Isah A. Jimoh Jimoh Robust Model Predictive Control for Autonomous Underwater Vehicles

Robust Model Predictive Control for Autonomous Underwater Vehicles

von Isah A. Jimoh

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Beschreibung

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® 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.


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® 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.


Comprehensive up-to-date survey of predictive motion control algorithms for AUVs, addressing real-world challenges Step-by-step guide to adopting advanced control methods to achieve robust motion control of AUVs in taxing environments Downloadable MATLAB® simulations make it easier to understand, replicate and improve the design solutions proposed

Autor*in

Isah A. Jimoh

Themen in »Robust Model Predictive Control for Autonomous Underwater Vehicles«

Model Predictive Control MPC Autonomous Underwater Vehicles Autonomous Marine Vehicles Unmanned Underwater Vehicles Robust Optimal Control Motion Control Trajectory Tracking Path-following Dynamic Positioning

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Details

ISBN: 9783032168443
Verlag: Springer International Publishing
Erscheinung: 04.08.2026

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