Intelligent ship autopilots––A historical perspective

Roberts, G.N.; Sutton, Robert I.; Zirilli, A.; Tiano, A.

doi:10.1016/s0957-4158(03)00044-8

Cited by 41 publications

(20 citation statements)

References 18 publications

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“…The classical PID control is often preferred for motion control of ROVs, and likewise for industrial applications in general (Smallwood & Whitcomb, 2004;Roberts, Sutton, Zirilli, & Tiano, 2003;Hsu, Costa, Lizarralde, & da Cunha, 2000), despite the availability of several other control techniques. Although the PID control has its limitations to cope with highly coupled multivariable nonlinear and time-varying dynamics, it is often preferred due to its synthesis and implementation simplicity, apart from being fully understood and having been extensively and successfully tested in practice for almost one century since it was introduced (Åström & Hägglund, 2011;Franklin, Powell, & Emami-Naeini, 2009;Roberts et al, 2003;Friedland, 1986).…”

Section: Introductionmentioning

confidence: 98%

“…Although the PID control has its limitations to cope with highly coupled multivariable nonlinear and time-varying dynamics, it is often preferred due to its synthesis and implementation simplicity, apart from being fully understood and having been extensively and successfully tested in practice for almost one century since it was introduced (Åström & Hägglund, 2011;Franklin, Powell, & Emami-Naeini, 2009;Roberts et al, 2003;Friedland, 1986). The performance limitations can be sought to be circumvented by combining other techniques with the basic PID algorithm, whereupon satisfactory PID-based controllers can be obtained.…”

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

Output feedback motion control system for observation class ROVs based on a high-gain state observer: Theoretical and experimental results

Fernandes

Sørensen

Pettersen

et al. 2015

Control Engineering Practice

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

Output feedback motion control system for observation class ROVs based on a high-gain state observer: Theoretical and experimental results

Fernandes

Sørensen

Pettersen

et al. 2015

Control Engineering Practice

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“…With their strong autonomy and adaptability, unmanned ships have gradually become the new research direction pursued by the current industry [3]. Unmanned ships can not only perform tasks independently in dangerous sea areas, but also cooperate with manned ships to improve work efficiency.…”

Section: Introductionmentioning

confidence: 99%

An Autonomous Path Planning Model for Unmanned Ships Based on Deep Reinforcement Learning

Guo

Zhang

Zheng

et al. 2020

Sensors

153

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Deep reinforcement learning (DRL) has excellent performance in continuous control problems and it is widely used in path planning and other fields. An autonomous path planning model based on DRL is proposed to realize the intelligent path planning of unmanned ships in the unknown environment. The model utilizes the deep deterministic policy gradient (DDPG) algorithm, through the continuous interaction with the environment and the use of historical experience data; the agent learns the optimal action strategy in a simulation environment. The navigation rules and the ship’s encounter situation are transformed into a navigation restricted area, so as to achieve the purpose of planned path safety in order to ensure the validity and accuracy of the model. Ship data provided by ship automatic identification system (AIS) are used to train this path planning model. Subsequently, the improved DRL is obtained by combining DDPG with the artificial potential field. Finally, the path planning model is integrated into the electronic chart platform for experiments. Through the establishment of comparative experiments, the results show that the improved model can achieve autonomous path planning, and it has good convergence speed and stability.

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“…This requires that the controllers are able to act in real-time, while continuing the execution of the assigned tasks. To achieve this goal, modern ship Mechatronics behaviour-based systems make use of an effective approach to robotic and autonomous agent con-trol due to its modularity and robust real-time properties (Roberts et al 2003). -The third challenge is the realism of the behaviour of the autonomous ship.…”

Section: Introductionmentioning

confidence: 99%

Research on Ship Autonomous Steering Control for Short-Sea Shipping Problems

Jakovlev¹,

Andziulis

Daranda

et al. 2017

Transport

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Today most ship rotation angle (steering control during movement) increase or decrease is done using an operator on deck or the auxiliary system in the ships engine room. Formal regulations suggest using manual inspection of the ship rotation and the work effectiveness of the engine during manoeuvring in ports and in the open sea regions. The accuracy of this procedure is very low and depends on the personnel of the deck. Therefore, automation and computer control systems are constantly required to assist the human eye. This problem becomes clearly visible when dealing with full ship autonomy in the open sea in the short-sea shipping regions. The trend of maritime technology development will only increase in the area of human interaction decrease with the physical operations and the shipping procedures, which will lead to the future full ship autonomy in the open sea regions around the globe. With the growing automation technologies, predictive control can prove to be a better approach than the traditionally applied visual inspection policy and linear control models. Ship full autonomy is also linked to the ship's machinery regular repair and maintenance that has to be carried out for delivering satisfactory performance and minimizing downtime during transportation operations. In this paper, current stages of development of the intelligent transportation system concept are discussed for the ship autonomy in manoeuvring control and a robust ships' systems integration and communication system concept is presented for several normal and abnormal situations: high-traffic, potentially dangerous situations or port approaching or ship maintenance, with the capability to solve problems with the limited human interface and with a remote control possibility. Then, simplified ship steering motor system for the main pump is analysed for rotation control using control voltage from the converters. Retrieved data from a small experimental control motor is used for the predictive control approach using two different methods: a neural network trained with Basic Levenberg-Marquardt Method and a Linear Model.

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Intelligent ship autopilots––A historical perspective

Cited by 41 publications

References 18 publications

Output feedback motion control system for observation class ROVs based on a high-gain state observer: Theoretical and experimental results

Output feedback motion control system for observation class ROVs based on a high-gain state observer: Theoretical and experimental results

An Autonomous Path Planning Model for Unmanned Ships Based on Deep Reinforcement Learning

Research on Ship Autonomous Steering Control for Short-Sea Shipping Problems

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