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Optimization And State Estimation Fundamentals
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Optimization And State Estimation Fundamentals
Last updated 6/2018
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.56 GB | Duration: 4h 36m

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.
Overview
Section 1: State Estimation
Lecture 1 Introduction to State Estimation
Lecture 2 State Space Representation
Lecture 3 State Space Block diagram
Lecture 4 State Space Example
Lecture 5 OCV-RRC Battery Model in State Space
Lecture 6 OCV-RRC Battery Model in State Space - MATLAB Example
Lecture 7 Introduction to Kalman Filters
Lecture 8 Conceptional Overview of Kalman Filter
Lecture 9 Kalman Filter Theory of operation
Lecture 10 Kalman Filter Implementation
Lecture 11 Extended Kalman Filter
Lecture 12 Extended Kalman Filter Algorithm in MATLAB
Lecture 13 Extended Kalman Filter Algorithm in MATLAB - Part 2
Section 2: Optimization
Lecture 14 Introduction to Genetic Algorithm Optimization
Lecture 15 GA Optimization Operation Overview
Lecture 16 Model Used for Parameters Optimization
Lecture 17 How to create an experimental model to test your GA algorithm
Lecture 18 MATLAB Example: Genetic Algorithm for Battery Parameter optimization #1
Lecture 19 MATLAB Example: Simulation Model Testing
Lecture 20 GA Optimization Example in MATLAB
Lecture 21 GA Optimization Example in MATLAB - Part 2
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


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