Open AccessEvent-triggered Adaptive Dynamic Surface Output Feedback Inverse Control for a Class of Hysteresis Nonlinear Systems
Author(s) -
Wenbo Liu,
Shuai Di,
Yaoqi Dai,
Wenjing Cao
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/752/1/012006
Subject(s) - control theory (sociology) , feed forward , nonlinear system , controller (irrigation) , observer (physics) , computer science , state observer , discretization , adaptive control , mathematics , control engineering , engineering , control (management) , physics , artificial intelligence , mathematical analysis , agronomy , quantum mechanics , biology
Aiming at the difficult problem of the nonlinear system with hysteresis, the Prandtl-Ishlinskii model is used to describe the system. A neural network-based output feedback adaptive dynamic surface inverse control (DSIC) scheme is proposed. Firstly, in order to overcome the hysteresis compensation error, an auxiliary design parameter is introduced into the observer to construct an improved high-gain k-order filter state observer to accurately estimate the unmeasurable state. Then, the inverse of the asymmetric displacement matrix of the Prandtl-Ishlinskii model is used as feedforward compensation. the unknown density function with different thresholds is not estimated, the analysis compensation error is obtained, the over-parameterization problem is effectively avoided. At the same time, the event trigger mechanism is introduced in the controller design process to discretize the continuous control signal under the condition of event triggering to improve the computational efficiency of the controller. Finally, the simulation is verified, the results shows the control scheme has higher control precision and faster control speed.