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Provides the reader with an accessible primer on a new direction in control theory still in its infancy, namely Learning-Based Control Theory, that is closely tied to the literature of safe Reinforcement Learning and Adaptive Dynamic Programming.
This book presents a study on the novel concept of "event-triggered control of nonlinear systems subject to disturbances", discussing the theory and practical applications.
The subject of nonlinear control systems analysis has grown rapidly and this book provides a simple presentation of their stability and feedback stabilization. It enables the reader to learn and understand major techniques used in mathematical control theory.
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