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Intention priority fuzzy fusion control method for brain-controlled vehicle

A control method and a technology of fuzzy fusion, applied in the control field of brain-controlled vehicles, can solve the problems of modeling and complexity, and achieve the effect of improving the degree of participation, improving the control performance, and ensuring the control accuracy.

Pending Publication Date: 2020-11-27
TIANJIN UNIV
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Problems solved by technology

However, the brain's decision-making process is itself a complex process, making it difficult to model accurately

Method used

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  • Intention priority fuzzy fusion control method for brain-controlled vehicle
  • Intention priority fuzzy fusion control method for brain-controlled vehicle
  • Intention priority fuzzy fusion control method for brain-controlled vehicle

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Embodiment

[0034] Example: The present invention designs a set of BCV lateral control system based on shared control, such as figure 1 Shown. The BCI type selected in this embodiment is an improved SSVEP-SSMVEP (brain-computer interface for steady-state motor evoked potential based on rotational visual perception). The overall work flow is: First, the brain-controlled driver decides a steering command (steering wheel to the left, steering wheel to the right, and steering wheel to hold) based on vehicle status and environmental information. Then the driver generates EEG signals representing three steering commands by looking at three patterns with different rotation frequencies in the user interface. The left, center, and right patterns correspond to turn left, hold, and turn right respectively. 3 paradigm patterns such as image 3 Shown in the upper left part of the. Then the EEG signal is collected by the collecting device, and the collected EEG signal is sent to the fuzzy brain-contro...

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Abstract

The invention discloses an intention priority fuzzy fusion control method for a brain-controlled vehicle. The intention priority fuzzy fusion control method comprises the steps of: deciding a brain-controlled command by a brain-controlled driver based on a vehicle state and environment information, wherein the brain-controlled command comprises turning a steering wheel to the left, turning the steering wheel to the right and keeping the steering wheel; secondly, according to a type of a used brain-computer interface, applying corresponding stimulation to the brain-controlled driver through a user interface, wherein the stimulation comprises a rotation paradigm picture; subjecting acquired electroencephalogram signals to signal decoding and taking the decoded signals as one path of input signals to be sent to a fuzzy brain control fusion controller; synthesizing the brain-controlled command and the current vehicle state by means of the fuzzy brain control fusion controller in real time;deciding whether to execute the brain-controlled command or not and how to execute the brain-controlled command according to a fuzzy rule based on a principle of respecting subjective ideas of peopleas much as possible; and finally, outputting a steering wheel turning angle and sent it to a vehicle. The intention priority fuzzy fusion control method realizes cooperative control over automatic control and brain control, and therefore the performance of a brain-controlled system is improved.

Description

Technical field [0001] The invention relates to a control method of a brain-controlled vehicle, in particular to an intention priority fuzzy fusion control method for a brain-controlled vehicle. Background technique [0002] At present, the hybrid intelligence of man and machine has become an advanced form of artificial intelligence. There are many paradigms in human-computer hybrid intelligence, one of which is the brain-computer interface. The brain-computer interface (BCI) analyzes brain signals to understand the intentions and states of people that can be used to control various machines. Due to its excellent time resolution, non-invasiveness and good portability, compared with other neuroimaging technologies, electroencephalography (EEG) is more widely used. There are many researches on control based on electroencephalogram (EEG) signals, such as electromyographic prostheses, brain-controlled wheelchairs, brain-controlled robots, brain-controlled drones, brain-controlled v...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/00G05D1/02
CPCG05D1/0016G05D1/0223G05D1/0221G05D1/0276
Inventor 董娜张文锜李英杰高忠科
Owner TIANJIN UNIV
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