Uploaded June 2021 | Updated September 2026, 5 hours ago
Original Parallel Quadratic Programming Algorithm: merl.com/publications/docs/TR2011-056.pdf
My Paper: ieeexplore.ieee.org/document/9282815
Hello!
In this video you will learn how to implement a Quadratic Optimization solver in Simulink without using any built in toolboxes. Optimization is an extremely important mathematical concept used within statistics, machine learning, control systems, and artificial intelligence algorithms. It is also used in all industries (finance, engineering etc.).
The background is covered in that paper I published as part of my Master's thesis. This video is the first part of my tutorial series on model predictive control (MPC). You will learn the following Simulink concepts:
1) Working with project files
2) Variant Subsystems
3) Iterator Subsystems (For / While Loops)
4) Struct objects
5) Assignment and Selector blocks
You will also get the hang of basic Optimization concepts needed for MPC such as:
1) Cost function
2) Constraints
3) Primal-Dual Procedure
Thanks for watching!
~~My Udemy Courses on Motion Planning / Navigation / Trajectory Planning:
udemy.com/course/autonomous-robots-nonholonomic-motion-planning-algorithms
Buy Coffee: buymeacoffee.com/vdengineering
My Website: vinayakd.com
My Instagram: instagram.com/vinayak_desh
Original Parallel Quadratic Programming Algorithm: merl.com/publications/docs/TR2011-056.pdf
My Paper: ieeexplore.ieee.org/document/9282815
Hello!
In this video you will learn how to implement a Quadratic Optimization solver in Simulink without using any built in toolboxes. Optimization is an extremely important mathematical concept used within statistics, machine learning, control systems, and artificial intelligence algorithms. It is also used in all industries (finance, engineering etc.).
The background is covered in that paper I published as part of my Master's thesis. This video is the first part of my tutorial series on model predictive control (MPC). You will learn the following Simulink concepts:
1) Working with project files
2) Variant Subsystems
3) Iterator Subsystems (For / While Loops)
4) Struct objects
5) Assignment and Selector blocks
You will also get the hang of basic Optimization concepts needed for MPC such as:
1) Cost function
2) Constraints
3) Primal-Dual Procedure
Thanks for watching!
~~My Udemy Courses on Motion Planning / Navigation / Trajectory Planning:
udemy.com/course/autonomous-robots-nonholonomic-motion-planning-algorithms
Buy Coffee: buymeacoffee.com/vdengineering
My Website: vinayakd.com
My Instagram: instagram.com/vinayak_desh
