Bøker i Advanced Textbooks in Control and Signal Processing-serien

Robotics provides the know-how on the foundations of robotics: modelling, planning and control. It covers mobile robots, visual control and motion planning. A variety of problems are worked through, and the tools to find engineering solutions are explained.

This MATLAB exercise book accompanies the textbook Control Engineering, providing a platform for students to practice problem solving in the analysis and design of continuous and discrete control problems reflected in the main textbook.

This book shows how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. It details how to convert theoretically-based control algorithms into realistic real-world aerospace applications.

MATLAB (R) files supplied to assist in working through exercises and examples. Solutions manual pdf.

Following an introduction on system theory, this book shows the reader how to approach the system identification problem in a systematic fashion. It aims to teach students the fundamentals of systems identification without unduly complicated mathematics.

Introduces the proper tools to find engineering-oriented solutions. This book includes fundamental coverage of kinematics, statics and dynamics of manipulators, and trajectory planning and motion control in free space. It offers technological aspects that include hardware- and software-control architectures and industrial robot-control algorithms.

Robust Control Design with MATLAB (R) (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases.

The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners.

A comprehensive introduction to the most popular class of neural network, the multilayer perceptron, showing how it can be used for system identification and control.