Sliding mode control and power transformation

Dr. Yau proposed an effective maximum power point tracking method by integrating the sliding control theory with the incremental conductance. Most of the conventional feedback methods sought to find the maximum power point within the working area by means of numerical search. These methods lacked robustness and are susceptible to external disturbance. In contrast, Dr. Yau’s method provides an effective solution to the problem that the output of solar power systems may be affected by changes in the load of the solar cells. This method can improve the performance of the power supply and storage systems. The research result was published in the SCI journal Transactions of the Institute of Measurement and Control, 2011. Dr. Yau further extended the use of the method to the fuel cell system. Theories and experiments have validated the applicability of the method to the traditional fuel cell system to stabilize its power output by shielding the maximum power point tracking from the load fluctuation response. This result was published in the SCI journal Abstract and Applied Analysis, 2013. Moreover, Dr. Yau proposed an algorithm based on the extremum seeking control and combined it with the sliding control theory. Conventional algorithms encounter the problem of convergence on the partial maxima in the event of solar irradiance changes. The algorithm proposed by Dr. Yau solves this problem and enhances the robustness and stability of the system. The algorithm also suppresses the loss caused by high frequency switching and other components using the sliding mode control with a sliding layer in place of the gradient detector. Moreover, the PSO (Particle Swarm Optimization) algorithm was used to tune the parameters and the optimum values of the parameters were included in the outcomes of the simulation analysis and experiment. This result was published in the SCI journal International Journal of Photoenergy, 2013.