Linear and nonlinear arx model for intelligent pneumatic actuator systems

Abstract

System modeling in describing the dynamic behavior of the system is very important and can be considered as a challenging problem in control systems engineering. This article presents the linear and nonlinear approaches using AutoRegressive with Exogenous Input (ARX) model structure for the modeling of position control of an Intelligent Pneumatic Actuator (IPA) system. The input and output data of the system were obtained from real-time experiment conducted while the linear and nonlinear mathematical models of the system were obtained using system identification (SI) technique. Best fit and Akaike’s criteria were used to validate the models. The results based on simulation reveals that nonlinear ARX (NARX) had the best performance for the modeling of position control of IPA system. The results show that nonlinear modeling is an effective way of analyzing and describing the dynamic behavior and characteristics of IPA system. This approach is also expected to be able to be applied to other systems. A future study exploring the execution of other model structures in demonstrating the position control of IPA system would be exceptionally intriguing.