Preface

Luongo, Angelo

doi:10.1007/s11012-014-0089-5

Cited by 4 publications

(1 citation statement)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This model consists of a system of four physical domains interacting via coupling terms, which further describe the microscopic phenomena that produces the electromechanical transduction of IPMCs. This work mitigates the amount of water lost in IPMC actuators by replenishing IPMC water supply, when needed, by using a mechanism that encapsulates the IPMC in a wet environment [29,30].…”

Section: Introductionmentioning

confidence: 99%

Adaptive observer-based control for an IPMC actuator under varying humidity conditions

Bernat

Kołota

2018

Smart Mater. Struct.

View full text Add to dashboard Cite

As ionic polymer metal composites (IPMC) are increasingly applied to mechatronic systems, many new IPMC modeling efforts have been reported in the literature. The demands of rapidly growing technology has generated interest in advancing the intrinsic actuation and sensing capabilities of IPMC. Classical IPMC applications need constant hydration to operate. On the other hand, for IPMCs operating in air, the water content of the polymer varies with the humidity level of the ambient environment, which leads to its strong humidity-dependent behavior. Furthermore, decreasing water content over time plays a crucial role in the effectiveness of IPMC. Therefore, the primary challenge of this work is to accurately model this phenomenon. The principal contribution of the paper is a new IPMC model, which considers the change of moisture content. A novel nonlinear adaptive observer is designed to determine the unknown electric potential and humidity level in the polymer membrane. This approach effectively determines the moisture content of the IPMC during long-term continuous operation in air. This subsequently allows us to develop an effective back-stepping control algorithm that considers varying moisture content. Data from experiments are presented to support the effectiveness of the observation process, which is shown in illustrative examples.

show abstract

Section: Introductionmentioning

confidence: 99%