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Advanced Model Predictive Control for Autonomous Marine Vehicles

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This book provides a comprehensive overview of marine control system design related to underwater robotics applications. In particular, it presents novel optimization-based model predictive control strategies to solve control problems appearing in autonomous underwater vehicle applications. These novel approaches bring unique features, such as constraint handling, prioritization between multiple design objectives, optimal control performance, and robustness against disturbances and uncertainties, into the control system design. They therefore form a more general framework to design marine control systems and can be widely applied.

Advanced Model Predictive Control for Autonomous Marine Vehicles balances theoretical rigor – providing thorough analysis and developing provably-correct design conditions – and application perspectives – addressing practical system constraints and implementation issues. Starting with a fixed-point positioning problem for a single vehicle and progressing to the trajectory-tracking and path-following problem of the vehicle, and then to the coordination control of a large-scale multi-robot team, this book addresses the motion control problems, increasing their level of challenge step-by-step. At each step, related subproblems such as path planning, thrust allocation, collision avoidance, and time constraints for real-time implementation are also discussed with solutions.

In each chapter of this book, compact and illustrative examples are provided to demonstrate the design and implementation procedures. As a result, this book is useful for both theoretical study and practical engineering design, and the tools provided in the book are readily applicable for real-world implementation.

Author(s): Yang Shi, Chao Shen, Henglai Wei, Kunwu Zhang
Series: Advances in Industrial Control
Publisher: Springer
Year: 2023

Language: English
Pages: 209
City: Cham

Series Editor’s Foreword
Preface
Acknowledgements
Contents
Abbreviations
1 Introduction
1.1 Autonomous Marine Vehicles
1.1.1 Overview
1.1.2 The Motion Control Problems
1.2 Model Predictive Control
1.2.1 The Receding Horizon Control Strategy
1.2.2 Stability of MPC
1.2.3 MPC for the Motion Control of AMVs
1.3 Motivations of the Book
1.4 Outline of the Book
1.5 Notes and Summary
References
2 AMV Modeling
2.1 Kinematics of AMVs
2.1.1 Reference Frames
2.1.2 Transformation Between Reference Frames
2.2 Nonlinear Dynamics of AMVs
2.2.1 Rigid-Body Dynamics
2.2.2 Hydrodynamic Forces and Moments
2.3 AMV Model for Motion Control Design
2.4 Notes and Summary
References
3 Receding Horizon Optimization for Integrated Path Planning and Tracking Control of an AUV
3.1 Introduction
3.1.1 Research Background and Contributions
3.1.2 Chapter Organization
3.2 Problem Statement
3.3 Minimum Curvature Receding Horizon Path Planning
3.4 Nonlinear Model Predictive Tracking Control
3.5 Integrated Receding Horizon Path Planning and Tracking Control: Algorithm Description
3.6 Simulation Study
3.6.1 Parameter Selection
3.6.2 Tracking Performance
3.7 Notes and Summary
References
4 Lyapunov-Based Model Predictive Control for Dynamic Positioning and Trajectory-Tracking Control of an AUV
4.1 Introduction
4.1.1 Research Background and Contributions
4.1.2 Chapter Organization
4.2 LMPC Design for Dynamic Positioning Control
4.2.1 Problem Formulation
4.2.2 Main Results
4.2.3 Simulation Study
4.3 LMPC Design for Trajectory-Tracking Control
4.3.1 Problem Formulation
4.3.2 Main Results
4.3.3 Simulation Study
4.4 Notes and Summary
References
5 Multi-objective Model Predictive Control for Path-Following Control of an AUV
5.1 Introduction
5.1.1 Research Background and Contributions
5.1.2 Chapter Organization
5.2 Problem Formulation
5.2.1 The Path-Following Problem
5.2.2 Zero-Path-Error Manifold
5.2.3 The MOMPC Formulation
5.3 Solve the MOMPC Problem
5.3.1 Weighted-Sum Method
5.3.2 Lexicographic Ordering Method
5.4 Convergence Analysis
5.5 Simulation Study
5.5.1 PF Control Using WS-MOMPC
5.5.2 PF Control Using LO-MOMPC
5.5.3 Robustness Test
5.6 Notes and Summary
References
6 Distributed Lyapunov-Based Model Predictive Formation-Tracking Control for AUVs Subject to Disturbances
6.1 Introduction
6.1.1 Research Background and Contributions
6.1.2 Chapter Organization
6.2 Problem Statement and Preliminaries
6.2.1 AUV Modeling
6.2.2 Problem Formulation
6.3 Distributed Lyapunov-Based Model Predictive Formation-Tracking Control
6.3.1 Design of the Auxiliary Control Law
6.3.2 Design of the Optimization Problem
6.3.3 Feasibility and Stability Analysis
6.4 Simulation Study
6.4.1 Simulation Setup
6.4.2 Formation Tracking with Collision Avoidance
6.4.3 Multi-AUV Formation Tracking with Disturbances
6.5 Notes and Summary
References
7 Robust Distributed Model Predictive Platooning Control for Heterogeneous Autonomous Surface Vehicles
7.1 Introduction
7.1.1 Research Background and Contributions
7.1.2 Chapter Organization
7.2 Problem Setup
7.2.1 Autonomous Surface Vehicle Modeling
7.2.2 ASV Platoon Modeling
7.2.3 Control Objectives
7.3 Robust Distributed Model Predictive Platooning Control
7.3.1 DMPC Optimization Problem
7.3.2 The Auxiliary Controller
7.4 Theoretical Analysis
7.5 Simulation Study
7.6 Notes and Summary
References
8 Efficient Implementation Algorithms for NMPC-Based AUV Trajectory-Tracking Control
8.1 Introduction
8.1.1 Research Background and Contributions
8.1.2 Chapter Organization
8.2 Modified C/GMRES Algorithm
8.2.1 Problem Formulation
8.2.2 Solving the NMPC Problem
8.2.3 Modified C/GMRES Algorithm
8.2.4 Simulation Study
8.3 Distributed Implementation Strategy
8.3.1 Problem Formulation
8.3.2 Solving the NMPC Problem
8.3.3 Distributed NMPC Implementation
8.3.4 Simulation Study
8.3.5 Robustness Test
8.4 Notes and Summary
References
9 Concluding Remarks
9.1 Summary of the Book
9.2 Future Missions
9.2.1 Some Fundamental Questions
9.2.2 Some Tractable AMV Research Directions
References
Appendix A
A.1 Forward Difference Generalized Minimal Residual Method
A.2 Derivation of Jacobians
A.3 Introduction to MPC Simulations
A.3.1 Illustration of the Software Implementation
A.3.1.1 Creating a Controlled AUV System
A.3.1.2 Creating an MPC Controller
A.3.1.3 Creating a Planner Object
Index