Recent advancements in Lyapunov-based design and analysis techniques have applications to a broad class of engineering systems, including mechanical, electrical, robotic, aerospace, and underactuated systems. This book provides a practical yet rigorous development of nonlinear, Lyapunov-based tools and their use in the solution of control-theoretic problems. Rich in motivating examples and new design techniques, the text balances theoretical foundations and real-world implementation. Features include: * Control designs for a broad class of engineering systems * Presentation of adaptive and learning control methods for uncertain nonlinear systems * Experimental testbed descriptions and results that guide the reader toward techniques for further research * Development of necessary mathematical background in each chapter; additional mathematical prerequisites contained in two appendices Intended for readers who have some knowledge of undergraduate systems theory, the book includes a wide range of applications making it suitable for an extensive audience. Graduate students and researchers in control systems, robotics, and applied mathematics, as well as professional engineers will appreciate the work's combination of theoretical underpinnings and current and emerging engineering applications.

Control designs for a broad class of engineering systems Presentation of adaptive and learning control methods for uncertain nonlinear systems Experimental testbed descriptions and results that guide the reader toward techniques for further research Development of necessary mathematical background in each chapter; additional mathematical prerequisites contained in two appendices

Inhalt
1 Introduction.- 1.1 Pitfalls of Linear Control.- 1.2 Lyapunov-Based Control.- 1.3 Summary.- References.- 2 Mechanical Systems.- 2.1 Introduction.- 2.2 Autobalancing Systems.- 2.3 Dynamically Positioned Ships.- 2.4 Euler-Lagrange Systems.- 2.5 Background and Further Reading.- References.- 3 Electric Machines.- 3.1 Introduction.- 3.2 Induction Motor.- 3.3 Switched Reluctance Motor.- 3.4 Active Magnetic Bearings.- 3.5 Background and Further Reading.- References.- 4 Robotic Systems.- 4.1 Introduction.- 4.2 Learning Control Applications.- 4.3 Position and Force Control Applications.- 4.4 Visual Servo Control Application.- 4.5 Background and Further Reading.- References.- 5 Aerospace Systems.- 5.1 Introduction.- 5.2 Attitude Tracking.- 5.3 Energy/Power and Attitude Tracking.- 5.4 Formation Flying.- 5.5 Background and Further Reading.- References.- 6 Underactuated Systems.- 6.1 Introduction.- 6.2 Overhead Crane Systems.- 6.3 VTOL Systems.- 6.4 Satellite Systems.- 6.5 Background and Further Reading.- References.- Appendices.- A Mathematical Background.- References.- B Supplementary Lemmas and Definitions.- B.1 Chapter 2 Lemmas.- B.l.1 Convolution Operations for Torque Filtering.- B.1.2 Control Signal Bound.- B.1.3 Control Signal Bound.- B.1.4 Control Signal Bound.- B.1.5 Inequality Proofs.- B.1.6 Control Signal Bounds.- B.1.7 Matrix Property.- B.2 Chapter 3 Definitions and Lemmas.- B.2.1 Supplemental Definitions.- B.2.2 Stability Analysis for Projection Cases.- B.2.3 Dynamic Terms for a 6-DOF AMB System.- B.2.4 Partial Derivative Definitions.- B.3 Chapter 4 Lemmas.- B.3.1 Inequality Lemma.- B.3.2 Stability Analysis for Projection Cases.- B.3.3 Boundedness Lemma.- B.3.4 State-Dependent Disturbance Bound.- B.3.5 Matrix Property.- B.4 Chapter 5 Lemmas.- B.4.1 Skew-Symmetry Property.- B.4.2 Control Signal Bound.- B.5 Chapter 6 Definitions and Lemmas.- B.5.1 Definitions for Dynamic Terms.- B.5.2 Linear Control Law Analysis.- B.5.3 Coupling Control Law Analysis.- B.5.4 Matrix Property.- References.