Online Adaptive Smith Predictor with Fuzzy Controller for Networked Control Systems

Networked Control Systems (NCSs) are used for controlling remote plants via shared-band data communication networks. These systems have widely applications in industrial, medical and space sciences fields. Designing of these system deals with the potential instabilities, arises from various parameters. One of these problematic factors is the time delay which is stochastic and varying by these systems nature. However, convenient PID and other common controllers designed to stabilize the closed feedback loop in NCSs are just proper to address constant time delays. This paper proposed a novel control method through the integration of an online adaptive Smith predictor and a fuzzy controller. This suggested design has been applied to control the position of an AC 400 W servo motor as a remote plant via the Ethernet network. Achieved results verified this novel design effectiveness, in reduction of error responses due to the delay time in NCSs. Fuzzy controllers, possess more capabilities to tackle packet dropouts and dynamically system variations and make the system more compatible with none-linear processes. Meanwhile, they provides a more robust system against the big time delay values as large as 600 ms despite their convenient rivals with a limited capacity to handle over 200 ms delays