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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.

The design of nonlinear controllers for mechanical systems has been an ex­ tremely active area of research in the last two decades. From a theoretical point of view, this attention can be attributed to their interesting dynamic behavior, which makes them suitable benchmarks for nonlinear control the­ oreticians. On the other hand, recent technological advances have produced many real-world engineering applications that require the automatic con­ trol of mechanical systems. the mechanism for de­ Often, Lyapunov-based techniques are utilized as veloping different nonlinear control structures for mechanical systems. The allure of the Lyapunov-based framework for mechanical system control de­ sign can most likely be assigned to the fact that Lyapunov function candi­ dates can often be crafted from physical insight into the mechanics of the system. That is, despite the nonlinearities, couplings, and/or the flexible effects associated with the system, Lyapunov-based techniques can often be used to analyze the stability of the closed-loop system by using an energy­ like function as the Lyapunov function candidate. In practice, the design procedure often tends to be an iterative process that results in the death of many trees. That is, the controller and energy-like function are often constructed in concert to foster an advantageous stability property and/or robustness property. Fortunately, over the last 15 years, many system the­ ory and control researchers have labored in this area to produce various design tools that can be applied in a variety of situations.