Written by two of Europe's leading robotics experts, this book provides the tools for a unified approach to the modelling of robotic manipulators, whatever their mechanical structure. No other publication covers the three fundamental issues of robotics: modelling, identification and control. It covers the development of various mathematical models required for the control and simulation of robots.·World class authority·Unique range of coverage not available in any other book·Provides a complete course on robotic control at an undergraduate and graduate level

This compact and original reference and textbook presents the most important classical and modern essentials of control engineering in a single volume. It constitutes a harmonic mixture of control theory and applications, which makes the book especially useful for students, practicing engineers and researchers interested in modeling and control of processes. Well written and easily understandable, it includes a range of methods for the analysis and design of control systems.

Most of the research and experiments in the fields of modeling and control systems have spent significant efforts to find rules from various complicated phenomena by principles, observations, measured data, logic derivations. The rules are normally summarized as concise and quantitative expressions or “models”. “Identification” provides mechanisms to establish the models and “control” provides mechanisms to improve system performances. This book reflects the relevant studies and applications in the area of renewable energies, with the latest research from interdisciplinary theoretical studies, computational algorithm development to exemplary applications. It discusses how modeling and control methods such as recurrent neural network, Pitch Angle Control, Fuzzy control, Sliding Mode Control and others are used in renewable systems. It covers topics as photovoltaic systems, wind turbines, maximum power point tracking, batteries for renewable energies, solar energy, thermal energy and so on. This book is edited and written by leading experts in the field and offers an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, control system and energy.

A presentation of techniques in advanced process modelling, identification, prediction, and parameter estimation for the implementation and analysis of industrial systems. The authors cover applications for the identification of linear and non-linear systems, the design of generalized predictive controllers (GPCs), and the control of multivariable systems.

Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches. This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering. - Explains the latest research outputs on modeling, identification and adaptive control for systems with nonsmooth dynamics - Provides practical application and experimental results for robotic systems, and servo motors

This book covers recent results in the analysis, identification and control of systems described by Volterra models. Topics covered include: qualitative behavior of finite Volterra models compared and contrasted with other nonlinear model classes, structural restrictions and extensions to Volterra model class, least squares and stochastic identification approaches, model inversion issues, and direct synthesis and model predictive control design, guidelines for practical applications. Examples are drawn from Chemical, Biological and Electrical Engineering. The book is suitable as a text for a graduate control course, or as a reference for both research and practice.

Fractional-order Modelling of Dynamic Systems with Applications in Optimization, Signal Processing and Control introduces applications from a design perspective, helping readers plan and design their own applications. The book includes the different techniques employed to design fractional-order systems/devices comprehensively and straightforwardly. Furthermore, mathematics is available in the literature on how to solve fractional-order calculus for system applications. This book introduces the mathematics that has been employed explicitly for fractional-order systems. It will prove an excellent material for students and scholars who want to quickly understand the field of fractional-order systems and contribute to its different domains and applications. Fractional-order systems are believed to play an essential role in our day-to-day activities. Therefore, several researchers around the globe endeavor to work in the different domains of fractional-order systems. The efforts include developing the mathematics to solve fractional-order calculus/systems and to achieve the feasible designs for various applications of fractional-order systems. - Presents a simple and comprehensive understanding of the field of fractional-order systems - Offers practical knowledge on the design of fractional-order systems for different applications - Exposes users to possible new applications for fractional-order systems