Elsevier has released a couple of new books that take deep dive into the programming of robots.
By Boris A. Skorohod
This book presents a new approach to training which can be applied to solve the control, identification, signal processing, and classification problems arising in practice.
It offers an improvement from the existing learning techniques in control, robotics, and machine learning.
The book provides examples of the use of diffuse algorithms for solving problems in various engineering applications.
It is ideal for researchers and graduate students in control, signal processing, and machine learning, says Elsevier.
Active Disturbance Rejection Control of Dynamic Systems: A Flatness Based Approach
By Hebertt Sira-Ramirez, Alberto Luviano-Juárez, Mario Ramírez-Neria and Eric William Zurita-Bustamante
This book describes the linear control of uncertain nonlinear systems.
The net result is a practical controller design that is simple and surprisingly robust, one that also guarantees convergence to small neighborhoods of desired equilibria or tracking errors that are as close to zero as desired.
This methodology differs from current robust feedback controllers characterized by either complex matrix manipulations, complex parameter adaptation schemes and, in other cases, induced high frequency noises through the classical chattering phenomenon.
