학술논문

Practical Nonlinear Model Predictive Control for Piezoelectric Actuators Based on an Echo State Network
Document Type
Conference
Source
2023 42nd Chinese Control Conference (CCC) Chinese Control Conference (CCC), 2023 42nd. :728-733 Jul, 2023
Subject
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Vibrations
Computational modeling
Piezoelectric actuators
Predictive models
Data models
Nonlinear dynamical systems
Computational complexity
Piezoelectric Actuator
Hysteresis Model
Echo State Network
Nonlinear Model Predictive Control
Language
ISSN
1934-1768
Abstract
The piezoelectric actuator (PEA) is widely used to realize high precise motion of the micro-systems. However, the inherent nonlinear property such as hysteresis, creep, thermal drift and vibration impairs the overall performance and leads to the system instability. In this paper, a practical nonlinear model predictive control (PNMPC) approach based on an echo state network is proposed for the displacement tracking of PEAs. The proposed method has the advantage of omitting the common building process of an inversion model for hysteresis compensation, which avoids the problem of model inversion and the inversion imprecision. Specifically, an echo state network (ESN) is adopted to model the nonlinear dynamics of the PEA system. On this basis, the PNMPC method is designed via utilizing the linearized ESN model, which reduces the computational complexity of the optimization problem caused by nonlinear model predictive control. Finally, the tracking performance of the proposed controller is verified through experimental results.