Mitigation of Power Quality Issues by Nine Switches UPQC Using PI & ANN with Hysteresis Control

In this paper, a neural network based internal model control is designed for a pH process and its performance is compared with conventional PI controller and inverse neuro

Temperature control using adjusted fuzzy-PI controller with SR III configuration with noisy data: (a) Temperature inside the bioreactor and control signal sent to: (b) cold

It was observed that Modified Oswin and Modified Halsey models showed random residual distribution, besides lower values of standard deviation of the estimate and relative mean

Figure 26: Input voltage ( v ref = 30 V ) of the buck converter with the control system designed in Section 3.3 (voltage loop with inner peak current

Chandra, “ A new control philosophy for a unified power quality conditioner (UPQC) to coordinate load- reactive power demand between shunt and series inverters, ”

The performance of this method was verified by simulations with a wide range of parameters including the size of the segregation population, recombination rate, genome size and

For the pilot reactor, the practical performance of the reactor temperature control systems with on-off con- trol and with PI control is in good accordance with the

The current control loop consists of a hysteresis current controller (HCC). The block diagram of a hysteresis current controller is shown in Fig. HCC is used to