Affiliation:
1. College of Mechanical Engineering, Guizhou University , Guiyang 550000 , Guizhou , China
Abstract
Abstract
In order to improve the CNC roll grinder production efficiency, a novel three-point non-contact measurement device is proposed. An adaptive back-stepping control system that combines with a radial basis function neural network (RBFNN) was designed to control the measurement device working position and also to track the periodic reference movement trajectory. In the proposed control system, the RBFNN approximation and tracking ability are used to identify the unknown measuring device dynamic information. Then, the Lyapunov stability theorem is used to derive the adaptive online learning algorithm. All control algorithms are placed in the control chip based on the TMS320F28335 archive. The simulation results show that the proposed control system has a good control effect when applied to the three-point non-contact measuring device in CNC roll grinders.
Funder
Science and Technology Innovation Team Project in Guizhou Province
Training Plan for High-level Innovative Talent in Guizhou Province
Major Science and Technology Project in Guizhou Province
Preferred Project of Scientific and Technological Activities for Personnel Studying Abroad in Guizhou Province
Subject
Energy Engineering and Power Technology
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