Adaptive and Learning-Based Control of Safety-Critical Systems

Häftad, Engelska, 2024

AvMax Cohen,Calin Belta

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This book stems from the growing use of learning-based techniques, such as reinforcement learning and adaptive control, in the control of autonomous and safety-critical systems. This book contains recent results on provably correct control techniques from specifications that go beyond safety and stability, such as temporal logic formulas.

Produktinformation

Utgivningsdatum2024-06-03
Mått168 x 240 x 12 mm
Vikt371 g
FormatHäftad
SpråkEngelska
SerieSynthesis Lectures on Computer Science
Antal sidor194
FörlagSpringer International Publishing AG
ISBN9783031293122

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Max Cohen is a Ph.D. Candidate and National Science Foundation Graduate Research Fellow in the Department of Mechanical Engineering at Boston University. He received his B.S. in Mechanical Engineering from the University of Florida and his M.S. in Mechanical Engineering from Boston University. Outside of academia he has worked as a Systems Engineer at Lockheed Martin and held research internships at MIT Lincoln Laboratory. His research interests include nonlinear control theory, learning-based control, and hybrid systems, with applications in robotics and autonomous systems.Calin Belta, Ph.D, is a Professor in the Department of Mechanical Engineering at Boston University, where he holds the Tegan family Distinguished Faculty Fellowship. He is also the Director of the BU Robotics Lab. He received B.Sc. and M.Sc. degrees from the Technical University of Iasi and M.Sc. and Ph.D. degrees from the University of Pennsylvania. His research interests include dynamics and control theory, with particular emphasis on hybrid and cyber-physical systems, formal synthesis and verification, and applications in robotics and systems biology. He has received the Air Force Office of Scientific Research Young Investigator Award and the National Science Foundation CAREER Award. He is a Fellow and Distinguished Lecturer of IEEE.

Introduction.- Lyapunov-based Control Design.- Safety-Critical Control.- Adaptive Control Lyapunov Functions.- Adaptive Safety-Critical Control.- Modular Adaptive Safety-Critical Control.- Robust Safety-Critical Control for Systems with Actuation Uncertainty.- Safe Exploration in Model-Based Reinforcement Learning.- Temporal Logic Guided Safe Model-Based Reinforcement Learning.- Conclusion.