Traffic signal self-adaptive iterative learning control method for attenuation memory de-counterfeiting control

An iterative learning control and adaptive iterative technology, applied in the direction of controlling traffic signals, complex mathematical operations, etc., can solve problems such as the iterative effect cannot be achieved, and achieve the effect of improving traffic efficiency, improving accuracy, and realizing dynamic changes.

Inactive Publication Date: 2020-11-17
TAIYUAN UNIV OF TECH
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Problems solved by technology

[0004] The main purpose of the present invention is to overcome the technical deficiencies of traditional signal control schemes, and propose open-closed-loop PD-type iterative learning control based on the repetitive characteristics of traffic flow. Due to real-time changes in traffic flow, the system structure will change to a certain extent, and the fixed closed-loop The learning law cannot achieve the best itera

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  • Traffic signal self-adaptive iterative learning control method for attenuation memory de-counterfeiting control
  • Traffic signal self-adaptive iterative learning control method for attenuation memory de-counterfeiting control
  • Traffic signal self-adaptive iterative learning control method for attenuation memory de-counterfeiting control

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[0028] In order to have a clearer understanding of the technical features, objectives and effects of the present invention, the specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0029] The main purpose of the present invention is to overcome the technical shortcomings of traditional signal control schemes, and propose open-closed loop PD-type iterative learning control based on the repetitive characteristics of traffic flow, and aim at the influence of historical traffic flow data on the current real-time state over time. It keeps decreasing, and it is proposed to add an attenuation memory function to the anti-counterfeiting control performance index function to realize the dynamic change of the closed-loop learning law, improve the accuracy of iterative learning, and thereby improve the traffic efficiency of the road network.

[0030] See figure 1 , The present invention provides a traffic signal adaptive i...

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Abstract

The invention relates to a traffic signal self-adaptive iterative learning control method for attenuation memory de-counterfeiting control. The method combines attenuation memory de-counterfeiting control with iterative learning control so as to overcome the technical defects of the traditional signal control scheme. Open-loop and closed-loop PD type are adopted for iterative learning control by taking the repetitive characteristic of traffic flow as an entry point, therefore, in order to solve the problem that the influence of traffic flow historical data on the current real-time state is continuously reduced as time goes on, an attenuation memory function is added to a pseudo-removal control performance index function, dynamic change of a closed-loop learning law is realized, and the accuracy of iterative learning is improved, so that the traffic efficiency of a road network is improved.

Description

technical field [0001] The invention relates to the technical field of urban traffic signal control, in particular to a traffic signal self-adaptive iterative learning control method for attenuation memory and false control. Background technique [0002] With the continuous progress and development of social science and technology, the scope of people's life and travel continues to expand, and the improvement of material life prompts people to pursue higher-quality spiritual life. However, these changes will be realized based on the urban transportation system, which makes urban planners Focus on transportation infrastructure. However, under the new development situation, urban traffic also has many new problems. The cross-mixing of various urban traffic problems has brought serious challenges to traffic management departments, such as traffic congestion, environmental pollution, how to coordinate various travel modes, and the use of new energy. Transportation applications,...

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Application Information

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IPC IPC(8): G08G1/07G06F17/10
CPCG08G1/07G06F17/10
Inventor 闫飞仇江辰田建艳李浦
Owner TAIYUAN UNIV OF TECH
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