(SEM VIII) THEORY EXAMINATION 2023-24 COMPUTERIZED PROCESS CONTROL

SECTION A

(Attempt all | 2 × 10 = 20 Marks)

a. Role of computers in process control
Computers are used to monitor, control, optimize, and supervise industrial processes by processing real-time data, executing control algorithms, and improving accuracy, safety, and efficiency.

b. Concept of Aided Process Control
Aided process control refers to the use of computers to assist operators in monitoring and decision-making while the final control action may still be manual.

c. Elements of a computer-aided process control system
The main elements are sensors, signal conditioning units, A/D converters, computer system, control software, actuators, and human–machine interface.

d. ISO Reference Model for communication
The ISO model consists of seven layers: Physical, Data Link, Network, Transport, Session, Presentation, and Application layers.

e. Concept of Process Modeling
Process modeling is the mathematical representation of a physical process to analyze, predict, and control its behavior.

f. Need of process model
Process models are needed for system analysis, controller design, simulation, prediction of behavior, and optimization of process performance.

g. Applications of statistical control
Statistical control is applied in quality control, process monitoring, defect detection, performance analysis, and process improvement.

h. Advantages of computerized process control
It provides high accuracy, fast response, improved safety, reduced manpower, better data handling, and efficient process optimization.

i. Principle of electric oven temperature control
It works on feedback control where temperature is sensed, compared with set value, and heating power is adjusted to maintain desired temperature.

j. Advantages of furnace temperature control
It ensures uniform heating, energy efficiency, improved product quality, reduced fuel consumption, and safe operation.

SECTION B

(Attempt any THREE | 3 × 10 = 30 Marks)

2(a) Computer-aided process control architecture

Computer-aided process control architecture consists of field level (sensors and actuators), control level (controllers, PLCs, computers), and supervisory level (operator interface, data storage). Sensors collect data, computers process signals, control algorithms generate outputs, and actuators regulate the process. This layered architecture ensures reliable and efficient control.

2(b) Types of computer control process software

The main types are:

Operating system software – manages hardware and real-time tasks

Control software – implements control algorithms like PID

Supervisory software – handles monitoring, alarms, and data logging

Application software – supports process optimization and analysis

Together, they enable automation and reliable process control.

2(c) Physical model, Control model, Process modeling

(Any two)

Physical model:
Represents the actual physical behavior of the system using laws of physics.

Control model:
Used for controller design and focuses on input–output relationships.

Process modeling:
Involves developing mathematical equations that describe dynamic behavior of industrial processes.

2(d) Predictive control and Adaptive control

Predictive control uses a process model to predict future outputs and optimizes control actions accordingly.
Adaptive control automatically adjusts controller parameters when system characteristics change.
Both are used for complex, time-varying processes.

2(e) Reheat furnace temperature control

Reheat furnace temperature control maintains uniform temperature during reheating of metal billets. Sensors measure temperature, controllers regulate fuel and air flow, and feedback ensures desired temperature profile for quality processing.

SECTION C

3(a) Process-related interfaces in control system

Process-related interfaces include sensors, transducers, signal conditioners, A/D and D/A converters, communication interfaces, and actuators. They connect the physical process with the computerized control system.

3(b) Centralized vs Distributed control system

Centralized control uses a single controller for the entire plant, while distributed control uses multiple controllers. DCS offers higher reliability, scalability, faster response, and fault tolerance compared to centralized systems.

4(a) Elements of computer-aided process control system

The elements include process, sensors, signal conditioning, computer hardware, control software, actuators, and operator interface. Each element works together to achieve effective control.

4(b) Real-time operating system (RTOS)

RTOS is designed to handle real-time tasks with strict timing constraints. It provides task scheduling, interrupt handling, memory management, and reliability for time-critical control applications.

5(a) Modeling and steps in modeling procedure

Modeling is the representation of a system using mathematical equations.
Steps include system identification, assumption formulation, equation development, parameter estimation, validation, and refinement.

5(b) Supervisory control in computerized process control

Supervisory control monitors overall process performance, adjusts set points, coordinates multiple controllers, and provides alarms and reports for operators.

6(a) Homogeneous transform and inverse in robot elements

Homogeneous transformation represents position and orientation of robot links using matrix form. Its inverse is used to find reverse transformation for coordinate conversion.

6(b) Inferential control and Cascade control

Inferential control estimates unmeasured variables using models.
Cascade control uses multiple controllers where output of one controller sets the reference for another, improving disturbance rejection.

7(a) Computer-aided control of electric power generation plant

Computer control optimizes boiler pressure, turbine speed, generator output, fuel efficiency, and safety. It improves reliability, load balancing, and energy efficiency.

7(b) Model formulation, solution finding, results analysis

(Any two)

Model formulation: defining equations of the system
Solution finding: solving equations using analytical or numerical methods
Results analysis: interpreting outcomes to improve system performance