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Q-function self-adaptation dynamic planning method based on data

A dynamic programming and self-adaptive technology, applied in self-adaptive control, instruments, control/regulation systems, etc., can solve problems such as unfavorable algorithms, redundancy, complex algorithm structure, etc., and achieve the effect of satisfying continuous incentive conditions

Active Publication Date: 2013-07-24
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

However, after adding the system identification network, the structure of the entire algorithm becomes complex and redundant, and the training of the identification network and the operation of the V-function adaptive dynamic programming method are completely separated, which is not conducive to the entire algorithm

Method used

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  • Q-function self-adaptation dynamic planning method based on data
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Embodiment Construction

[0027] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings.

[0028] figure 1 It is an application flowchart of the adaptive dynamic programming method based on Q function.

[0029] Such as figure 1 As shown, the method includes the following steps:

[0030] Step 1, first initialize any stable control strategy, which is required to stably control the controlled system.

[0031] figure 2 is a schematic diagram of the lane keeping problem. Among them, the lateral offset distance of the center of gravity of the vehicle is y cg Refers to the offset distance from the center of gravity of the vehicle to the lane, and the deflection angle ψ between the vehicle and the lane d It refers to the angle between the direction of the vehicle and the tangent direction of the lane, and δ is the angle of the front wheel. A stable control str...

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Abstract

The invention provides a Q-function self-adaptation dynamic planning method based on data. The Q-function self-adaptation dynamic planning method based on the data achieves an optimal control aim. The Q-function self-adaptation dynamic planning method based on the data mainly comprises the following steps: (1) initializing a stable control strategy, (2) initializing a weight value of an actuator and critic neural network through the existing control strategy, (3) according to the current control strategy and a system state of a current state, generating a control motion of a controlled system, exerting the control motion on a controlled member, observing a system state of a next time, (4) regulating the weight value of the actuator and critic neural network, (5) judging whether a current iteration cycle is finished or not, if the current iteration cycle is finished, entering step (6), if the current iteration cycle is not finished, returning to the step (3), (6) judging whether neural network weight values generated by the two closest iteration cycles are obviously changed, if the neural network weight values generated by the two closest iteration cycles are obviously changed, entering the step (2) through a newly generated actor and critic neural network, and if the neural network weight values generated by the two closest iteration cycles are not obviously changed, outputting a final actor and critic neural network.

Description

technical field [0001] The invention relates to the technical field of intelligent control, in particular to a data-based Q function self-adaptive dynamic programming method. Background technique [0002] In the fields of industrial production, aerospace, automotive engineering, etc., the controlled object can use the smallest resources to complete the control objectives under limited resources, that is, optimal control. Optimal control refers to finding an optimal control strategy that can make the performance index function optimal. The performance index function is related to the state of the system and the control strategy adopted, and it can reflect the control effect of the control strategy at the current and future moments. The performance index function for discrete systems can be expressed in mathematical form as the following formula: [0003] V ( x k ) = ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
Inventor 赵冬斌朱圆恒刘德荣
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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