High-rise fire-fighting unmanned aerial vehicle formation optimization control method and system with disturbance compensation

It is a technology of optimization control and disturbance compensation, which is applied in control/regulation system, non-electric variable control, vehicle position/route/height control, etc. It can solve problems such as complex building structure and heavy rescue tasks, so as to improve control accuracy and have Practical value, simple effect of weight update method

Pending Publication Date: 2021-04-13
GUANGDONG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, high-rise buildings often have complex structures and heavy rescue tasks, and a drone alone cannot meet the needs of actual tasks.

Method used

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  • High-rise fire-fighting unmanned aerial vehicle formation optimization control method and system with disturbance compensation
  • High-rise fire-fighting unmanned aerial vehicle formation optimization control method and system with disturbance compensation
  • High-rise fire-fighting unmanned aerial vehicle formation optimization control method and system with disturbance compensation

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Embodiment 1

[0032] In recent years, when solving the UAV swarm formation control, people always expect to design the optimal cooperative control law to minimize the performance index while the UAV swarm realizes the formation formation. From a physical point of view, optimal cooperative control considers how to make each UAV reach the formation state with the least amount of energy. From a mathematical point of view, the optimal control problem is finally transformed into solving the Hamilton-Jacobi-Bellman equation, which is a sufficient condition for the existence of an optimal solution. However, for a nonlinear system like a UAV, the Hamilton-Jacobi-Bellman equation is actually a nonlinear partial differential equation, which is generally difficult to solve mathematically. Reinforcement learning methods provide an efficient way to solve such nonlinear partial differential equations.

[0033] In a complex fire scene environment, the external disturbances suffered by UAVs will be more s...

Embodiment 2

[0129] In this embodiment, a high-level fire-fighting UAV formation optimization control system with disturbance compensation is disclosed, including:

[0130] A data collection module, used to collect the operating status information of the UAV formation;

[0131] The cooperative control strategy generation module is used to input the collected running state information of the UAV formation into the UAV formation optimization control model to obtain the UAV formation coordination control strategy, wherein the UAV formation optimization control model includes The distributed Hamilton-Jacobi-Bellman equation and the disturbance observer model under disturbance, the distributed Hamilton-Jacobi-Bellman equation under no disturbance aim at the minimum performance index, and obtain the maximum value under no disturbance. The optimal cooperative control strategy, the external disturbance is estimated by the disturbance observer model, and the cooperative control strategy of the UAV ...

Embodiment 3

[0133] In this embodiment, an electronic device is disclosed, including a memory, a processor, and computer instructions stored in the memory and run on the processor. The steps described in the method for optimal control of high-level fire-fighting UAV formation with disturbance compensation.

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Abstract

The invention discloses a high-rise fire-fighting unmanned aerial vehicle formation optimization control method and system with disturbance compensation. The method comprises the steps of collecting operation state information of an unmanned aerial vehicle formation; and inputting the collected operation state information of the unmanned aerial vehicle formation into an unmanned aerial vehicle formation optimization control model to obtain a cooperative control strategy of the unmanned aerial vehicle formation, wherein the unmanned aerial vehicle formation optimization control model comprises a distributed Hamilton-Jacobi-Bellman equation without disturbance and a disturbance observer model, the distributed Hamilton-Jacobi-Bellman equation without disturbance takes the minimum performance index as a target to obtain the optimal cooperative control strategy under the disturbance-free condition through solving, external disturbance is estimated through the disturbance observer model, and through the optimal cooperative control strategy under the disturbance-free condition and the estimated external disturbance, the cooperative control strategy of the unmanned aerial vehicle formation is obtained. According to the invention, the performance index is minimized while the formation pattern of the unmanned aerial vehicle formation is kept.

Description

technical field [0001] The invention relates to the field of artificial intelligence and control technology, in particular to a method and system for optimizing the formation of high-level fire-fighting drones with disturbance compensation. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] As the scale of urban construction continues to expand, people are paying more and more attention to how to extinguish fires in high-rise buildings and escape personnel in complex and changeable fire conditions. The use of drones for on-site fire investigation and personnel escape guidance has become an effective means. However, high-rise buildings often have complex structures and heavy rescue tasks, and a drone alone cannot meet the needs of actual tasks. Compared with a single drone, the drone cluster has the characteristics of cooperative control an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/10
CPCG05D1/104Y02T10/40
Inventor 李鸿一郭子杰鲁仁全周琪刘洋
Owner GUANGDONG UNIV OF TECH
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