Real-time model predictive line following control for underactuated marine vehicles

Kapetanović, Nadir; Bibuli, Marco; Mišković, Nikola; Caccia, Massimo

doi:10.1016/j.ifacol.2017.08.2501

Cited by 13 publications

(5 citation statements)

References 9 publications

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“…Further, a multi-objective MPC method is proposed for the AUV considering the flexibility of adjusting the vehicle's velocity. On the other hand, MPC has been adopted for the fully-actuated marine vehicles [75,131] and underactuated marine vehicles [48,72,107,112,176]. The robust MPC is employed to solve the path following problem of the AMV with disturbances in [176].…”

Section: Dynamic Positioning and Path Followingmentioning

confidence: 99%

Self-Triggered Min–Max DMPC for Asynchronous Multiagent Systems With Communication Delays

Wei

Zhang

Shi

2022

IEEE Trans. Ind. Inf.

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Distributed coordination of multi-agent systems (MASs) has been widely studied in various emerging engineering applications, including connected vehicles, wireless networks, smart grids, and cyber-physical systems. In these contexts, agents make the decision locally, relying on the interaction with their immediate neighbors over the connected communication networks. The study of distributed coordination for the multi-agent system (MAS) with constraints is significant yet challenging, especially in terms of ubiquitous uncertainties, the heavy communication burden, and communication delays, to name a few. Hence, it is desirable to develop distributed algorithms for the constrained MAS with these practical issues. In this dissertation, we develop the theoretical results on robust distributed model predictive control (DMPC) algorithms for two types of control problems (i.e., formation stabilization problem and consensus problem) of the constrained and uncertain MAS and apply robust DMPC algorithms in applications of cooperative marine vehicles.More precisely, Chapter 1 provides a systematic literature review, where the state-of-the-art DMPC for formation stabilization and consensus, robust MPC, and MPC for motion control of marine vehicles are introduced. Chapter 2 introduces some notations, necessary definitions, and some preliminaries. In Chapter 3, we study the formation stabilization problem of the nonlinear constrained MAS with uncertainties and bounded time-varying communication delays. We develop a min-max DMPC algorithm with the self-triggered mechanism, which significantly reduces the communication burden while ensuring closed-loop stability and robustness. Chapter 4 investigates the consensus problem of the general linear MAS with input constraints and bounded time-varying delays. We design a robust DMPC-based consensus protocol that integrates a predesigned consensus protocol with online DMPC optimization techniques. Under mild technical assumptions, the estimation errors propagated over prediction due to delay-induced inaccurate neighboring information are proved bounded, based on which a robust DMPC strategy is deliberately designed to achieve robust consensus while satisfying control input constraints. Chapter 5 proposes a Lyapunov-based DMPC approach for the formation tracking control problem of cooperative autonomous underwater vehicles (AUVs) subject to environmental disturbances. A stability constraint leveraging the extended state observer-based auxiliary control law and the associated Lyapunov function is incorporated into the optimization problem to enforce the stability and enhance formation tracking performance. A iv collision-avoidance cost is designed and employed in the DMPC optimization problem to further guarantee the safety of AUVs. Chapter 6 presents a tube-based DMPC approach for the platoon control problem of a group of heterogeneous autonomous surface vehicles (ASVs) with input constraints and disturbances. In particular, a coupled inter-vehicle safety constraint is added to the DMPC ...

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Section: Dynamic Positioning and Path Followingmentioning

confidence: 99%

Self-Triggered Min–Max DMPC for Asynchronous Multiagent Systems With Communication Delays

Wei

Zhang

Shi

2022

IEEE Trans. Ind. Inf.

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“…For the path-following, the basic algorithms used by researchers include PID [93], fuzzy logic control [94], predictive control [95], sliding mode control [96], ADRC [97] and AI algorithm [98], etc. The basic algorithms can be combined, such as the combination of fuzzy control and PID algorithm [93], the combination of prediction algorithm and PID algorithm [99], the combination of sliding mode and backstepping control [96], etc. In recent years, the application of AI algorithms in path-following has been increasing.…”

Section: Path-following Controlmentioning

confidence: 99%

“…The high-level motion control is a linear MPC (LMPC) controller, which optimizes the reference yaw rate. The low-level control is PID control, which realizes the surge speed reference tracking [99].…”

Section: Model Prediction Control Algorithmmentioning

confidence: 99%

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Wang

Liu

et al. 2019

JMSE

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At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.

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“…Li and Sun [12] proposed a new disturbance-compensated MPC algorithm for ship heading control. Kapetanović et al [13] proposed applied linear model predictive control (LMPC) for the trajectory tracking of underactuated ships under disturbance and input constraint saturation. Furthermore, since ship dynamics is highly nonlinear, in order to improve the control performance, it stimulates the development of nonlinear model predictive control (NMPC) [14].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Weight Optimization of a Nonlinear Model Predictive Controller Using a Genetic Algorithm for Ship Trajectory Tracking

Deng

Wang

et al. 2022

JMSE

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This paper presents a weight optimization method for a nonlinear model predictive controller (NMPC) based on the genetic algorithm (GA) for ship trajectory tracking. The weight coefficients Q and R of the objective function in NMPC are obtained via the real-time optimization of the genetic algorithm instead of the trial and error method, which improves the efficiency and accuracy of the controller. In addition, targeted improvements are made to the internal crossover operator, mutation operator, crossover rate, and mutation rate of the genetic algorithm. The simulation comparison of trajectory tracking between NMPC with real-time-optimized weight coefficients and the one with constant coefficients is performed. Finally, the simulation result shows that the controller with real-time-optimized weight coefficients has a better trajectory tracking effect than that with constant weight coefficients.

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Real-time model predictive line following control for underactuated marine vehicles

Cited by 13 publications

References 9 publications

Self-Triggered Min–Max DMPC for Asynchronous Multiagent Systems With Communication Delays

Self-Triggered Min–Max DMPC for Asynchronous Multiagent Systems With Communication Delays

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Real-Time Weight Optimization of a Nonlinear Model Predictive Controller Using a Genetic Algorithm for Ship Trajectory Tracking

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