Adaptive neural networks for AC voltage sensor-less control of three-phase PWM rectifiers

Fig. Ripple of DC voltage, but the writer insert PWM signals.
Fig. DC bus voltage, but the writer insert AC signals.
Fig (7) line current and line dc voltage, but the writer insert AC signals.

They add 4 equation only, but the equations in another paper are at least 20.
I asked the load to be DC motor before the writer starts the work, but until now I didn’t see the DC motor as a load in the circuit.

Please see the Ref. 07455121.pdf [in Material], it is same control strategy, So the results should be same results with our values and also the results for the source (grid) side and load side have to be inserted and discussed technically.
Compare the simulation results with the reference 07455121 and follow the instructions (insert the same results from our simulation model) which is used in the reference 07455121. add more equations, and discussed the results technically. also, correct the results of the ANN training. make sure that all the results are correct technically and take it from our Simulation.

In this paper, a new adaptive grid voltages estimator for
AC voltage sensorless control of three-phase pulsewidth
modulation (PWM) rectifier is proposed. This method is based on a simple adaptive neural network
(ANN) to estimate online the grid voltages. Its main advantages are the simplicity and low computational cost
requirements. The proposed ANN estimator is inserted in voltage-oriented control (VOC) to perform an AC
voltage sensorless control scheme. As the start-up is a common problem in case of sensorless control, a new
start-up process is also proposed for estimating initial values of the grid voltages. Experimental tests are
carried out to verify the feasibility and robustness of the proposed ANN estimator. Obtained results show good