Chapter23 - Biosystems Control Design, PPT, Chemical Engineering, Semester, Engineering Computer Science Engineering (CSE) Notes | EduRev

Biosystems Control Design

Chapter 23 addresses a variety of synthesis  problems in the field of biosystems:

• Pharmaceutical Operations

  • Bioreactors

  • Crystallizers

  • Granulation

• Drug Delivery

  • Type 1 Diabetes

  • Blood Pressure Control

  • Cancer Treatment

  • Controlled Treatment for HIV/AIDS

  • Cardiac Assist Devices

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Figure 23.1 Schematic of a typical industrial fermentor.

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Figure 23.2 Step response of fermentor model to symmetric changes in dilution of magnitude 10% from the nominal value of D=0.202 h-1.

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Figure 23.3 Step response of fermentor model to symmetric changes in dilution of magnitude 10% from the  nominal value of D=0.0389 h-1.

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Figure 23.4 Flowsheet of a typical industrial crystallizer showing concentration and temperature controllers, including cascade control for temperature.

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Hierarchy of Process Information

Need relationships between levels to deliver product which consistently meets the customers needs

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Specific Challenges in Agglomeration Control

Various process operations

• granulation

• polymerization

• spray drying

Common characteristics

• real-time analysis required for distribution

• complex heat/mass/momentum transfer problems

• multiple attributes of interest (size, shape, concentration, etc.)

• high dimension, stiff models

• underactuated

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Granulation Control – Challenges

Multivariable interactions (5th and 90th percentiles)

No target (setpoint) for 5th and 90th percentiles

• One-sided limits

Data acquisition is difficult.Suggested Operating Objectives:

• Track bulk density to reference

• Minimize control effort if PSD within limits

• Strong action if PSD out of limits

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Figure 23.5 Process flowsheet for granulation circuit with recycle.

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Case Study
[Pottman, Ogunnaike, Adetayo, and Ennis, Powder Tech., 1999]

Correlated Process Variables

• particle size distribution (5th, 90th percentiles)
• bulk density

Manipulated Variables

• 3 spray nozzles (flow rate) [bounded]

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Figure 23.6 Simplified process flowsheet for granulator example. Here u1, u2, u3 are, respectively, nozzles 1,2, and 3, and y1, y2, y3 are, respectively, bulk density, d5 and d90.

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Figure 23.7 Closed-loop response of granulator to +10 step change in set point for y1 – left plot is outputs, right plot is inputs (dashed line, y1 and u1; dotted line, y2 and u2; dash-dot line, y3 and u3).

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Figure 23.8 Closed-loop response of granulator to +50 step change in set point for y1 with constraints enforced on the inputs. The left plot is outputs, right plot is inputs (dashed line, y1 and u1; dotted line, y2 and u2; dash-dot line, y3 and u3).

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Diabetes Mellitus

World’s most common and costly disease

About one in every 400 to 600 children and adolescents has type 1 diabetes mellitus (T1DM)

National Diabetes Fact Sheet, 2005, Centers for Disease Control and Prevention

Complications of T1DM reduce life expectancy by ~15 years through micro- and macro-vascular disease

• Heart disease and stroke

• Blindness

• Kidney disease

• Nervous system disease

Evidence that intensive insulin therapy (IIT) reduces complications

• Diabetes Control and Complications Trial Research Group, 1993

Increased hypoglycemic events with IIT

Diabetes Control and Complications Trial Research Group, 1993

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Model-Based Control Approach for Diabetes
[Parker, Peppas, Doyle III, IEEE Trans Biomed. Eng. 1999]

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Figure 23.9 Block diagram for artificial β-cell, illustrating the meal as the most common disturbance. G denotes the blood sugar of the patient, Gm is the output of the glucose sensor, and Gsp is the glucose setpoint.

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Figure 23.10 Open-loop response of patient’s blood glucose when the insulin pump is turned off.

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Figure 23.11 Open-loop response of the patient’s blood glucose to a constant infusion rate of 15 mU/min  from her insulin pump.

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Figure 23.12 Open-loop response of patient’s blood glucose to a constant infusion rate of 25 mU/min  from her insulin pump.

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Figure 23.13 Closed-loop response of patient’s mean arterial blood pressure and cardiac output to a -10 mmHg change in the MAP set point.