The main objective of this course is to teach the fundamental aspectsof process dynamics and control, which includes developing dynamic models of processes,control strategies for linear time-invariant systems and instrumentationaspects. At the end of this course, the student would be able to: (i) develop transfer function (input-output) and state-space models for linear dynamical processes,(ii) characterize the dynamics and stability of processes based on mathematical analysis (iii) understand the principles of feedback and feedforward controllers (iv) design PID controllers using different tuning rules (v) carry out a frequency-domain analysis of control loop systems (vi) understand the philosophy of and design model-predictive controllers and (vii) assess performance of control loop systems. The course is conducted on the integrated theory-with-practice paradigm, wherein the classroom lectures are seamless integration of theory with live computational / simulation demonstrations of the concepts. Students are provided with the opportunity to reinforce and implement the course concepts in academic and real-life problems through assignments. The majority of this course is concerned with development, analysis and use of input-output (transfer function) models for control system design.MATLAB (a registered trademark), and its associated dynamic simulator Simulink (a registered trademark) provides the required software support for this course.
Motivation: Overview of control, modelling and control principles; course outline.System-theoretic models:First-principles models, linearization, linear time-invariant (LTI) systems, Laplace transforms, state-space and transfer function models.Stability analysis: Notions of stability for LTI systems; asymptotic and bounded-input, bounded-output stability.Response-based descriptions: Impulse-, step- and frequency-response models. Process characterization: Concepts of gain, time-constants and time-delays, first- andsecond-order systems, effects of zero and pole locations on process characteristics. Empirical models: Estimating response models from input-output data.Feedback control: Fundamentals, control instrumentation, closed-loop system analysis, overview of control system design.Stability analysis of closed-loop systems:Root locus techniques, Bode’s stability result, Nyquist diagramsPID controllers: Characteristics of PID controllers, design, performance criteria, stan- dard tuning rules, model-based tuning.Uncertainties in control design: Gain and phase margins, closed-loop characterization, small gain theorem.Two case studies in complete analysis of process dynamics and design of control system.Instrumentation: Sensors, actuators, valve characteristicsModel predictive control: Basics and foundations of predictive control, design of MPC, case study.Performance assessment: Control loop performance monitoring – overview, minimum variance benchmark, case study.Selected topics: Feedforward control, ratio control, cascade control.In addition: Use of MATLAB / SIMULINK for analysis of process dynamics and design of controllers.
D.E. Seborg, T.E. Edgar, D.A. Mellichamp (2016). Process Dynamics and Control, Wiley India Pvt. Ltd., Fourth Edition
- George Stephanopoulus (1984). Chemical Process Control: An Introduction to Theory and Practice, Prentice-Hall.B. Wayne Bequette (2003).
- Process Control – Modeling, Design & Simulation, Prentice Hall.B. Ogunnaike and W.H. Ray (1994).
- Process Dynamics, Modelling and Control, Oxford University Press.