Neural Network-Based Prediction of Feedback Gain Parameters in Networked Control System

The main challenges which are being faced by the networked control system (NCS) are transmission delays and vacant sampling. This paper proposes a method to design an intelligent feedback controller based on an artificial neural network(ANN) for a networked control system while stability is set as a performance criterion. This proposed controller does an accurate estimation of feedback gain parameters for the random network delay. There is a very thin range of feedback gain parameters that ensure stability in the system concerning each random value of network time delay that may be within the sampling interval and beyond the sampling interval. This paper suggests ANN based learning mechanism to make a networked control system stable in the presence of random delay. The predicted feedback gain parameters with the learning mechanism ensure the NCS stable. Simulation results in MATLAB ensure stability in the loop of the networked control system.