An Adaptive Control Scheme Based on Non-Interference Nonlinearity Approximation for a Class of Nonlinear Cascaded Systems and Its Application to Flexible Joint Manipulators

Control design for the nonlinear cascaded system is challenging due to its complicated system dynamics and system uncertainty, both of which can be considered some kind of system nonlinearity. In this paper, we propose a novel nonlinearity approximation scheme with a simplified structure, where the...

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Published inSensors (Basel, Switzerland) Vol. 24; no. 10; p. 3178
Main Authors Liu, Zhangxing, Jin, Hongzhe, Zhao, Jie
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 01.05.2024
Subjects
Approximation
Artificial intelligence
cascaded system
Control algorithms
Controllers
Engineering
flexible joint
Management science
model-free adaptive control
Neural networks
nonlinearity approximation
Numerical analysis
Parameter identification
Robots
Simulation
Simulation methods
System theory
Unmanned aerial vehicles
model-free adaptive control
cascaded system
nonlinearity approximation
flexible joint
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Summary:Control design for the nonlinear cascaded system is challenging due to its complicated system dynamics and system uncertainty, both of which can be considered some kind of system nonlinearity. In this paper, we propose a novel nonlinearity approximation scheme with a simplified structure, where the system nonlinearity is approximated by a steady component and an alternating component using only local tracking errors. The nonlinearity of each subsystem is estimated independently. On this basis, a model-free adaptive control for a class of nonlinear cascaded systems is proposed. A squared-error correction procedure is introduced to regulate the weight coefficients of the approximation components, which makes the whole adaptive system stable even with the unmodeled uncertainties. The effectiveness of the proposed controller is validated on a flexible joint system through numerical simulations and experiments. Simulation and experimental results show that the proposed controller can achieve better control performance than the radial basis function network control. Due to its simplicity and robustness, this method is suitable for engineering applications.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s24103178