PI Controller for IPMC Actuators Based on Nafion®/PT Using Machine Vision for Feedback Response at Different Relative Humidities

Abstract

Ionomeric Polymer-Metal Composites (IPMCs) are sandwich-like materials based in a polymeric membrane covered on both sides by metallic electrodes. Its operation mechanism consists of hydrated ions migration in response to an external electrical field generated between the electrodes, leading to a spatially nonuniform mass accumulation which causes the device to bend. Its performance as an actuator depends mainly on the environment's relative humidity and electrical stimuli. Consequently, IPMCs present variations in the electromechanical properties exhibiting nonlinearities and time-varying behaviors, limiting the major applications. For this reason, this paper investigated a PI controller performance to overcome these drawbacks and effectively control a Nafion-based IPMC-Li + exposed to different relative humidities and electrical stimulis. The PI control system uses a camera with a machine vision application as a feedback sensor. Support instrumentation was developed to control the relative humidity, apply an electrical stimulus, and measure the electromechanical response. The pattern recognition algorithm implemented in the controller is efficient, with accuracy above 95%, making the feedback sensor reliable. Therefore, the PI controller was effective, stable, and capable of controlling and characterizing IPMC devices when relative humidity was above 60% at a low-frequency displacement and avoided the undesired back-relaxation phenomenon.

Novel IP2C sensors with flexible electrodes based on plasma-treated conductive elastomeric nanocomposites

“…Conventional IPMCs were produced using the electroless plating method developed by Oguro et al [51] and modified by our group [52,53]. First, the ionomeric polymer (Nafion) is immersed in a platinum-amino complex ([Pt(NH 3 ) 4 ]Cl 2 ) solution containing 3 mg of Pt 2+ per cm 2 of the film.…”

Beyond static: Tracking the dynamic nature of water absorption and Young's modulus in IPMC devices

“…61 Many efforts have been made to develop new strategies for controlling them in real-world applications; the most straightforward is the proportional-integral-derivative controller. 46 In this case, predictive (feedforward) and corrective (feedback) schemes proved to be effective methods capable of ensuring proper system functioning and reliability. 62 The input data (voltage and current) and output (electromechanical response) must be acquired and applied, precisely.…”

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

“…The classical identification model reveals the physical characteristics of the IPMC actuator to a low degree, and the output displacement and input voltage are the physical quantities directly modeled. These models can predict the displacement of IPMC actuator well, [33][34][35][36][37][38][39][40][41] but only a few models can characterize the hysteresis or creep of IPMC. [38][39][40][41] Based on this model, a controller can be developed to achieve more accurate IPMC control.…”

“…When the neural network model is available, system identification can develop a nonlinear controller to adjust the performance of the actuator. [52] The autoregressive model, such as models, [33,34,36,38,48,52] uses previous samples from the system output during its recognition process, constituting a fundamental constraint on the practical applications of IPMCs. However, acquiring information about the output is not feasible in dominant applications of IPMCs, especially in biomedical applications.…”

“…Notably, the identification model derived from simple experimental identification is extensively used in developing IPMC controllers, [ 35 ] but not all controls are based on the model. [ 36 ] Open‐loop control typically relies on the precise model of IPMCs. However, temperature influences the dynamic characteristics of IPMCs.…”