Graduate Courses

• EECE 445 - Introduction to Control Systems
  Introduction to the feedback control problem. Plant modelling, transfer function and state-space descriptions. Stability criteria. Nyquist and root-locus design. Introduction to analytical design. Z-transforms and digital control. Laboratory design project.
  
  Prerequisite: C- or better in 314 and Math 312. Fall, Spring



• EECE 446 - Design of Feedback Control Systems
  Modelling of continuous and sampled-date control systems. State-space representation. Sensitivity, stability, and optimization of control systems. Design of compensators in the frequency and time domains. Phase-plane and describing function design for non-linear systems.
  
  Prerequisite: C- or better in 445.



• EECE 500 - Theory of Linear Systems
  State space representation of dynamical systems. Analysis of linear models in control systems, network theory, signal processing. continuous, discrete and sampled representations.
  
  Prerequisite: 314, and Math 321 or Math 464. Fall



• EECE 506 - Optimization Theory
  Introduction to optimization by computer. Linear programming, nonlinear programming, and combinatorial optimization. Simplex method, Karmarkar's method, dynamic programming, gradient and conjugate gradient search, quasi-Newton methods, Fibonacci and golden search methods, penalty methods, projection methods, Lagrange multiplier methods, greedy methods, and divide and conquer methods.

• EECE 514 - Nonlinear and Adaptive Control
  

  Linearization of nonlinear systems. Phase-plane analysis. Lyapunov stability analysis. Hyperstability and Popov stability criterion. Direct and indirect adaptive control systems. Adaptive estimation. Stability of adaptive control systems.
  
  Prerequisite: 446, 500.



• EECE 544 - Digital Control Systems
  

  Discrete-time signals and systems. Performance and stability criteria. Design approaches for digital control of analog plants. Sampling and signal quantization. Optimal and adaptive control. Microprocessor implementation of digital control algorithms.
  
  Prerequisite: 446, 500.



• EECE 545 - Large-Scale Systems
  

  Introduction to large-scale systems, models for large scale systems, model reduction, hierarchical control, decentralized control, structural properties of large-scale systems.
  
  Prerequisite: 500.



• EECE 546 - Multivariable Control Theory
  

  Hermite, Smith, and Smith-McMillan canonic forms for polynomial and rational matrices. Coprime matrix-fraction representations for rational matrices. Bezout identity. Poles and zeros for multivariable systems. Matrix-fraction approach to feedback system design. Optimal linear-quadratic-Gaussian (LQG) control. Multivariable Nyquist stability criteria.
  
  Prerequisite: 445, 500. Spring



• EECE 547 - Neural Networks
  

  A study of neuron models, basic neural nets and parallel distributed processing.



• EECE 548 - Fuzzy Logic with Applications
  

  (Also offered as C E 548.) Theory of fuzzy sets; foundations of fuzzy logic. Fuzzy logic is shown to contain evidence, possibility, and probability logics; course emphasizes engineering applications; control, pattern recognition, damage assessment, decisions; hardware/software demonstrations.
  
  Prerequisite: Basic set theory and probability theory.



• EECE 649 - Special topics in Control Systems
  
  Prerequisite: 546.