This paper presents a Generalized MPPT control based DC-DC boost converter to generate continuous power with its preserved dynamic control system. The PV array is modeled with algebraic loop to achieve accurate solution with iterations in large sample of times. The larger time steps are utilized in this model to obtain fast simulation. MPPT controller embedded with Generalized P and O technique in PV system to regulate duty cycle through which maximum continuous power will be obtained. The MPPT controller with proposed converter is designed in a strategy to extract continuous power regardless of irradiance and temperature. 100kW PV array connected 25kV utility grid is examined in MATLAB SIMULINK and compared with other models in available literature to show effectiveness of designed model.

In this paper, a novel model-based method for induction motor with stator inter-turn short-circuit fault detection is presented. The proposed technique is based on the whiteness of innovation sequence developed by the standard extended Kalman filter. Nonlinear Generalized Likelihood Ratio method is applied to identify the faulty phase along with its severity. This technique just requires current sensors which are available in most induction motor drive systems to provide good controllability, and induction motor design details are not necessary. Computer simulations are carried out for a 4-hp squirrel cage induction motor using MATLAB environment. The results show the superiority of the proposed method as it provides better estimates for stator interturn fault detection.

Many wound rotor induction motor models are available in the literature. In this paper, a modified extended wound rotor induction motor model using reference frame theory is presented. State estimation of the proposed WRIM model is carried out using discrete-time extended Kalman filter (DTEKF). Rotor current sensors are required for state estimation which are usually present in all WRIM applications. Analytical simulations are carried out for a 3.7 kW four-pole wound rotor induction motor using MATLAB scientific environment-version R2016a. The results show the advantage of the proposed state estimation in realistic applications from the rotor prospective.

Many induction motor models are available in the literature for modeling, simulation, control as well as fault diagnosis. In this paper, novel induction motor models are formulated based on stationary, rotor and synchronously rotating reference frames. All these proposed models are compared and analyzed in terms of their diagnostic relevance to stator inter-turn faults. Ability to generate distinct residual signatures is a key for model-based diagnostics. Performance of these models in term of their ability to diagnose a fault is compared and best suited models are suggested based on a discriminatory ability index proposed in this paper. As continuous-time extended Kalman filter (CTEKF) is the most commonly used estimator for state estimation, the same has been considered. Computer simulations are carried out for a 4-hp squirrel-cage induction motor using MATLAB. The results prove that all induction motor models do not perform equally well when it comes to fault diagnosis.

This paper presents new passive islanding detection methods for a grid-connected PV (GCPV) system. In the first proposed approach, the 3-phase voltage (p.u) at the point of common coupling (PCC) is extracted and calculates the mean voltage samples. This is passed through the wavelet transform, decomposed up to the level-6(d6) coefficient and then it obviously localizes the event and as a result detects the islanding condition. Finally, to calculate the energy and standard deviation (STD) at level-6(d6) for 2-cycles mean voltage samples it will discriminate islanding condition from the non-islanding condition. The second proposed approach, the negative sequence voltage is considered at PCC. This is passed through the wavelet transform and successfully detects the islanding state. This method also calculates the energy and standard deviation (STD) at level-4(d4) for one cycle of negative sequence voltage it will discriminate islanding situation from the non-islanding situation. The proposed passive methods are tested on a GCPV system with islanding and non-islanding (normal operation and abrupt load change) situation. These techniques are turn out the extremely successfully in islanding detection at PCC for GCPV system. The test GCPV system and simulations are developed in MATLAB/Simulink Software.

A novel model-based strategy for bearing fault detection in induction motor is presented. The proposed technique is based on state estimation of induction motor using non-linear derivative free kalman filter. Non-invasive fault detection is the critical advantage of the proposed strategy. The method is robust towards unbalanced supply and variable speed. Analytical computations are carried on 4 hp squirrel-cage induction motor using MATLAB software for different bearing faults. The presented simulation results are validated using auto correlation coefficients. Additionally, the proposed strategy provides better estimates for all types of bearing faults.