Experimental Output Regulation of Linear Motor Driven Inverted Pendulum With Friction Compensation

Over the past few decades, the nonlinear output regulation (NOR) theory has attracted extensive attentions in control society. However, few experimental results have been reported about the NOR theory. This article first presents experimental results on discrete-time NOR problem for a linear motor d...

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Published in:	IEEE transactions on systems, man, and cybernetics. Systems Vol. 51; no. 6; pp. 3751 - 3758
Main Authors:	Ping, Zhaowu, Liu, Chenxi, Huang, Yunzhi, Yu, Ming, Lu, Jun-Guo
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.06.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Artificial neural networks Compensation Control algorithms Control theory Controllers Discrete-time nonlinear system Eigenvalues and eigenfunctions Electric motors Friction linear motor driven inverted pendulum (LMDIP) Mathematical model Mechanical systems neural network (NN) Neural networks Nonlinear systems output regulation Pendulums Steady-state
ISSN:	2168-2216, 2168-2232
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Abstract	Over the past few decades, the nonlinear output regulation (NOR) theory has attracted extensive attentions in control society. However, few experimental results have been reported about the NOR theory. This article first presents experimental results on discrete-time NOR problem for a linear motor driven inverted pendulum (LMDIP) system. To solve this problem, it is essential to find the solution of the complicated discrete regulator equations (DREs). Moreover, the friction force commonly exists in mechanical systems and cannot be neglected for control systems requiring high precision tracking performance. We present a novel discrete-time controller by combining neural network (NN) approach and friction-feedforward compensation mechanism. Finally, we verify the proposed control algorithm by experiment and make some comparisons with the linear controller.
AbstractList	Over the past few decades, the nonlinear output regulation (NOR) theory has attracted extensive attentions in control society. However, few experimental results have been reported about the NOR theory. This article first presents experimental results on discrete-time NOR problem for a linear motor driven inverted pendulum (LMDIP) system. To solve this problem, it is essential to find the solution of the complicated discrete regulator equations (DREs). Moreover, the friction force commonly exists in mechanical systems and cannot be neglected for control systems requiring high precision tracking performance. We present a novel discrete-time controller by combining neural network (NN) approach and friction-feedforward compensation mechanism. Finally, we verify the proposed control algorithm by experiment and make some comparisons with the linear controller.
Author	Huang, Yunzhi Yu, Ming Lu, Jun-Guo Ping, Zhaowu Liu, Chenxi
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SubjectTerms	Algorithms Artificial neural networks Compensation Control algorithms Control theory Controllers Discrete-time nonlinear system Eigenvalues and eigenfunctions Electric motors Friction linear motor driven inverted pendulum (LMDIP) Mathematical model Mechanical systems neural network (NN) Neural networks Nonlinear systems output regulation Pendulums Steady-state
Title	Experimental Output Regulation of Linear Motor Driven Inverted Pendulum With Friction Compensation
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