Robust Model Predictive Control for Autonomous Underwater Vehicles
暫譯: 自主水下航行器的穩健模型預測控制

This book offers a comprehensive and practical guide to the design of advanced model predictive control (MPC) strategies for the three-dimensional motion control of autonomous underwater vehicles (AUVs). It addresses the full six-degrees-of-freedom dynamics of AUVs using convex optimization-based MPC techniques, making the resulting control problems computationally tractable.

The book adopts a structured two-stage approach. The first stage provides a self-contained tutorial on advanced MPC design for uncertain systems, including strategies to ensure closed-loop stability. This equips students, academic researchers and engineers with the theoretical and practical foundations needed to understand and apply advanced MPC to complex systems. The second stage applies these methods to the real-world challenge of three-dimensional AUV motion control, offering novel control formulations that outperform conventional methods.

Throughout the book, special attention is given to robustness, constraint handling and optimization structure. Through detailed case studies and extensive simulations, including downloadable MATLAB(R) implementations in many cases, the book validates the proposed strategies against conventional methods using quantitative performance metrics to demonstrate improved control accuracy, robustness and efficiency. This makes Robust Model Predictive Control for Autonomous Underwater Vehicles a valuable resource not only for researchers and postgraduate students, but also for practicing engineers working on marine robotics and model-based control system design.