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Graduate Certificate Programs
Advanced Control Systems
Department of Electrical and Computer Engineering
The graduate certificate in Advanced Control Systems incorporates the broad range of control systems into its curriculum. There are four courses required to complete the certificate.
The following courses are required:
- Elec Eng 5300 Digital Control
- Elec Eng 6300 Linear Control Systems
Choose at least two courses from the following:
- Elec Eng 5320 Neural Networks Control and Applications
- Elec Eng 5330 Fuzzy Logic Control
- Elec Eng 5350 Plantwide Process Control
- Elec Eng 5360 System Simulation and Identification
- Elec Eng 5380 Autonomous Mobile Robots
- Elec Eng 6310 Optimal Control and Estimation
- Elec Eng 6330 Robust Control Systems
- Elec Eng 6390 Current Topics in Control Theory
- Elec Eng 6335 Discrete-Time Neural Network Control or Elec Eng 6350: Neural Network Control of Nonlinear Continuous-time Systems
- Elec Eng 5325 Applied Nonlinear or Elec Eng 6320 - Nonlinear Control Systems
Elec Eng 5300 Digital Control
Analysis and design of digital control systems. Review of ztransforms; root locus and frequency response methods; state space analysis and design techniques; controllability, observability and estimation. Examination of digital control algorithms. Prerequisite: Elec Eng 3320.
Elec Eng 6300 Linear Control Systems
Review of linear algebra, state variable formulations, solutions of state equations; controllability and observability; multivariable systems, matrix-fraction decompositions; design of state and output feedback controllers and observers; introduction to calculus of variations; linear quadratic regulators. Prerequisite: Elec Eng 3320.
Elec Eng 5320 Neural Networks Control and Applications
Introduction to artificial neural networks and various supervised and unsupervised learning techniques. Detailed analysis of some of the neural networks that are used in control and identification of dynamical systems. Applications of neural networks in the area of Control. Case studies and a term project. Prerequisites: Elec Eng 3320.
Elec Eng 5330 Fuzzy Logic Control
A mathematical introduction to the analysis, synthesis, and design of control systems using fuzzy sets and fuzzy logic. A study of the fundamentals of fuzzy sets, operations on these sets, and their geometrical interpretations. Methodologies to design fuzzy models and feedback controllers for dynamical systems. Various applications and case studies. Prerequisite: Elec Eng 3320.
Elec Eng 5350 Plantwide Process Control
Synthesis of control schemes for continuous and batch chemical plants from concept to implementation. Mulitloop control, RGA, SVD, constraint control, multivariable model predictive control, control sequence descriptions. Design project involving a moderately complicated multivariable control problem. Prerequisites: Chem Eng 4110 or Elec Eng 3320 or Elec Eng 3340 or graduate standing.
Elec Eng 5360 System Simulation and Identification
Computationally efficient methods of digital simulation of linear systems. Non-parametric identification. Parametric identification with least squares and recursive least squares algorithms. Algorithms programmed using MATLAB. Prerequisite: Elec Eng 3320.
Elec Eng 5380 Autonomous Mobile Robots
This course will provide an introduction to mobile robots and current approaches to robot autonomy. Topics include mobile robot systems, modeling and control, sensors and estimation, localization and mapping, and motion planning. Prerequisites: Elec Eng 3320 or equivalent and Stat 3117 or equivalent.
Elec Eng 6310 Optimal Control and Estimation
Review of linear quadratic regulators (LQR), LQR extensions; constrained optimization (Pontragin's minimum principle); review of probability theory and random processes; optimal prediction and filters; frequency domain properties of LQR and Kalman filters; linear quadratic Gaussian (LQG) control; model uncertainties, frequency shaping, LQG/LTR design methodology. Prerequisite: Elec Eng 6300.
Elec Eng 6330 Robust Control Systems
Performance and robustness of multivariable systems, linear fractional transformations, LQG/LTR advanced loop shaping, Youla parameterization, H (subscript infinity) optimal control, mixed H (subscript 2) and H (subscript infinity) control, controller synthesis for multiple objective optimal control, linear matrix inequalities theory and case studies. Prerequisite: Elec Eng 6300.
Elec Eng 6390 Current Topics in Control Theory
Topics of current interest in control theory literature. Offered as interest and demand warrant. Prerequisite: Consent of instructor.
Elec Eng 6335 Discrete-Time Neural Network Control
Neural network topologies, universal function approximation property, background on Lyapunov stability & dynamic systems, control of a class of nonlinear systems using single and multilayer neural networks, feedback linearization, strict & nonstrict feedback systems, MIMO system, system identification, output feedback control, and hardware implementation. Prerequisites: Elec Eng 6300.
Elec Eng 6350 Neural Network Control of Nonlinear Continuous-time Systems
Neural network topologies, universal function approximation property, background on Lyapunov stability and dynamic systems, control of a class of nonlinear systems and robot manipulators, feedback linearization, backstepping control, force control, neural observers, decentralized neural network control, neural network-based optimal control and applications. Prerequisite: Elec Eng 6300.
Elec Eng 5325 Applied Nonlinear
Program description currently not available.
Elec Eng 6320 Nonlinear Control Systems
Numerical solution methods, describing function analysis, direct and indirect methods of Liapunov stability, applications to the Lure problem - Popov circle criterion. Applications to system design and feedback linearizations. Prerequisite: Elec Eng 6300.
This graduate certificate is open to all persons holding a B.S. degree in any field of engineering from an ABET-accredited undergraduate program or a degree in a closely related technical field such as physics or mathematics. The minimum overal GPA in the B.S. degree program should be at least 2.5.
Once admitted to the program, the student must take four designated courses as outlined above. In order to receive a graduate certificate, the student must have an average GPA of 3.0 or better in the certificate courses taken.
Students admitted to the certificate program will have non-degree graduate status. If the four-course sequence is completed with a grade of B or better in each of the courses taken, they may apply for admission to the M.S. program in electrical engineering, provided that all other program prerequisites and admission requirements are met.
Students who do not have all of the prerequisite courses necessary to take the courses in the certificate program will be allowed to take "bridge" courses at either the graduate or undergraduate level to prepare for the formal certificate courses.
Once admitted to the program, a student will be given three years to complete the program so long as a B average is maintained in the courses taken.
Graduate certificates act as a gateway to a master’s degree. They are designed for working professionals who have real life work experience, but may not have time to take the GRE. Admission requirements for the graduate certificate program are more relaxed and credit earned may be counted toward the master's degree.
Students must earn a B or better in each certificate course in order to earn the certificate, and be eligible to apply for admission into the corresponding degree program without needing to submit GRE scores, or letters of recommendation.
This graduate certificate program acts as a gateway to the following master’s program:
Effective July 1, 2011, the Department of Education requires that all certificate programs must disclose particular Gainful Employment information to current and prospective students. The information that is provided in the disclosure includes the estimated cost of the certificate program as well as on-time graduation and job placement rates for this particular certificate program. The disclosure information is based on data from the 2017-18 school year(defined as the period between July 1, 2017, and June 30, 2018)
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