This book provides a comprehensive and practical framework for model-based control of MKC (mass-stiffness-damping or mass-spring-damper) systems, emphasizing seamless integration of theory and application. It explores the intricacies of modeling and control strategies tailored to the complexities of MKC systems, prevalent in various industrial applications. Clear explanations and real-world examples equip readers with advanced techniques for enhancing system performance, robustness, and adaptability in the face of nonlinearities and uncertainties.

Key topics include:

• fundamentals of MKC system modeling;
• strategies for feedback linearization and dynamic decoupling; and
• robust control techniques essential for managing real-world systems.

This book is an important resource for anyone dealing with multivariable systems, introducing innovative approaches to disturbance and uncertainty reduction, and decentralized adaptive pole placement. It addresses the need for robust and adaptable control strategies that can handle the inherent complexities and uncertainties of MKC systems, often encountered in industries like robotics, automotive engineering, and aerospace. Collectively, these topics help engineers and researchers deal with common challenges in designing controllers for systems with complex dynamics and interactions.

Model-Based Control of Mass-Stiffness-Damping Systems is valuable for control engineers, researchers, and postgraduate students looking to enhance their understanding and practical familiarity with advanced control methods. Offering a generally applicable and expandable control framework, this book enables immediate practical improvements in existing control schemes and a solid foundation for further exploration and innovation in the control of complex dynamic systems.

This book provides a comprehensive and practical framework for model-based control of MKC (mass-stiffness-damping or mass-spring-damper) systems, emphasizing seamless integration of theory and application. It explores the intricacies of modeling and control strategies tailored to the complexities of MKC systems, prevalent in various industrial applications. Clear explanations and real-world examples equip readers with advanced techniques for enhancing system performance, robustness, and adaptability in the face of nonlinearities and uncertainties.

Key topics include:

fundamentals of MKC system modeling; strategies for feedback linearization and dynamic decoupling; and robust control techniques essential for managing real-world systems.

This book is an important resource for anyone dealing with multivariable systems, introducing innovative approaches to disturbance and uncertainty reduction, and decentralized adaptive pole placement. It addresses the need for robust and adaptable control strategies that can handle the inherent complexities and uncertainties of MKC systems, often encountered in industries like robotics, automotive engineering, and aerospace. Collectively, these topics help engineers and researchers deal with common challenges in designing controllers for systems with complex dynamics and interactions.

Model-Based Control of Mass-Stiffness-Damping Systems is valuable for control engineers, researchers, and postgraduate students looking to enhance their understanding and practical familiarity with advanced control methods. Offering a generally applicable and expandable control framework, this book enables immediate practical improvements in existing control schemes and a solid foundation for further exploration and innovation in the control of complex dynamic systems.