Modeling and Control of IPMC Actuators Based on LSSVM-NARX Paradigm

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.

Application‐Oriented Modeling of Soft Actuator Ionic Polymer–Metal Composites: A Review

“…Zamyad et al [ 46 ] proposed an improved ANFIS‐NARX model that extends the input space by substituting a hysteresis operator for the previous output samples. In order to overcome the IPMC hysteresis phenomenon, Huang et al [ 47 ] used the least squares support vector machine (LSSVM) NARX model to model the tip displacement of IPMC actuators and proposed an artificial honeycomb algorithm to optimize the LSSVM NARX model's parameters. A related study has shown that there is a definite relationship between the electrical characteristics and shape of IPMCs, especially between the resistance and shape of IPMCs.…”

Challenges and Perspectives in Control of Ionic Polymer-Metal Composite (IPMC) Actuators: A Survey

“…Among such models are the Preisach operator [81], Prandtl-Ishlinskii hysteresis models [28], [42], [43], [82], [83], and Bouc-Wen hysteresis model [27]. In [100] the least squares support vector machine nonlinear autoregressive model was developed to eliminate the effect of the hysteresis. Moreover, an inverse controller was combined with the PID feedback control to compensate the hysteretic characteristics.…”

Least Square Support Vector Machines Laguerre Hammerstein Model Identification and Non-linear Model Predictive Controller Design for pH Neutralization Process

“…Several researchers have tried to get an identified model of nonlinear processes for the controller implementation [4][5][6]. Many processes are nonlinear in the chemical, food, and pharmaceutical industries and have multiple operating regions over their operating range.…”