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The design and development of eco-friendly renewable energy sources is a critical process in the power generation system. Power generation of photovoltaic system depend on temperature and irradiation. Variation of atmospheric conditions need to find points for every instant on V-I characteristics of PV in which maximum power transfer from source to load is achieved. This work deals with Maximum Power Point Tracking (MPPT) method based on Adaptive Neuro Fuzzy Interference System (EANFIS) in standalone operation. The novelty is introduced in the design of inverter, motor selection, and maximum power point tracking. Quasi-Z-source inverter (qZSI) is designed with Z-shaped impedance network to continuously draw constant current from solar panel. MPPT enhance the efficiency of PV panel via load matching; however, it may be affected by environmental changes. Hence, an EANFIS-based MPPT technique is used in the proposed work to confirm maximum power delivery to current motor. The proposed method is the combination of ParticleSwarmOptimization (PSO) and Adaptive Neuro Fuzzy Inference System (ANFIS). Training stage of ANFIS is optimized by PSO to handle switching angle of Multi-Level Inverter (MLI) and generate harmonic-less control voltage, hence named Enhanced ANFIS (EANFIS). Voltage and current control of solar panel decide maximum power generation which is verified using Simulink and practical environment. Thus, EANFIS-based MPPT technique achieved the maximum tracking efficiency of 94% which is better than other comparison methods, namely P&O, RBFNN, ANN, and IDISMC. [ABSTRACT FROM AUTHOR]

The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature. [ABSTRACT FROM AUTHOR]

PIC microcontroller has a vital role in various types of controllers and nowadays the presence of PIC microcontroller is unavoidable in most control applications. This paper describes the enhancement of soft starting of induction motors using PIC microcontroller. Soft starting is required for the induction motors with reduced applied voltages so that the peak starting current is reduced and the startup of the motor is smooth with controlled torque and reduced mechanical vibrations, reduced starting current with correspondingly reduced bus voltage drops. While many of the available schemes of soft starting offer better results in view of smooth starting process, the proposed methodology offers soft starting as well as it cares about the source current quality. In contrast to the conventional multistep starting scheme, in this work a continuously controlled starting scheme is proposed. The three phase AC voltage controller topology is used as the core controller. In each of the half cycles, instead of a single conduction period with a single delay angle, the proposed AC voltage controller is switched symmetrically in each half cycle with multiple pulses in each quarter cycle. Symmetrically placed fixed numbers of switching pulses are used. The paper also describes the various time ratio controls namely the phase angle controller, the extinction angle controller and the symmetrical angle controller. The design aspects of the proposed soft starting scheme and the validation of the proposed system in the MATLAB SIMULINK environment are presented in this paper. [ABSTRACT FROM AUTHOR]

Generally, partially shaded conditions frequently arise in large photovoltaic generation systems which in turn cause system losses. Therefore, arrival of multiple peak values is possible in the power–voltage characteristic curves of photovoltaic systems. Such kind of issues is resolved through the usage of novel control algorithms for multilevel dc link inverters. These algorithms depend on the arrangement of pulse width modulation and direct pulse width modulation system to be with MPPT performance based on fuzzy controller to control the multilevel DC link inverter. Under the partial shading conditions, the proposed algorithm is applied on single-phase seven-level inverter with isolated maximum power point tracking techniques. The maximum power recovery of photovoltaic sources is enabled by several maximum power point tracking (MPPT) techniques like modified perturb and observe (P&O), incremental conductance and voltage hold P&O. The spectral quality of the inverter output is observed through the simulation studies of MATLAB/Simulink working platform. Also, hardware results are verified with the help of ATMEGA8 microcontroller. [ABSTRACT FROM AUTHOR]

An effort is made to design the fuzzy proportional-derivative (PD) plus I controller for a nonlinear cruise control system in automobiles, which provides adaptive capability in set-point tracking performance. A cruise control system has been considered as a nonlinear first order plus delay time model to exhibit the control behaviour involved in both conventional proportional-integral-derivative (PID) control and fuzzy control. The paper demonstrates the design of fuzzy PD plus I controller including comparative investigation with control structures like PID, I - PD, and PI - D using Simulink modelling. Real-time implementation has been carried out on a robotic prototype using Arduino UNO micro-controller. Based on the performance measures such as integral absolute error (IAE) and integral squared error (ISE), the proposed fuzzy PD plus I structure shows superior performance on servo and regulatory problems in the cruise control system. This control structure avoids integral windup issues and to suppress the derivative kick in the cruise control system. [ABSTRACT FROM AUTHOR]

