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Unmanned vessel data driving reinforcement learning control method with specified performance

A reinforcement learning and data-driven technology, applied in the field of trajectory tracking, can solve problems such as tracking errors cannot be guaranteed, and achieve the effects of accelerating convergence speed, improving adaptability and reliability

Active Publication Date: 2020-06-19
DALIAN MARITIME UNIVERSITY
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Problems solved by technology

In the actual operation process, the tracking error of the unmanned ship needs to be within a certain range, but although the existing technology can realize the tracking control of the unmanned ship, the tracking error cannot be guaranteed to be within the required range

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  • Unmanned vessel data driving reinforcement learning control method with specified performance
  • Unmanned vessel data driving reinforcement learning control method with specified performance
  • Unmanned vessel data driving reinforcement learning control method with specified performance

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[0088] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0089] It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate ...

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Abstract

The invention provides an unmanned vessel data driving reinforcement learning control method with specified performance for an unmanned surface vessel system. The method comprises the steps of S1, building an unmanned surface vessel mathematic model, S2, introducing a specified performance function, S3, designing an optimal controller of the unmanned vessel, and S4, designing weight updating ratesof the evaluator and the actuator. According to the method, simultaneous updating of the actuator and the evaluator can be realized, and the error can be within a specified range, so that the optimalcontrol strategy is obtained. Meanwhile, the method accelerates the convergence speed of the control system, and obviously improves the adaptability and reliability of the operation of the unmanned vessel system in an unknown environment.

Description

technical field [0001] The invention relates to the technical field of reinforcement learning and trajectory tracking of surface unmanned ships, in particular, to a data-driven reinforcement learning control method for unmanned ships with specified performance. Background technique [0002] Nowadays, artificial intelligence technology has been widely used in the field of control, especially in unmanned ship systems. Compared with traditional ships, unmanned ships can well deal with complex and changeable marine environments and reduce the impact of human factors and uncertain disturbances. Reinforcement learning is an efficient solution to the optimal control problem. It can solve the shortcoming that it is not easy to solve the Hamilton-Jacobi-Bellman equation in the traditional optimal control problem. Werbos proposed an optimal control framework based on reinforcement learning and using actor-critic neural networks. By using actor-critic neural network, the cost functi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042Y02T90/00
Inventor 王宁李堃高颖杨忱
Owner DALIAN MARITIME UNIVERSITY
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