EE 107: Control System Design The course covers design of linear feedback control systems, selected from the following: lag-lead compensators; pole placement controllers; state-variable feedback and observers; linear quadratic optimal control, stochastic systems, sampled-data-and computer-controlled systems; and phase-plane and describing function techniques for nonlinear systems.
Prerequisite(s): EE 3064.
EE 3064: Feedback Control This course introduces analysis and design of linear feedback-control systems; modeling of physical systems, performance specifications, sensitivity and steady-state error; Routh- Hurwitz and Nyquist Stability tests; the use of Root Locus and frequency-response techniques to analyze system performance and design compensation (lead/lag and PID controllers) to meet performance specifications. Students analyze and design control systems using math packages in the alternate-week computer laboratory. The course establishes the foundation of feedback-control theory for use in more advanced courses; introduces control-systems design concepts and practices; and develops facility with computer design packages for design and simulation.
Prerequisite(s): EE 3054 (C- or better) and PH 2023.
EL 5213: Introduction to Systems EngineeringThis course introduces fundamentals of systems engineering process. Topics: Multidisciplinary systems methodology, design and analysis of complex systems. Brief history of systems engineering. Mathematical models. Objective functions and constraints. Optimization tools. Topics to be covered include identification, problem definition, synthesis, analysis and evaluation activities during conceptual and preliminary system design phases. Decision analysis and utility theory. Information flow analysis in organizations. Elements of systems management, including decision styles, human information processing, organizational decision processes and information system design for planning and decision support. Basic economic modeling and analysis. Requirements development, life-cycle costing, scheduling and risk analysis. Application of computer-aided systems engineering (CASE) tools.
EL 5223: Sensor Based RoboticsThe course covers robot mechanisms, robot arm kinematics (direct and inverse kinematics), robot arm dynamics (EulerLagrange, Newton-Euler and Hamiltonian Formulations), six degree-of-freedom rigid body kinematics and dynamics, quaternion, nonholonomic systems, trajectory planning,various sensors and actuators for robotic applications, end-effector mechanisms, force and moment analysis, introduction to control of robotic manipulators.
Prerequisite(s): Graduate status. Corequisite(s): EE 3064. Pre/Co-requisite: EE 3064.
EE 5253: Applied Matrix Theory The course focuses on in-depth introduction to theory and application of linear operators and matrices in finite-dimensional vector space. Topics: determinants, eigenvalues and eigenvectors. Theory of linear equations. Canonical forms and Jordan canonical form. Matrix analysis of differential and difference equations. Singular value decomposition. Variational principles and perturbation theory. Numerical methods.
Prerequisite(s): Graduate status, MA 2012, MA 2132, MA 2112 and MA 2122.
EL 6213: System Modeling, Analysis and DesignSystems Engineering is an interdisciplinary approach and means to enable the realization of complex systems with desirable specifications. This course introduces basic tools for modeling, analysis and design of complex engineering systems. Topics of this course include Modeling methods and Computer Aided Systems Engineering (CASE) formal structures, CASE tools for solving practical systems related problems, quantitative techniques including linear programming, basic graph tools, architecture development methods, interface design strategies, graphical modeling techniques, and fundamentals of decision and risk analysis for systems engineering. Successful systems engineering cases will also be studied.
EL 6223: Nonlinear and Sampled-data Control SystemsIntroduction of nonlinear systems. Phase plane analysis, nonlinearities, linearization, limit cycles and averaging. Stability techniques: describing function, Lyapunov functions, Popov locus ad circle criterion. Analysis and design of sampled-data systems by Z-transforms and state variable methods. Semiglobal and global stabilization of nonlinear sampled-data systems.
Prerequisite(s): Graduate status and EL 6253.
EL 6233: System Optimization Methods Formulations of system optimization problems. Elements of functional analysis applied to system optimization. Local and global system optimization with and without constraints. Variational methods, calculus of variations, and linear, nonlinear and dynamic programming iterative methods. Examples and applications. Newton and Lagrange multiplier algorithms, convergence analysis.
Prerequisite(s): Graduate status and EL 5253 or EL 6253.
EL 6243: System Theory and Feedback ControlDesign of single-input-output and multivariable systems in frequency domain. Stability of interconnected systems from component transfer functions. Parameterization of stabilizing controllers. Introduction to optimization(Wiener-Hopf design).
Prerequisite(s): Graduate status and EE 3064.
EL 6253: Linear systems Basic system concepts. Equations describing continuous and discrete-time linear systems. Time domain analysis, state variables, transition matrix and impulsive response. Transform methods. Time-variable systems. Controllability, observability and stability. SISO pole placement, observer design. Sampled data systems.
Prerequisite(s): Graduate status and EE 3054 or EL 5253.
EL 7253: State-space design for linear control systems Topics covered in this course include canonical forms; control system design objectives; feedback system design by MIMO pole placement; MIMO linear observers; the separation principle; linear quadratic optimum control; random processes; Kalman filters as optimum observers; the separation theorem; LQG; Sampled-data systems; microprocessor-based digital control; robust control and the servocompensator problem.
Prerequisite(s): Graduate status and EL 6253.
EL 8233: Optimal Control TheoryThis course focuses on optimal control problem for deterministic systems with various constraints. Topics: solution for both continuous and discrete-time systems using the maximum principle and dynamic programming. Singular arcs. Neighboringoptimal solutions. Fuel and time optimal control problems. Computational methods.
Prerequisite(s): Graduate status, EL 6233 and EL 6253.
EL 8253: Large-Scale Systems and Decentralized ControlThis course introduces analysis and synthesis of large-scale systems. Topics: systemorder reduction algorithms, interconnected system stability, series expansion and singular perturbation. Lyapunov designs. Applications to traffic networks, power systems and transportation networks. Decentralized control: decentralized fixed-mode, LQR, frequency-shaped cost functional and overlapping decompositions. Stability of interconnected systems and Vector Lyapunov analysis.
Prerequisite(s): Graduate status and EL 7253 or instructor’s permission.
EL 8223: Applied Nonlinear Control Stability and stabilization for nonlinear systems; Lyapunov stability and functions, input-output stability and control Lyapunov functions. Differential geometric approaches for analysis and control of nonlinear systems: controllability, observability, feedback linearization, normal form, inverse dynamics, stabilization, tracking and disturbance attenuation. Analytical approaches: recursive back stepping, input-to-state stability, nonlinear small-gain methods and passivity. Output feedback designs. Various application examples for nonlinear systems including robotic and communication systems.
Prerequisite(s): Graduate status and EL 6253 or EL 7253.