Optimization technique for networked control DC motor with network-induced delays and noise

An industrial control with the network environment faces the data transfer interrupt or disturbances due to noise generated by the machinery's vibration and heavier components. Even though there are enough advantages over network in a closed loop system to control and automate in distant locations. In contrary effect on the poor performance and unstable system behavior due to delays in the network, missing of data and noise is major alarms in Networked Control System (NCS) design. Hence it motivate in developing a suitable controller for NCS, which could overcome the network deficiency. Speed control of a DC motor is developed under a noisy networked environment. A strategy to control and trail the speed of the DC motor in the transport medium with network noise and delays. The Particle Swarm Optimization (PSO) is implemented for its simplicity in implementing and no gradient data is needed to resolve an array of data under various optimization problems. To optimize the PID controller a new technique such as PID - PSO is employed. The effectiveness of planned controllers for networked DC motor is synthesized by simulation and compared with various controllers as PID, Fuzzy-Modulated PID (FMPID), Fuzzy Logic Controller (FLC), NARMA-L2 Controller and Adaptive Neuro-Fuzzy Controller (ANFC).