Recently, the importance of exploring the plausibility of renewable energy has been progressively increased, not only because of concerns over the shortage of current fossil fuels but also the consideration of sustainable development and the negative environmental impact caused by large scale use of fossil fuels. Among renewable sources, solar energy seems to be one of the promising energy sources for widespread application. Due to its inherent intermittency and fluctuation, one of the important research interests is to harness the maximum power possible from the solar energy falling on a panel. To this end, an efficient maximum power point tracker to harvest as much energy as possible is a key to improving the system's efficiency and performance. This paper presents a novel hybrid maximum power point tracking mechanism with adaptive perturbation size. The proposed method is implemented, analyzed, and evaluated in MATLAB/Simulink. Both numerical and experimental evaluation results prove that by using the proposed method, better tracking performance can be achieved and the power delivered at steady state can be increased by a factor of 7.31% compared with conventional methods.

This paper presents a review and analysis of current non-destructive failure detection methods of composite materials and a brief outline of the build of a bamboo bicycle which has been used as a development platform and test bed for the initial development of a novel and practical non-destructive failure detection solution, which has future compatibility for carbon-fibre (CF)-based bicycles. The paper begins by presenting the current market condition of composite materials and in particular, CF and CF-reinforced plastic, and then follows onto failure modes and proceeds to investigate a comprehensive range of failure detection methods.

This paper describes a nonlinear deterministic controller design for a helicopter with an underslung external load system. A robust control approach is considered for the control law development. The system is considered as a cascade connection of an uncertain nonlinear system. The controller is designed to ensure the stabilization of the helicopter system and the positioning of the underslung load at hover condition. Control analysis and numerical results show that the proposed controller is able to locate the load at the specified position or its neighbourhood.

This paper presents a review and analysis of a fuel cell system modelling and controller design for electric fuel cell vehicle applications. The paper begins by presenting the basic principal of PEM fuel cell dynamics. The work proceeds to investigate models and controller design techniques for fuel cell systems.

This paper investigates the analysis of the energy management system for a DC microgrid. The microgrid consists of a photovoltaic panel and a batteries system that is connected to the microgrid through a bidirectional power converter. The optimization problem is solved by the hybrid internal point method with the genetic algorithms method and particle swarm optimization (PSO) method, by considering forecasting demand and generation for all the elements of the microgrid. The analysis includes a comparison of energy optimization of the microgrid for solar radiation data from two areas of the world and a comparison the efficiency and effectiveness of optimization methods. The efficiency of the algorithm for energy optimization is verified and analyzed through experimental data. The results obtained show that the optimization algorithm can intelligently handle the energy flows to store the largest amount in the batteries and thus have the least amount of charge and discharge cycles for the battery and prolong the useful life.