[Proxima Technology Co., Ltd.]
Introducing the definitive introductory guide to next-generation control technology and model predictive control! “Learn Model Predictive Control with Python and CasADi” includes a wealth of Python code, so even beginners can learn while running the program in one day!
*View in browser* *Proxima Technology Co., Ltd.*
Press release: May 14, 2024
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Introducing the definitive introductory guide to next-generation control technology and model predictive control! “Learn Model Predictive Control with Python and CasADi” includes a wealth of Python code, so even beginners can learn while running the program in one day!
Proxima Technology Co., Ltd. (KDX Okachimachi, 5-24-16 Ueno, Taito-ku, Tokyo), which develops various AI systems mainly in the manufacturing industry.
6F) will start selling “Learn Model Predictive Control with Python and CasADi”, an introductory book on model predictive control, from June 18th (6/20 on Amazon)!
“Learn model predictive control with Python and CasADi”
https://amzn.asia/d/0W4QHUd
Cutting-edge control technology: model predictive control
The model predictive control method is based on the idea of
constantly predicting the future and calculating “good” control.If you use the analogy of shogi, this method involves reading deeply into the future and finding the best possible move at that time. , you might say.
Model predictive control is a technology that is beginning to show great results in humanoid robots, space rockets, self-driving cars, etc., but if the evolution of computers continues at this rate, the time may come when it will be used to control all kinds of devices. We believe that it has the potential to change the way all existing industries operate through significant energy savings and improved control performance.
*Publication background*
The impetus for writing this book stems from my experience of having great difficulty studying model predictive control due to the lack of Japanese literature at the time (and even now). Additionally, there was even less information on implementation, making it extremely difficult for beginners to apply this technology to real problems. I am extremely disappointed that such a wonderful technology is not becoming more widespread due to a simple lack of information, and I decided to write this because if it does not exist, we have no choice but to create it ourselves.
This book is written for university students who have studied control engineering from classical control to modern control, and for working adults who are involved in control-related work. We assume that the required mathematical knowledge is linear algebra and calculus equivalent to that of a second-year undergraduate student, and that the programming knowledge is sufficient to implement simple numerical calculation codes in Python.
Additionally, this book uses an open source library called CasADi. CasADi is a library that places particular emphasis on optimal control, so we decided to use it in this book.
Various demos
inverted pendulum
2D drone (quadrotor)
rubber string control
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