSITION FOR ISOBARIC FLASH

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SetPoint

Heating orCoolingMedia

VaporProduct

LiquidProduct

Flash Tank

HeatExchange

ProcessFeed

INFERENTIAL CONTROL

• EXAMPLE USING TEMPERATURE TO CONTROL COMPOSITION FOR ISOBARIC FLASH

• CONTROLS COMPOSITION BASED ON FLASH TEMPERATURE

• DIRECT CONTROLLED VARIABLE IS FLASH PRESSURE

• LEVEL IS ALSO DIRECTLY CONTROLLED

INFERENTIAL CONTROL

• EXAMPLE USING TEMPERATURE TO CONTROL COMPOSITION FOR ISOBARIC FLASH

• HOW IS THE TEMPERATURE SETTING CHECKED FOR THIS EXAMPLE?

• MANUAL ANALYSIS CAN BE USED TO ADJUST

• A FEED FORWARD SIGNAL FROM A PROCESS ANALYZER CAN ALSO BE USED (SEE SKETCH NEXT SLIDE)

INFERENTIAL CONTROL

• IT IS ASSUMED THAT THE LAG TIME FOR THE ANALYZER LOOP IS LONGER THAN THAT FOR THE TEMPERATURE LOOP.

• THIS ALSO WILL TAKE CARE OF ANY STEADY-STATE OFFSET FOR THE TEMPERATURE CONTROL

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SetPointSignal

Heating orCoolingMedia

VaporProduct

LiquidProduct

Flash Tank

HeatExchange

ProcessFeed

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INFERENTIAL TEMPERATURE CONTROL FOR DISTILLATION COLUMNS

• REBOILER CONTROL BASED ON TRAY TEMPERATURE

INFERENTIAL TEMPERATURE CONTROL FOR DISTILLATION COLUMNS

• CHOOSING A PROPER TRAY TEMPERATURE LOCATION

• TRAY TEMPERATURE USED FOR INFERENTIAL CONTROL SHOULD SHOW STRONG SENSITIVITY

INFERENTIAL TEMPERATURE CONTROL FOR FLOW REACTOR

• SEE EXAMPLE 13.2 IN TEXT

ARTIFICIAL NEURAL NETWORKS (ANN’s)

• THESE ARE NON-LINEAR CONTROLLERS THAT ARE USED TO CONTROL NON-LINEAR PROCESSES

• THE MODEL TAKES INPUT(S) FROM THE SYSTEM AND USES THESE WITH WEIGHTED FUNCTIONS, TO PROVIDE THE OUTPUT FOR THE CONTROLLER

ARTIFICIAL NEURAL NETWORKS (ANN’s)

• THE WEIGHTING FUNCTIONS ARE REVISED OVER TIME TO OPTIMIZE THE OUTPUT

• THE ANN IS TUNED BY THE SYSTEM AND ONLY APPLIES TO ONE SYSTEM.

ARTIFICIAL NEURAL NETWORKS (ANN’s)

• SOFT SENSORS BASED ON NEURAL NETWORKS

• NEURAL NETWORK (NN) PROVIDES NONLINEAR CORRELATION.

• WEIGHTS ARE ADJUSTED UNTIL NN AGREES WITH PLANT DATA

• NN-BASED SOFT SENSORS ARE USED TO INFER NOX LEVELS IN THE FLUE GAS FROM POWER PLANTS.

SCHEDULING CONTROLLER TUNING

• THIS IS A METHOD TO COMPENSATE FOR PROCESS NON-LINEARITY THAT CAN AFFECT CONTROL RESPONSE

• THE BASIC TECHNIQUE IS TO TUNE THE CONTROLLER BASED ON EMPIRICAL DATA– OPTIMUM TUNING DATA IS OBTAINED

OVER A RANGE OF PROCESS SETTINGS.