Fault detection and isolation are related to system monitoring, identifying when a fault has occurred, and determining the type of fault and its location. Fault detection is utilized to determine whether a problem has occurred within a certain channel or area of operation. Fault detection and diagnosis have become increasingly important for many technical processes in the development of safe and efficient advanced systems for supervision. This paper presents an integrated technique for fault diagnosis and classification for open- and short-circuit faults in three-phase inverter circuits. Discrete wavelet transform and principal component analysis are utilized to detect the discontinuity in currents caused by a fault. The features of fault diagnosis are then extracted. A fault dictionary is used to acquire details about transistor faults and the corresponding fault identification. Fault classification is performed with a fuzzy logic system and relevance vector machine (RVM). The proposed model is incorporated with a set of optimization techniques, namely, evolutionary particle swarm optimization (EPSO) and cuckoo search optimization (CSO), to improve fault detection. The combination o f optimization techniques with classification techniques is analyzed. Experimental results confirm that the combination of CSO with RVM yields better results than the combinations of CSO with fuzzy logic system, EPSO with RVM, and EPSO with fuzzy logic system. [ABSTRACT FROM AUTHOR]

This paper presents a comparative evaluation of Fuzzy Logic (FLC) Controller and Open loop Controller for a modified LCL Resonant Converter has been simulated and the performance is analyzed. A three element LCL Resonant converter working under load independent operation is presented in this paper. In this work, the applicability of the ARM (Advanced RISC Machine) processor LPC 2148 is to be investigated as the controller for resonant converter. The simulation study indicates the superiority of Fuzzy Logic control over the conventional control method. The evaluation version of MATLAB was used to model the LCL topology for varied loads and LCL configurations. A LCL Resonant Inverter is proposed for applications in high frequency distributed AC power systems and Resonant Converter is proposed for applications in many space and radar power supplies. The advantages of the LCL topology are low total harmonic distortion (THD) high efficiency and the ability to handle varying loads. [ABSTRACT FROM AUTHOR]

The resonant converter (RC) is finding wide applications in many space and radar power supplies. Among various RCs LCL, LCC, and LCL-T topologies are broadly used. This manuscript presents a comparative evaluation of steady-state stability of LCL, LCC, and LCL-T resonant configurations. Careful analysis favors LCL RC among the aforementioned three configurations since the stability region is good for the LCL RC over the other configurations. Also, this paper presents a comparative evaluation of proportional integral (PI) controller and fuzzy logic controller for a modified LCL RC. The aforementioned controllers are simulated using MATLAB and their performance is analyzed. The outcome of the analysis shows the superiority of fuzzy control over the conventional PI control method. The LCL RC is proposed for applications in many space and radar power supplies. Design, simulation, and experimental results for a 133-W, 50-kHz LCL RC are presented in this manuscript which provide high efficiency (greater than 89%) even for 50% of load. Efficiencies greater than 80% are obtained at significantly reduced loads (11%). In this paper, the applicability of the Philips advanced RISC machine processor LPC 2148 is also investigated for implementing the controller for an RC. [ABSTRACT FROM AUTHOR]

Power quality is considered to be the major challenging one in the realization of the smart grid. So as to compensate for the issues occurring in power quality, active power filter (APFs) is mainly chosen as they are capable of filtering fast and has some active compensation. Also, load current related power quality constraint can be solved, such as unbalanced power, huge (Total harmonic distortion) THD level, and reduced power factor. For correcting the inappropriate supply of voltage and load current, the unified power quality conditioner (UPQC) and an effective integration of wind turbine are employed. A UPQC is a group of both shunt and series APF in a continuous manner having a conventional DC link capacitor. The voltage control of the DC link capacitor is significant in attaining a preferred performance on UPQC. In this paper, the UPQC with a Modified Grey Wolf Optimization (MGWO) based PI controller integrated with renewable energy like Wind turbine squirrel cage induction generator (SCIG) was implemented for the elimination of voltage and current harmonics imperfection precisely. Likewise, the Modified Grey Wolf Optimization (MGWO) was also exploited in UPQC. The performance analysis was made with UPQC, without UPQC, and with MGWO & UPQC and the simulation, outcomes are estimated and compared for the parameters THD values, load voltage and current. Also, the performance analysis was implemented in hardware prototype set-up and the results attained are depicted. [ABSTRACT FROM AUTHOR]