adaptive

Elsevier has published two new books in the area of Control Systems. 

Learning-Based Adaptive Control: An Extremum Seeking Approach – Theory and Applications by Mouhacine Benosman

Adaptive control is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control.

As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change.

The book offers a new perspective about how to deal with these variations.

By merging together Model-Free and Model-Based learning algorithms, it demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained.

The book is aimed at researchers and graduate students in adaptive robust control, and engineers in the mechatronics field.

Control of Complex Systems: Theory and Applications edited by Kyriakos Vamvoudakis and Sarangapani Jagannathan

This book cover a variety of interests within the broader field of learning, adaptation, optimization and networked control.

It groups these topics into five sections:

1. Introduction and Background on Control Theory
2. Adaptive Control and Neuroscience
3. Adaptive Learning Algorithms
4. Cyber-Physical Systems and Cooperative Control
5. Applications

The diversity of the research presented gives readers a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists.

The book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems.