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PROCESS CONTROL AND INSTRUMENTATION

3. Process control and instrumentation.pdf (Size: 224.78 KB / Downloads: 189)

INSTRUMENTATION

General concepts and terminology of measurement systems, static and dynamic

characteristics, errors, standards and calibration.

Introduction, principle, construction and design of various active and passive transducers.

Introduction to semiconductor sensors and its applications.

Design of signal conditioning circuits for various Resistive, Capacitive and Inductive

transducers and piezoelectric transducer.

Introduction to transmitters, two wire and four wire transmitters, Smart and intelligent

Transmitters. Design of transmitters.

Introduction to EMC, interference coupling mechanism, basics of circuit layout and

grounding, concept of interfaces, filtering and shielding.

Safety: Introduction, electrical hazards, hazardous areas and classification, non-hazardous

areas, enclosures – NEMA types, fuses and circuit breakers. Protection methods: Purging,

explosion proofing and intrinsic safety.

MODERN CONTROL SYSTEM

Introduction to control systems, properties of signals and systems. Convolution integral,

Ordinary differential equation, Transfer function, Pole zero concepts, effect of pole location

on performance specification. System models in state space, canonical model, MIMO

systems, solution of state equation, stability of systems in state space.

Linear algebra, vector spaces, span and change of basis, linear transformations. Gram

Schmidt orthogonalization criterion, QR decomposition. Singular Ivalue decomposition.

Computing eAT Controllability, Observability controller design, observer design, reduced

order observers, properties of controllability. Computing numerical rank of a matrix. Kalman

canonical forms, partial pole assignment using static pole output feedback. Design of non -

interacting systems.

PROCESS MODELLING AND SIMULATION

Introduction to modelling, a systematic approach to model building, classification of models.

Conservation principles, thermodynamic principles of process systems.

Development of steady state and dynamic lumped and distributed parameter models based on

first principles. Analysis of ill-conditioned systems.

Development of grey box models. Empirical model building. Statistical model calibration and

validation. Population balance models. Examples.

Solution strategies for lumped parameter models. Stiff differential equations. Solution

methods for initial value and boundary value problems. Euler’s method. R-K method,

shooting method, finite difference methods. Solving the problems using MATLAB/SCILAB.

Solution strategies for distributed parameter models. Solving parabolic, elliptic and

hyperbolic partial differential equations. Finite element and finite volume methods.

ADVANCED PROCESS CONTROL

Review of systems: Review of first and higher order systems, closed and open loop response.

Response to step, impulse and sinusoidal disturbances. Control valve types-linear, equal

percentage and quick opening valve. Design of valves. Transient response. Block diagrams.

Stability Analysis: Frequency response, design of control system, controller tuning and

process identification. Zigler-Nichols and Cohen-Coon tuning methods, Bode-Nyquist Plots -

Process modelling.

Special Control Techniques: Advanced control techniques, cascade, ratio, feed forward,

adaptive control, selective controls, computing relays, simple alarms, Smith predictor,

internal model control, theoretical analysis of complex processes.

Multivariable Control Analysis of multivariable systems, Interaction, examples of storage

tanks. Review of matrix algebra, Bristol arrays, Niederlinski index - Tuning of multivariable

controllers.

Sample Data Controllers: Basic review of Z transforms, Response of discrete systems to

various inputs. Open and closed loop response to step, impulse and sinusoidal inputs, closed

loop response of discrete systems. Design of digital controllers.