Courses | VD Academic Affairs

A capstone design course, students are exposed to creative design and synthesis in the various areas of industrial and management systems engineering. All knowledge acquired in mathematical modeling and economic techniques are utilized in conducting the design analysis.

Basic methods of modern control system theory. Time domain vs. frequency domain analysis. State space representation of linear continuous systems, features extracted from time domain representation, the concepts of stability, controllability, stabilizability, observability and detectability of linear systems. State space representation and features of discrete time linear systems. Pole assignments technique and Lunberger observer for continuous time linear systems, separation principle.

A unified approach to the modeling, analysis and simulation of energetic dynamic systems. Introduction to multi-domain systems. System dynamic response in time and frequency domains. Introduction to model reduction. Applications to various dynamic systems such as mechanical, thermal, fluid, electrical, electronic, chemical, electromechanical systems, emphasis on modelling and simulation of hybrid systems using modern computer-aided tools.

Introduction to nonlinear programming for static optimization, solution of static optimization problems without constrains, with equality constrains and with inequality constrains. The dynamic optimization problem, calculus of variation, maximum principle, dynamic programming. Optimal linear regulation problem and its properties, extension to servo-mechanism problem.

Characteristics of nonlinear system models, phase plane analysis, describing function approach. Stability of nonlinear systems, first and second theory of Lyapunov, second method of Lyapunov. Frequency domain stability criteria. Linearization and its properties. Introduction to operate theory and its applications to the study of nonlinearities.

Introduction to Gaussian random variables, conditional expectation and covariance matrices. State estimation and observation of discrete linear systems using Kalman filter. Systems identification of linear dynamic systems, problem formulation, least squares techniques and its application to the transfer function and state space description of linear discrete time systems, recursive least square techniques, maximum likelihood estimator, experimental method. Optimal control of linear quadratic Gaussian regulator problem.

Modeling of Process Quality. Inferences about Process Quality. Methods and Philosophy of Statistical Process Control. Control charts. Shewart, CUSUM and EWMA charts. Process capability analysis. Process Improvements with Designed Experiments. Acceptance sampling. Relation of SPC to Conventional Process Control.

Control instrumentation concepts, devices, and systems. Sensing and signal conversion and conditioning. Actuators and transmitters. Control valves characteristics and sizing. Controller types and tuning. Digital systems. Smart sensors and transmitters.

Hardware and software aspects of computer based control systems. Discretization techniques in frequency and time domain. Digital controller design techniques. Optimal control. Adaptive and self tuning controllers.

Concept of decomposition-coordination techniques. Decomposition-coordination of large scale static optimization problems, goal coordination technique, model coordination and mixed method. Optimization and control of large scale linear quadratic problems, goal coordination method, interaction-prediction approach, Tamura's algorithms, hierarchical optimal controller, the concept of decentralized control. Optimization and control of nonlinear systems. Introduction to model simplification, aggregation technique. Introduction to time scale modeling and singular perturbation.

Observer design, separation principle, elements of estimation theory, least square estimation, extended least square method, model follower technique, self tuning, introduction to neural network for systems modeling.

An upper division of graduate technical elective treating topics in Engineering mostly not covered in other courses, chosen at the discretion of the Graduate Program Committee.

Project course for non-thesis students.