Distributed implementation of nonlinear model predictive control for AUV trajectory tracking

DOI10.1016/j.automatica.2020.108863zbMath1436.93094OpenAlexW3006129553MaRDI QIDQ2307547

Chao Shen, Yang Shi

Publication date: 24 March 2020

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2020.108863

zbMATH Keywords

nonlinear controldistributed controltrajectory trackingmodel predictive controlreal-time controlautonomous underwater vehicle

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Automated systems (robots, etc.) in control theory (93C85) Model predictive control (93B45)

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Stabilizing terminal constraint-free nonlinear MPC via sliding mode-based terminal cost ⋮ PSO-based nonlinear model predictive planning and discrete-time sliding tracking control for uncertain planar underactuated manipulators ⋮ Adaptive interval type-2 fuzzy control for multi-legged underwater robot with input saturation and full-state constraints ⋮ A multi-rate hierarchical fault-tolerant adaptive model predictive control framework: theory and design for quadrotors ⋮ High-order fully actuated system approaches: model predictive control with applications to under-actuated systems ⋮ Improved SSA‐RBF neural network‐based dynamic 3‐D trajectory tracking model predictive control of autonomous underwater vehicles with external disturbances ⋮ Finite-time covert attacks on reference tracking systems with unknown-but-bounded noises ⋮ Event-triggered attitude synchronization of multiple rigid-body systems ⋮ Distributed event-triggered control for multi-agent systems under intermittently random denial-of-service attacks ⋮ Distributed model predictive control for nonlinear large-scale systems based on reduced-order cooperative optimisation

Cites Work

• Event-triggered robust model predictive control of continuous-time nonlinear systems
• A global output-feedback controller for stabilization and tracking of underactuated ODIN: A spherical underwater vehicle.
• SQP-methods for solving optimal control problems with control and state constraints: Adjoint variables, sensitivity analysis and real-time control
• Model predictive control: recent developments and future promise
• Computational Complexity Certification for Real-Time MPC With Input Constraints Based on the Fast Gradient Method

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