GTU Study
KHUDKIBOOK
ADVANCE PROCESS CONTROL
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4361703
Code: 4361703
Credits: 4
Semester 6
PE
Advance Process Control
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Advance Process Control Syllabus — Unit-wise Content
The official GTU curriculum for Advance Process Control (subject code 4361703) as prescribed for PE · Semester 6 divides the course into 4 units, covering 75 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (4361703)Unit 1 Introduction to Process Control
- 1. Define process and process control.
- 2. Enlist types of process.
- 3. List benefits, difficulties and Requirements of Process Control Implementation.
- 4. Classify process variables.
- 5. Compare Open-loop vs. Closed-loop Systems.
- 6. Compare Servo vs. Regulatory Control.
- 7. Compare Feedback and Feedforward Control Configuration.
- 8. List Steps followed in Synthesis of a Control System.
- 1.2. Evolution of Process Control.
- 1.3. Concept, Definition, and Types of Process.
- 1.4. Benefits, Difficulties, and Requirements of Process Control Implementation.
- 1.5. Classification of Process Variables.
- 1.6. Open-loop vs. Closed-loop Systems.
- 1.7. Servo vs. Regulatory Control.
- 1.8. Feedback and Feedforward Control Configuration.
- 1.9. Steps in Synthesis of a Control System. Advance Process Control Course Code: 4361703
Unit 2 Closed-loop Response
- 1. Derive transfer functions of Closed Loop.
- 2. Explain P controller.
- 3. Explain PI controller.
- 4. Explain PD controller.
- 5. Explain PID controller.
- 6. Discuss response of controller for step, pulse, ramp, sinusoid.
- 7. Compare Various Controller Configurations.
- 8. Discuss Controller Tuning procedure.
- 2.1. Transfer Functions of Closed Loop control system.
- 2.2. Proportional Controller in Closed Loop.
- 2.3. Integral Controller in Closed Loop.
- 2.4. PI Controller in Closed Loop.
- 2.5. PD Controller in Closed Loop.
- 2.6. PID Controller in Closed Loop.
- 2.7. Controller response for different test inputs.
- 2.8. Integral Windup and Anti- windup.
- 2.9. Comparison of Various Controller Configurations.
- 2.10. Controller tuning methods: Process Reaction Curve, Ziegler –Nichols. Evaluation Criteria- IAE, ISE, ITAE. Unit– III Digital Controllers
- 1. Define key parts of Direct Digital Control system.
- 2. Explain DDC operation and communication flow.
- 3. Apply DDC benefits in varied scenarios for efficiency and scalability.
- 4. Design digital controller for specific applications using discrete domain analysis.
- 5. Evaluate system stability, critique various DDC configurations in discrete domain.
- 6. Discuss DDC application in brief.
- 7. Analyze trends in DDC like IoT integration, machine learning, and analytics.
- 3.1. Introduction to DDC.
- 3.2. Components a n d w o r k i n g o f DDC.
- 3.3. Benefits of DDC.
- 3.4. Digital Controller Realization.
- 3.5. Discrete Domain Analysis.
- 3.6. Application of DDC DDC of air heater. DDC of DC motor speed control.
- 3.7. Future Trends and Innovations IoT Integration Machine Learning in DDC Advanced Analytics
Unit 3 Advance Control Strategies
- 1. Explain cascade control.
- 2. Explain Feedforward control.
- 3. Explain Feedforward- feedback Control Configuration.
- 4. Explain Ratio Control with an examples.
- 5. Explain Selective Control.
- 6. Explain Adaptive Control.
- 7. Compare Selective Control v/s Adaptive Control.
- 8. Draw and explain Adaptive
- 4.1. Cascade Control: Features, Cascade control of Jacketed CSTR and boiler drum level, and advantages of Cascade Control.
- 4.2. Feedforward Control: Feedforward control of distillation column, heat exchanger, and drum boiler, advantages and disadvantages of Feedforward Control.
- 4.3. Ratio Control.
- 4.4. Selective Control: Override control, protection of a drum boiler, protection of steam Advance Process Control Course Code: 4361703 Control Configuration. distribution system, and prevention of flooding in distillation column, Split-range control.
- 4.5. Adaptive Control.
- 4.6. Adaptive Control Configuration: Programmed adaptive control, Self-adaptive controller, Model Reference adaptive controller, and self- tuning Regulator.
Unit 4 Introduction to Neural-Fuzzy system
- 1. Define Artificial Neural Network (ANN).
- 2. Classify Artificial Neural Network (ANN).
- 3. List Applications of ANN.
- 4. Define Fuzzy Logic.
- 5. List Applications of Fuzzy Logic.
- 6. Compare Fuzzy vs. ANN.
- 5.1. Introduction Artificial Neural Network (ANN).
- 5.2. Perceptron Model for ANN.
- 5.3. Classification of ANN.
- 5.4. Introduction of fuzzy logic.
- 5.5. Crisp vs. Fuzzy Logic.
- 5.6. Fuzzy Logic vs. Probability.
- 5.7. Applications of Fuzzy Logic and ANN. Note: The UOs need to be formulated at the ‘Application Level’ and above of Revised Bloom’s Taxonomy’ to accelerate the attainment of the COs and the competency.
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