SCHEDULING CONTROLLER TUNING

• THE TUNING DATA IS THEN CONVERTED INTO PROPORTIONAL, INTEGRAL AND DERIVATIVE RESET FUNCTIONS OF THE MANIPULATED VARIABLE.

• THIS METHOD IS SIMILAR TO ANN EXCEPT IT ONLY LOOKS AT ONE INPUT VARIABLE AND RESULTS IN CLEARLY DEFINED FUNCTIONS

SCHEDULING CONTROLLER TUNING

• ADJUST TUNING OF HEAT EXCHANGER CONTROL FOR VARIOUS FEED RATES

• LINK TUNING PARAMETERS TO THE FLOW RATES

SCHEDULING CONTROLLER TUNING

• TYPICAL OPEN LOOP RESPONSE

SCHEDULING CONTROLLER TUNING

• CLOSE LOOP RESPONSE WITH SCHEDULING

SCHEDULING CONTROLLER TUNING

• CLOSE LOOP RESPONSE WITH SCHEDULING

SCHEDULING CONTROLLER TUNING

• IMPLEMENTATION CAN TAKE THE FORM OF ADJUSTMENT OF PI GAIN AND INTEGRAL TIME USING THE TUNING FACTORS

• FOR EXAMPLE USING ZEIGLER-NICHOLS (EQUATION 9.11.2):

OVERRIDE/SELECT CONTROL

• THIS METHOD EMPLOYS A SELECTION AMONG MULTIPLE INPUTS– IT CAN BE APPLIED TO ROUTINE CONTROL– IT CAN BE USED TO IMPLEMENT EMERGENCY

CONTROL

• UNDER NORMAL OPERATION A LOW SELECT OR A HIGH SELECT METHOD IS USED BY THE CONTROLLER TO ADJUST THE MANIPULATED VARIABLE

OVERRIDE/SELECT CONTROL

• INPUT COMES FROM TWO OR MORE CONTROLLERS TO A SECOND IN A CASCADE CONFIGURATION

• THE COMPARISON CONTROLLER CHOOSES THE LOWEST OR HIGHEST TO SEND TO THE ACTUATOR

• CONSIDER A REACTOR WITH COOLING FOR TEMPERATURE CONTROL

OVERRIDE/SELECT CONTROL

• THE LOW SELECTOR TAKES THE LOWER VALUE FROM THE COMPOSITION ANALYZER AND THE REACTOR TEMPERATURE SENSOR

• THE LOWER VALUE IS SELECTED BECAUSE THIS ASSURES THE HIGHEST COOLING FLOW TO THE UNIT.

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ISOTHERMALCSTR

OVERRIDE/SELECT CONTROL• TEXT PROVIDES SEVERAL OTHER

EXAMPLES BASED ON HIGH, LOW AND COMBINED SELECTION

• NOTE THAT IT IS IMPORTANT FOR THE OPERATOR TO KNOW WHICH SIGNAL IS BEING USED BY THE CONTROLLER.

• MAY BE USED FOR LOW AND HIGH LEVEL ALARM ACTIONS– ALERTS OPERATOR TO OUT-OF-RANGE AND

INITIATES CORRECTION WITHIN THE LOOP– NOT INTENDED TO REPLACE SEPARATE HI-HI AND

LO-LO ALARMS

COMPUTED MANIPULATED VARIABLE CONTROL

• THESE ARE APPLIED MASS BALANCES, ENERGY BALANCES OR REACTION MODELS THAT ARE USED TO SPECIFY OPERATING SET POINTS.

• CAN BE USED FOR COMPLICATED SYSTEMS THAT CAN BE CONVENIENTLY MODELED

• TYPICALLY USED AS A SECONDARY SET POINT GENERATOR

• MAY BE LINKED TO SIMULATORS

COMPUTED MANIPULATED VARIABLE CONTROL

• COMPUTED REBOILER DUTY CONTROL

COMPUTED MANIPULATED VARIABLE CONTROL

• INTERNAL REFLUX CONTROL