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This study presents an adaptive perturb and observe (P&O)-fuzzy control maximum power point tracking (MPPT) for photovoltaic (PV) boost dc-dc converter. P&O is known as a very simple MPPT algorithm and used widely. Fuzzy logic is also simple to be developed and provides fast response. The proposed technique combines both of their advantages. It should improve MPPT performance especially with existing of noise. For evaluation and comparison analysis, conventional P&O and fuzzy logic control algorithms have been developed too. All the algorithms were simulated in MATLAB-Simulink, respectively, together with PV module of Kyocera KD210GH-2PU connected to PV boost dc-dc converter. For hardware implementation, the proposed adaptive P&O-fuzzy control MPPT was programmed in TMS320F28335 digital signal processing board. The other two conventional MPPT methods were also programmed for comparison purpose. Performance assessment covers overshoot, time response, maximum power ratio, oscillation and stability as described further in this study. From the results and analysis, the adaptive P&O-fuzzy control MPPT shows the best performance with fast time response, less overshoot and more stable operation. It has high maximum power ratio as compared to the other two conventional MPPT algorithms especially with existing of noise in the system at low irradiance.

Current harmonics is one of the most significant power quality issues which has attracted tremendous research interest. Shunt active power filter (SAPF) is the best solution to minimize harmonic contamination, but its effectiveness is strictly dependent on how quickly and accurately its control algorithms can perform. This manuscript reviews various types of existing control algorithms which have been employed for controlling operation of SAPF. Harmonic extraction, DC-link capacitor voltage regulation, current control and synchronizer algorithms are examined and discussed. The most relevant techniques which have been applied for each control algorithm are described and contrasted in an organized manner to identify their respective strengths and weaknesses. It is found that the applied control algorithms differ in two conditions: (1) the condition where harmonic current distortion is treated by the SAPF in the presence of non-ideal source voltage; and (2) the condition where multilevel inverter is employed as the circuit topology of SAPF.

Heating, Ventilating, and Air Conditioning (HVAC) systems are the major energy-consuming devices in buildings. Nowadays, due to the high demand for HVAC system installation in buildings, designing an effective controller in order to decrease the energy consumption of the devices while meeting the thermal comfort demands in buildings are the most important goals of control designers. The purpose of this article is to investigate the different control methods for Heating, Ventilating, and Air Conditioning and Refrigeration (HVAC & R) systems. The advantages and disadvantages of each control method are discussed and finally the Fuzzy Cognitive Map (FCM) method is introduced as a new strategy for HVAC systems. The FCM method is an intelligent and advanced control technique to address the nonlinearity, Multiple-Input and Multiple-Output (MIMO), complexity and coupling effect features of the systems. The significance of this method and improvements by this method are compared with other methods.

In this paper, a new reference current generation method is proposed for effective harmonics mitigation and reactive power compensation of three-level neutral-point diode clamped inverterbased shunt active power filter (SAPF) under nonideal grid voltage conditions. The proposed method is named as dual fundamental component extraction algorithm. In operation, the proposed algorithm extracts at the same time, the desired fundamental current and voltage components for generating reference current and synchronization phases, respectively. As a result, the proposed algorithm is able to generate reference current that ensures in phase operation of SAPF with the operating power system, without depending on any phase-locked loop elements. Besides, the proposed algorithm employs self-tuning filter (STF) for accurate computation of the fundamental components. Design concept and effectiveness of the proposed algorithm are thoroughly studied and evaluated in MATLAB-Simulink. Additionally, a laboratory prototype utilizing TMS320F28335 digital signal processor is built to validate its feasibility. Encouraging findings obtained from both simulation and experimental works demonstrate effectiveness of the proposed algorithm under both ideal and nonideal grid voltage conditions.

Abstract-This paper proposes a new approach to diagnose broken rotor bar failure in a line start-permanent magnet synchronous motor (LS-PMSM) using random forests. The transient current signal during the motor startup was acquired from a healthy motor and a faulty motor with a broken rotor bar fault. We extracted 13 statistical time domain features from the startup transient current signal, and used these features to train and test a random forest to determine whether the motor was operating under normal or faulty conditions. For feature selection, we used the feature importances from the random forest to reduce the number of features to two features. The results showed that the random forest classifies the motor condition as healthy or faulty with an accuracy of 98.8% using all features and with an accuracy of 98.4% by using only the mean-index and impulsion features. The performance of the random forest was compared with a decision tree, Naïve Bayes classifier, logistic regression, linear ridge, and a support vector machine, with the random forest consistently having a higher accuracy than the other algorithms. The proposed approach can be used in industry for online monitoring and fault diagnostic of LS-PMSM motors and the results can be helpful for the establishment of preventive maintenance plans in factories.

This study presents an improved self-charging algorithm by introducing a new feature known as step size error cancellation for better performance of DC-link capacitor voltage control in single-phase shunt active power filter (SAPF). Previous works of self-charging algorithms were focused only for steady-state operation by using either proportionalintegral (PI) or fuzzy logic control (FLC). However, in a certain operation of any power system, dynamic operation may also happen. Thus, by introducing step size error cancellation as an additional feature to the self-charging algorithm, both steady state and dynamic operations can be covered. For evaluation and comparison analysis, self-charging with PI and FLC algorithms have been developed too. All the algorithms were simulated in MATLAB-Simulink, respectively, together with the single-phase SAPF. For hardware implementation, the proposed algorithm was programmed in TMS320F28335 digital signal processing board. The other two conventional self-charging algorithms were also programmed for comparison purposes. From the results and analysis, the proposed self-charging with step size error cancellation shows the best performance with high accuracy, fast response time and less overshoot and undershoot. It performs well in both steady state and dynamic operations as compared with both previous self-charging techniques which only work well in steady-state operation.

Abstract:Harmonic distortion in power networks has greatly reduced power quality and this affects system stability. In order to mitigate this power quality issue, the shunt active power filter (SAPF) has been widely applied and it is proven to be the best solution to current harmonics. This paper evaluates the performance of the modified synchronous reference frame extraction (MSRF) algorithm with fuzzy logic controller (FLC) based current control pulse width modulation (PWM) inverter of three-phase three-wire SAPF to mitigate current harmonics. The proposed FLC is designed with a reduced amount of membership functions (MFs) and rules, and thus significantly reduces the computational time and memory size. Modeling and simulations of SAPF are carried out using MATLAB/Simulink R2012a with the power system toolbox under steady-state condition, and this is followed with hardware implementation using a TMS320F28335 digital signal processor (DSP), Specrum Digital Inc., Stafford, TX, USA. The results obtained demonstrate a good and satisfactory response to mitigate the harmonics in the system. The total harmonic distortion (THD) for the system has been reduced from 25.60% to 0.92% and 1.41% in the simulation study with and without FLC, respectively. Similarly for the experimental study, the SAPF can compensate for the three-phase load current by reducing THD to 5.07% and 7.4% with and without FLC, respectively. Keywords: active power filter (APF); modified synchronous reference frame (MSRF) d-q theory; fuzzy logic controller (FLC); low pass filter (LPF); high pass filter (HPF); band pass filter (BPF)