Optimization and State Estimation Fundamentals

Optimization and State Estimation Fundamentals

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.

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

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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

Rating: 3.2

Level: Intermediate Level

Duration: 4.5 hours

Instructor: Dr. Ryan Ahmed, Ph.D., MBA