Enhanced Single-Loop Control Strategies Chapter 16.

Enhanced Single-Loop Control StrategiesC

hap

ter

16

Ch

apte

r 16

Ch

apte

r 16

Cascade Control (multi-loop)

• Distinguishing features:

1. Two FB controllers but only a single control valve (or other -final control element).

2. Output signal of the "master" controller is the set-point for “slave" controller.

3. Two FB control loops are "nested" with the "slave" (or "secondary") control loop inside the "master" (or "primary") control loop.

• Terminology

slave vs. mastersecondary vs. primary inner vs. outer

Ch

apte

r 16

Ch

apte

r 16

1 21

2 2 2 2 1 2 2 1 11p d

c v p m c c v p p m

G GY

D G G G G G G G G G G

(Eq.16-5)

Ch

apte

r 16

Ch

apte

r 16

Ch

apte

r 16

Time Delay Compensation

• Model-based feedback controller that improvesclosed-loop performance when time delays are present

• Effect of added time delay on PI controller performancefor a second order process (1 = 3, 2 = 5) shown below

Ch

apte

r 16

No model error:

(sensitive to model errors > +/- 20%)

* *s sG G e G e

*

*

* *

11 1

(16 22)1 1

C CC s

sp CC

sC C

sp C C

G G GYG

Y G GG G e

G G e G GY

Y G G G G

Ch

apte

r 16

Ch

apte

r 16

Direct Synthesis Approach (Smith Predictor)

Assume time delay between set-point change and controlledvariable (same as process time delay, ).

If

then

From Block Diagram,

Equating...

s

PC

PC

sp

esQGG

GG

Y

Y

)(

1

sP e)s(PG

sPC

PeQP

1

G

1

RC1R

CG

s

C

C

PePG1

1G

)Q1(P

QGC

Ch

apte

r 16

Ch

apte

r 16

SELECTIVE CONTROL SYSTEMS (Overrides)

For every controlled variable, there must be at least one manipulatedvariable.

In some applications

# of controlledvariables

# of manipulatedvariables

•Low selector:

•High selector:

MC NN

Ch

apte

r 16

multiple measurementsone controllerone final control element

Ch

apte

r 16

Figure 16.13 Control of a reactor hot spot temperature by using a high selector.

Override using PI controllers - “old way” (vs. digital logic)

2 measurements, 2 controllers, 1 F.C.E.

Ch

apte

r 16

Figure 16.15 A selective control system to handle a sand/water slurry.

Split Range Control

2 Manipulated Vars.: V1 and V2

1 Controlled Var.:Reactor pressure

While V1 opens, V2 should close

Ch

apte

r 16

Ch

apte

r 16

3 6 9 15

Ch

apte

r 16

Ch

apte

r 16

Inferential Control

• Problem: Controlled variable cannot be measured or has large sampling period.

• Possible solutions:1. Control a related variable (e.g., temperature instead

of composition).2. Inferential control: Control is based on an estimate

of the controlled variable.• The estimate is based on available measurements.

– Examples: empirical relation, Kalman filter

• Modern term: soft sensor

Ch

apte

r 16

Gain Scheduling

• Objective: Make the closed-loop system as linear as possible.

• Basic Idea: Adjust the controller gain based on current measurements of a “scheduling variable”, e.g., u, y, or some other variable.

Ch

apte

r 16

• Note: Requires knowledge about how the process gain changes with this measured variable.

Ch

apte

r 16

Examples of Gain Scheduling

• Example 1. Once through boiler

The open-loop step response are shown in Fig. 16.18 for two different feedwater flow rates.

Fig. 16.18 Open-loop responses.

• Proposed control strategy: Vary controller setting with w, the fraction of full-scale (100%) flow.

• Example 2. Titration curve for a strong acid-strong base neutralization.

(16-30)c c I I D DK wK , / w, / w,

Ch

apte

r 16

Adaptive Control

• A general control strategy for control problems where the process or operating conditions can change significantly and unpredictably.

Example: Catalyst decay, equipment fouling

• Many different types of adaptive control strategies have been proposed.

• Self-Tuning Control (STC):

– A very well-known strategy and probably the most widely used adaptive control strategy.

– Basic idea: STC is a model-based approach. As process conditions change, update the model parameters by using least squares estimation and recent u & y data.

• Note: For predictable or measurable changes, use gain scheduling instead of adaptive control

Reason: Gain scheduling is much easier to implement and less trouble prone.

Ch

apte

r 16

16-26

Ch

apte

r 16

Figure 16.20 Membership functions for room temperature.

Ch

apte

r 16

Figure 16.23 Membership functions for the inputs of the PI fuzzy controller (N is negative, P is positive, and Z is zero).

Ch

apte

r 16

Ch

apte

r 16

Ch

apte

r 16

Basic Design Information

Final Control System – Distillation TrainC

hap

ter

16

Previous chapter Next chapter

Ch

apte

r 16