Decoupling control method of single leg joint of hydraulic four-leg robot

A quadruped robot, decoupling control technology, applied in the field of single-leg joint decoupling control of hydraulic quadruped robots, can solve the problems of complex control methods and difficult control methods to be transplanted into legged walking robots

Inactive Publication Date: 2016-05-04
HARBIN UNIV OF SCI & TECH
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Problems solved by technology

[0008] Both of the above two inventions are researches on the decoupling control of robots, but the types of robots studied by the two inventions are not legged walking robots, and their control methods are difficult to transplant to legged walking robots, especially for four-wheel robots driven by hydr

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  • Decoupling control method of single leg joint of hydraulic four-leg robot
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  • Decoupling control method of single leg joint of hydraulic four-leg robot

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Embodiment Construction

[0089] The present invention will be further described in detail below in combination with specific embodiments.

[0090] The present invention is a prediction-based decoupling control method for a single-leg joint of a hydraulic quadruped robot, such as figure 1 As shown, it includes PID neural network decoupling control module (solid line box), neural network model reference decoupling control module (dotted line box) and predictive control module (dotted line box).

[0091] The PID neural network decoupling control module such as figure 2 As shown, two BP neuron sub-networks are used, and the hidden layers of each sub-network are proportional (P) neurons, integral (I) neurons and differential (D) neurons.

[0092] The neural network model refers to the decoupling control module such as image 3 As shown, including reference model, neural network identifier, neural network controller.

[0093] The predictive control module such as Figure 4 shown, including reference tr...

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Abstract

The invention discloses a decoupling control method of a single leg joint of a hydraulic four-leg robot. The method comprises proportion integration differentiation (PID) neural network decoupling control, neural network model reference decoupling control and prediction control. The method comprises the following steps that a reference model under the condition that a system is free of coupling is set, and then a neural network controller is trained so that the output of the system can keep up with the output of the reference model; meanwhile, a neural network model is used for prediction, and the next step of output of the system is predicted according to current and previous input and output data of a controlled object; and finally, the weight of the neural network is rectified in an online mode according to the predicted output and the given reference output so that optimizing indexes of the decoupling controller of the neural network can reach the smallest value, and the purpose of decoupling control is achieved. By the adoption of the decoupling control method, the coupling influences among all the joints of the robot can be effectively reduced, and decoupling control over all the joints of the robot is achieved.

Description

technical field [0001] The invention relates to the technical field of quadruped robot control, in particular to a single-leg joint decoupling control method of a hydraulic quadruped robot. Background technique [0002] Hydraulically driven quadruped robot is a typical multi-input multi-output nonlinear system. In general, the input of a certain joint of the leg will be affected by the output of other joints, and at the same time, the output of this joint will also be affected by the input of other joints. Therefore, there is a coupling phenomenon between the joints. For a nonlinear multi-coupling complex system, due to the coupling between multiple variables, the system control becomes very complicated. This nonlinear strong coupling effect can Negligible, the movement of each joint can also be independently analyzed and studied. But in the case of high speed, the nonlinear strong coupling effect will seriously affect the control accuracy of the robot. This brings great ...

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Application Information

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IPC IPC(8): B25J13/00
CPCB25J13/00
Inventor 高炳微高元锋王思凯
Owner HARBIN UNIV OF SCI & TECH
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