Author(s) Name: Timothy Sands
Kirchhoffs laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newtons laws, while rotational motion mechanics comply with Eulers moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn.
This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers to very advanced topics of deterministic artificial intelligence, espoused in the book with applications to both electromechanics (e.g. the forced van der Pol equation) and also motion mechanics (i.e. Eulers moment equations). The reader will learn how to bestow self-awareness and express optimal learning methods for the self-aware object (e.g. robot) that require no tuning and no interaction with humans for autonomous operation.
The topics learned from reading this text will prepare students and faculty to investigate interesting problems of mechanics. It is the fondest hope of the editor and authors that readers enjoy the book.
Table of Contents
1. Stochastic Artificial Intelligence: Review Article
2. Simulated Real-Time Controller for Tuning Algorithm Using Modified Hill Climbing Approach Based on Model Reference Adaptive Control System
3. Random Forest-Based Ensemble Machine Learning Data-Optimization Approach for Smart Grid Impedance Prediction in the Powerline Narrowband Frequency Band
4. Application of Artificial Neural Networks for Accurate Prediction of Thermal and Rheological Properties of Nanofluids
5. The Technique of Automated Design of Technological Objects with the Application of Artificial Intelligence Elements
6. Deterministic Approaches to Transient Trajectory Generation
7. Sinusoidal Trajectory Generation Methods for Spacecraft Feedforward Control
8. Modern Control System Learning
ISBN: 978-1-78984-112-1
Publisher: IntechOpen
Year of Publication: 2020
Book Link: Home Page Url
