l10 - rockwell automation · plantpax mpc lab setup 12 controller 1756-mpc module lab files:...

Copyright © 2015 Rockwell Automation, Inc. All Rights Reserved.

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L10 - PlantPAx® MPC: Optimization in the Logix Controller for Easy Deployment


Agenda

Course Feedback

Lab Overview – Go!

What is Model Predictive Control?


Model Predictive Control (MPC) is an advanced process control (APC) technique which

Systematically handles multivariable control problems with difficult dynamics and internal

interactions between process variables in a unified way

Explicitly takes into account process constraints (safety, equipment, quality limits, …)

Handles measured disturbances (feed-forward control)

Uses process models to predict future process output

Handles process dead-time, processing and measurement lags

Calculates optimal control moves based on defined objective function subject to constraints

Design and tuning is intuitive and relatively easy compared with other APC techniques

What is Model Predictive Control


MPC versus PID Control

Coordinate multiple interacting PIDs

Predictably manage external disturbances

Handle long or complex process dynamics

Maximize performance up to process limits

PID tuning is subjective and requires time and experience

We do this because it makes

processors money:

Higher production, yields, efficiency

and product quality


MPC Opportunities

Coating Oven

Distillation Column

Compressor

Chemical Reactor

Boiler

Furnace

Dryer

Drilling Rig

and many more

5


Making Control Scheme Smarter

MPC

SP

6

M

Arc

hit

ec

ture

wit

h M

PC

PID

PID left in the scheme or direct output control

SP

PID PID

PID

High / Low Select Logic,

Gain Scheduler

Decoupling,

Override

Control

PID

M

SP

Tra

dit

ion

al

Co

ntr

ol A

rch

ite

ctu

re

Easier to design and maintain

6


now

CV

MV

MV

1 Horizon

CVSP

MVSP

0

How a Receding Horizon works

7

measured

calculated (predicted)

calculated and sent out as MV

CV

Constraints

CV MVProcess

Controller

Model

CV predictionMV prediction

MPC

Setpoints

1

0

2

1

0

2

1

2

)(

)()(

)()(

Horizon

k

MoveSupp

Horizon

k

SPCoef

Horizon

k

SPCoef

kMVMV

kMVkMVMV

kCVkCVCVJ

The Task: Minimize J by calculating MV over the Horizon

0

1 Horizon0

Horizon0 1


PID vs MPC variables

8

CV

CVSP

MVSP

DVDV

MV

CV

unmeasured disturbance

MPC

Process

PV

SPCV

PV

unmeasured disturbance

PID

Process

CV – Controlled (Process) Variables: objective and/or constraints

DV – Disturbance Variables: affects CVs, but is independent of controller

MV – Manipulated Variables: PID targets or outputs that MPC adjusts to meet

objectives


• Design the MPC Application:

• Controlled Variables: What are we trying to do better, what is in the way/limits this today?

• Manipulated Variables: What can we adjust to affect this result today?

• Disturbance Variables: What do you watch out for that causes / forecasts a change?

• Perform Plant Testing (set up trends/logs for above variables)

• Individually step each MV & DV (as possible) within safe limits to see changes in CV’s.

• Develop MPC models based on identification of above data

• Develop any calculations necessary to support MPC goals

• Implement/integrate and test application, train operators and turn-on!

Measure Improvement!

A MPC Project


MPC in Integrated Architecture

10

FactoryTalk® ProductionCentre, FactoryTalk® Historian,

Pavilion® Real-Time Optimization™ …

Pavilion8® MPC, Software CEM®, VOA®, Asset Management, …

Rockwell Software Studio 5000®, PlantPAx™ MPCBuilder,

PlantPAx™ ModelBuilder

• PlantPAx® MPC

• IMC,CC,MMC

• FuzzyLogic

• SoftSensor® (AOI)

• PID,PIDE

• Motion

• Discrete

M P C

Copyright © 2015 Rockwell Automation, Inc. All Rights Reserved. 11

PlantPAx™ MPC (logix embedded): simpler, faster

Coating Oven MPC

Note available Short-Cuts

Lab Problem


PlantPAx MPC Lab Setup

12

Controller 1756-MPC Module

Lab Files:

Oven.ACD

OvenDataSet.CSV

Oven_ModelReady.mpc

Oven_SimulationReady.mpc

Oven_ExportReady.mpc

0 1 2

• PlantPAx MPCBuilder

• Studio 5000

• RSLinx Classic

• FT View SE Client

192.168.1.112

192.168.1.113


Dynamic Identification


Combustion gas suction

MV0

DV3

CV0Oven_Temp

CV1Oven_Press

Ambient_Temp

MV1

Heating

Chamber

rpm constant

Combustion gas circulation

Atmospheric pressure (constant)

Curing Oven MPC – 2MVs, 4DVs, 2CVs

14

Metal stripDV2

Combustion gas exhaust

Metal strip

Hot air inlets Suction_Flow

Pressure

(constant)

DV2

DV1

MV0

MV1

DV0

CV1

Air_Flap_Valve

Gas_Valve

Suction_Flow

Hot_Air_Temp

Hot_Air_Press

Oven_Temp

Oven_Press

Ambient_Temp

DV3

CV0

Hot Air Supply

Gas Supply

Hot_Air_Temp

Hot_Air_Press

DV0

DV1 Air_Flap_Valve

Gas_Valve


MPC Configuration & Settings

Oven

DV2

DV1

MV0

MV1

DV0

CV1

Air_Flap_Valve

Gas _Valve

Suction_Flow

Hot_Air_Press

Hot_Air_Temp

Oven_Temp

Oven_PressAmbient_Temp

DV3

CV0310C

340C

60 50 260 s

2C/s

21 65

max -1 Pa

min -20 Pa

100%

0%

100%

0%

max 600C

min 550C

max 250Pa

min 200Pa

max 40C

min 27C

max 0.3m3/s

min 0.2m3/s

keep pressure within limits

track temperature setpoint

OversampleDT – MPC frequency 0.5 seconds

SPValueReq - True

SPProg 0%

ROC 10%/s

Scale 100%

ROC 10%/s

Scale 100%

SPTrajectoryReq - True

Coef 100

Scale 100 C

ZoneReq - True

Coef 10

Scale 10 Pa

CVSPTrajectory

0 s 310 C

6 s 310 C

21 s 340 C

50 s 340 C

65 s 310 C

260 s 310 C

ZoneHiLimit -1 Pa

ZoneLoLimit -20 PaDV2


Do not skip Faceplates


We Want Your Feedback!

Session Surveys:Please take a couple minutes to complete a quick session survey to tell us about the session you just attended.

3

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l10 - rockwell automation · plantpax mpc lab setup 12 controller 1756-mpc module lab files:...

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