Hongchun Shu

Passivity-based fractional-order sliding-mode control design and implementation of grid-connected photovoltaic systems

In order to achieve the maximum power point tracking of photovoltaic (PV) systems in the presence of time-varying stochastic operation conditions and various uncertainties/disturbances, a passivity-based fractional-order sliding-mode control (PbFoSMC) scheme is proposed. The design can be classified into two steps, i.e., (a) construct a storage function in terms of the tracking error of DC-link voltage, DC-link current, and q-axis current for the PV system, upon which the actual characteristics of each term is thoroughly analyzed. Moreover, the beneficial terms are carefully retained to enhance the dynamical responses of the closed-loop system while the detrimental terms are fully removed to realize a global control consistency; (b) based on the passivized system, a fractional-order sliding-mode control (FoSMC) is incorporated as an additional input, which can considerably improve the control performance with the aim of rapid uncertainties/disturbances rejection. Four case studies, including the solar irradiance change, temperature variation, power grid voltage drop, and PV inverter parameter uncertainties, are undertaken to evaluate the effectiveness of PbFoSMC in comparison to that of proportional-integral-derivative control, passivity-based control, and sliding-mode control (SMC), respectively. At last, a dSpace based hardware-in-loop test is carried out to validate the implementation feasibility of PbFoSMC.In order to achieve the maximum power point tracking of photovoltaic (PV) systems in the presence of time-varying stochastic operation conditions and various uncertainties/disturbances, a passivity-based fractional-order sliding-mode control (PbFoSMC) scheme is proposed. The design can be classified into two steps, i.e., (a) construct a storage function in terms of the tracking error of DC-link voltage, DC-link current, and q-axis current for the PV system, upon which the actual characteristics of each term is thoroughly analyzed. Moreover, the beneficial terms are carefully retained to enhance the dynamical responses of the closed-loop system while the detrimental terms are fully removed to realize a global control consistency; (b) based on the passivized system, a fractional-order sliding-mode control (FoSMC) is incorporated as an additional input, which can considerably improve the control performance with the aim of rapid uncertainties/disturbances rejection. Four case studies, including the solar irr...

A Bayesian Network Method for Quantitative Evaluation of Defects in Multilayered Structures from Eddy Current NDT Signals

Accurate evaluation and characterization of defects in multilayered structures from eddy current nondestructive testing (NDT) signals are a difficult inverse problem. There is scope for improving the current methods used for solving the inverse problem by incorporating information of uncertainty in the inspection process. Here, we propose to evaluate defects quantitatively from eddy current NDT signals using Bayesian networks (BNs). BNs are a useful method in handling uncertainty in the inspection process, eventually leading to the more accurate results. The domain knowledge and the experimental data are used to generate the BN models. The models are applied to predict the signals corresponding to different defect characteristic parameters or to estimate defect characteristic parameters from eddy current signals in real time. Finally, the estimation results are analyzed. Compared to the least squares regression method, BNs are more robust with higher accuracy and have the advantage of being a bidirectional inferential mechanism. This approach allows results to be obtained in the form of full marginal conditional probability distributions, providing more information on the defect. The feasibility of BNs presented and discussed in this paper has been validated.