Fuzzy Logic Approach for Maximum Power Point Tracking Implemented in a Real Time Photovoltaic System

A Novel Back-Stepping Sliding Mode Control Strategy of Direct-Drive Wave Energy Converters

In this paper, a maximum energy extraction and tracking strategy for direct-drive wave energy converters (DDWECs) based on back-stepping and sliding mode control strategies are developed. It is well known that the existence of the chattering phenomenon degrades the control performance of conventional sliding mode control (SMC). To mitigate the effects of flutter and external disturbances, a back-stepping sliding model control (BSMC) scheme is proposed. The main features of the proposed methodology are as follows: (1) By using the proposed BSMC, the maximum wave energy of DDWEC can be captured. Moreover, the speed tracking of the permanent magnet linear generator (PMLG), which is a subsystem of DDWEC, tracked in real-time. (2) By virtue of the proposed BSMC, the closed-loop control system is asymptotically stable in finite time. (3) With the superior controllability of the BSMC, it can handle disturbances that the SMC cannot handle. Comprehensive and comparative studies are proved to be superior to the most advanced method

Experimental Analysis of a Fuzzy Scheme against a Robust Controller for a Proton Exchange Membrane Fuel Cell System

Proton exchange membrane fuel cells (PEMFC) are capable of transforming chemical energy into electrical energy with zero emissions. Therefore, these devices had been a point of attention for the scientific community as to provide another solution to renewable sources of energy. Since the PEMFC is commonly driven with a power converter, a controller has to be implemented to supply a convenient voltage. This is an important task as it allows the system to be driven at an operative point, which can be related to the maximum power or an user desired spot. Along this research article, a robust controller was compared against a fuzzy logic strategy (with symmetric membership functions) where both were implemented to a commercial PEMFC through a dSPACE 1102 control board. Both proposals were analysed in an experimental test bench. Outcomes showed the advantages and disadvantages of each scheme in chattering reduction, accuracy, and convergence speed.

Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications

This article contains a review of essential control techniques for maximum power point tracking (MPPT) to be applied in photovoltaic (PV) panel systems. These devices are distinguished by their capability to transform solar energy into electricity without emissions. Nevertheless, the efficiency can be enhanced provided that a suitable MPPT algorithm is well designed to obtain the maximum performance. From the analyzed MPPT algorithms, four different types were chosen for an experimental evaluation over a commercial PV system linked to a boost converter. As the reference that corresponds to the maximum power is depended on the irradiation and temperature, an artificial neural network (ANN) was used as a reference generator where a high accuracy was achieved based on real data. This was used as a tool for the implementation of sliding mode controller (SMC), fuzzy logic controller (FLC) and model predictive control (MPC). The outcomes allowed different conclusions where each controller has different advantages and disadvantages depending on the various factors related to hardware and software.

Stability of Interval Type-3 Fuzzy Controllers for Autonomous Vehicles

Economic efficient Autonomous Road Vehicles (ARVs) are invariably subjected to uncertainties and perturbations. Therefore, control of vehicle systems requires stability to withstand the effect of variations in the nominal performance. Lateral path-tracking is a substantial task of ARVs, especially in critical maneuvering and cornering with variable speed. In this study, a new controller on the basis of interval type-3 (T3) fuzzy logic system (FLSs) is designed. The main novelties and advantages are as follows. (1) The uncertainty is a main challenge in the path-following problem of ARVs. However, in the fuzzy-based approaches, the bounds of uncertainty are assumed to be known. However, in the our suggested approach, the bounds of uncertainties are also fuzzy sets and type-3 FLSs with online adaptation rules are suggested to handle the uncertainties. (2) The approximation errors (AEs) and perturbations are investigated and tackled by the compensators. (3) The bounds of estimation errors are also uncertain and are estimated by the suggested adaptation laws. (4) The stability is ensured under unknown dynamics, perturbations and critical maneuvers. (5) Comparison with the benchmarking techniques and conventional fuzzy approaches verifies that the suggested path-following scheme results in better maneuver performance.