Optimization Methods for Systems and Control
This course provides an introduction to various methods of obtaining the extremum (minimum or maximum) of a non-dynamical system and the use of these methods in real-life applications. Computational methods for nonlinear optimization; unconstrained optimization. Constrained optimization; linear programming; simplex method for solving linear programs; Lagrange's conditions, the Karush-Kuhn-Tucker (KKT) conditions, Least squares, Convex optimization, Global optimization methods: Genetic algorithms and Particle swarm optimization (PSO) method.
ECE58000
Credit Hours:
3Learning Objective:
- Use various methods to compute minimum or maximum of nonlinear functions of many variables
- Solve linear programming problems
- Find minimum or maximum of nonlinear functions of many variables using population-based methods
- Apply various optimization methods learned in the course to real-life design problems
Description:
This course provides an introduction to various methods of obtaining the extremum (minimum or maximum) of a non-dynamical system and the use of these methods in real-life applications. Computational methods for nonlinear optimization; unconstrained optimization. Constrained optimization; linear programming; simplex method for solving linear programs; Lagrange's conditions, the Karush-Kuhn-Tucker (KKT) conditions, Least squares, Convex optimization, Global optimization methods: Genetic algorithms and Particle swarm optimization (PSO) method.