Fuzzy neural network controller

A fuzzy neural network and neural network technology, applied in the field of fuzzy neural network controller, can solve the problems of complex and changeable characteristics of the manipulator system, and it is difficult to derive mathematical models, so as to achieve the effect of solving the problem of trajectory tracking and strong adaptability

Pending Publication Date: 2020-10-30
MAANSHAN TECHN COLLEGE
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Problems solved by technology

However, the characteristics of the manipulator system are complex and changeable, and it is affected by many uncertain factors, such as load changes, self-uncertain factors, etc., so it is difficult to derive an accurate mathematical model

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Embodiment Construction

[0027] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. the embodiment. Elements and features described in one embodiment of the present invention may be combined with elements and features shown in one or more other embodiments. It should be noted that representation and description of components and processes that are not related to the present invention and that are known to those of ordinary skill in the art are omitted from the description for the purpose of clarity. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0028] ...

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Abstract

The invention discloses a fuzzy neural network controller. A signal collector is connected with the input end of the fuzzy neural network controller; a computer is connected with the input end of thefuzzy neural network controller; the output end of the fuzzy neural network controller is connected with a signal processor; a manipulator model is connected with the signal processor, the signal collector is connected with the manipulator model, the manipulator model is connected with a data collector, the data collector is connected with the fuzzy neural network controller, the output end of thefuzzy neural network controller is connected with an indicator lamp through a signal return device, and the indicator lamp is arranged between the signal collector and the fuzzy neural network controller. According to the fuzzy neural network controller, parameters of the fuzzy neural network controller are optimized in combination with a particle swarm algorithm and a BP algorithm, test simulation analysis verifies that the controller has high adaptability, stability and anti-interference performance, and the track tracking problem of a mechanical arm is effectively solved.

Description

Technical field: [0001] The invention relates to a fuzzy neural network controller. Background technique: [0002] Manipulator control is an important aspect of industrial robot control. Most of the traditional manipulator control methods require the precise mathematical model of the manipulator or the knowledge of manipulator dynamics, but it is difficult to guarantee the stability, robustness and dynamic performance of the whole system of the manipulator system in complex environments. [0003] The manipulator model is a multi-input multi-output system with highly coupled, nonlinear and other dynamic characteristics, and there are many unpredictable factors in the system structure and parameters in actual work. The dynamic model of the manipulator model can reflect the complex relationship among the position, velocity and acceleration of each joint, so establishing the dynamic model of the manipulator is very important for the study of the manipulator trajectory tracking ...

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042G05B13/0285
Inventor 缸明义柳传武史彦夏兴国朱虹
Owner MAANSHAN TECHN COLLEGE
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