Abstract
Ionic polymer-metal composites are electrically driven intelligent composites that are readily exposed to bending deformations in the presence of external electric fields. Owing to their advantages, ionicpolymer-metal composites are promising candidates for actuators. However, ionicpolymer-metal composites exhibit strong nonlinear properties, especially hysteresis characteristics, resulting in severely reduced control accuracy. This study proposes an ionic polymer-metal composite platform and investigates its modeling and control. First, the hysteresis characteristics of the proposed Pt-electrode ionic polymer-metal composite are tested. Based on the hysteresis characteristics, ionic polymer-metal composites are modeled using the Prandtl-Ishlinskii model and the least squares support vector machine-nonlinear autoregressive model, respectively. Then, the ionic polymer-metal composite is driven by a random sinusoidal voltage, and the LSSVM-NARX model is established on the basis of the displacement data obtained. In addition, an artificial bee colony algorithm is proposed for accuracy optimization of the model parameters. Finally, an inverse controller based on the least squares support vector machine-nonlinear autoregressive model is proposed to compensate the hysteresis characteristics of the ionic polymer-metal composite. A hybrid PID feedback controller is developed by combining the inverse controller with PID feedback control, followed by simulation and testing of its actual position control on the ionic polymer-metal composite platform. The results show that the hybrid PID feedback control system can effectively eliminate the effects of the hysteresis characteristics on ionic polymer-metal composite control.
Highlights
Intelligent materials are among the most rapidly developing technologies globally [1]
The the leastsquares support vector machine (LSSVM)-NARX model was verified using tip displacements at sinusoidal actuating voltages, LSSVM‐NARX model was verified using tip displacements at sinusoidal actuating voltages, where whereby one voltage has an amplitude of 2V and a frequency of 1/2π Hz and another voltage has by one voltage has an amplitude of 2V and a frequency of 1/2π Hz and another voltage has an an amplitude of 3V and a frequency 5/2π Hz
To verify the adaptability of LSSVM‐NARX model, two random sinusoidal actuating voltages were applied, the results of experiments are shown in Figures 25 and 26, the corresponding error curves of LSSVM‐NARX model are shown in Figure (RMSE = 0.6695) and Figure
Summary
Intelligent materials are among the most rapidly developing technologies globally [1]. Intelligent polymer materials have attracted considerable attention owing to their light weight, large deformation, good biocompatibility, long service life, low cost, and reasonable mouldability. Such intelligent materials exhibit various responses (e.g., volume expansion, shape reconstruction, and color change) to external stimulations. EAPs. Ionic polymer-metal composites (IPMCs) are ionic EAPs that have been widely employed as actuators in bionics, biomedicine, and microelectronics, owing to their low actuating voltage (1–5 V), rapid response, large actuating displacement, good mouldability, and excellent flexibility [9,10,11,12,13,14,15,16]
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