Optimization and State Estimation Fundamentals

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

What you'll 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

Requirements
Basic Mathematics background

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

Who this course is for:
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