Optimization and State Estimation Fundamentals

Learn optimization fundamentals and state estimation techniques with this practical course!

Ratings: 3.43 / 5.00




Description

This course covers the details of how to develop optimization and state estimation algorithms and apply them to real world practical applications. The course covers the following topics:

  1. Basic of system modeling which is how to describe any mechanical or electrical system in a mathematical form. 
  2. The theory of operation of Genetic Algorithm optimization which is extensively used in several industrial and academic applications 
  3. How to optimize parameters using experimental data
  4. Implementation of Genetic algorithm logic in MATLAB environment and apply it to real world problems
  5. How to represent systems in State space representation form. 
  6. Theory of operation of state estimation strategies such as Kalman Filtering 
  7. How to apply state estimation strategies such as Kalman filtering in MATLAB to real world problems.

What You Will Learn!

  • Understand the theory of operation of Kalman filters and optimization strategies
  • Estimate system states using Kalman Filters
  • Extract parameters from data using optimization strategies
  • Implement optimization and state estimation algorithms in MATLAB environment

Who Should Attend!

  • For people who want to learn how to develop optimization/Estimation algorithms in MATLAB and Simulink
  • For students who want to learn Genetic Algorithm optimization theory and practical implementation
  • For students who want to learn Kalman filtering and state estimation strategies implementation