DC-DC power converters such as buck converters are susceptible to degradation and failure due to operating under conditions of electrical stress and variable power sources in power conversion applications, such as electric vehicles and renewable energy. Some key components such as electrolytic capacitors degrade over time due to evaporation of the electrolyte. In this paper, a model-observer based scheme is proposed to monitor the states of Buck converters and to estimate their component parameters, such as capacitance and inductance. First, a diagnosis observer is proposed, and the generated residual vectors are applied for fault detection and isolation. Second, component condition parameters, such as capacitance and inductance are reconstructed using another novel observer with adaptive feedback law. Additionally, the observer structures and their theoretical performance are analyzed and proven. In contrast to existing reliability approaches applied in buck converters, the proposed scheme performs online-estimation for key parameters. Finally, buck converters in conventional dc-dc step-down and photovoltaic applications are investigated to test and validate the effectiveness of the proposed scheme in both simulation and laboratory experiments. Results demonstrate the feasibility, performance, and superiority of the proposed component parameter estimation scheme.

Being reliant on Air Conditioning (AC) throughout the majority of the year, desert countries with extremely hot weather conditions such as Qatar are facing challenges in lowering weariness cost due to AC On-Off switching while maintaining an adequate level of comfort under a wide-range of ambient temperature variations. To address these challenges, this paper investigates an optimal On-Off control strategy to improve the AC utilization process. To overcome complexities of online optimization, a Elman Neural Networks (NN)-based estimator is proposed to estimate real values of the outdoor temperature, and make off-line optimization available. By looking up the optimum values solved from an off-line optimization scheme, the proposed control solutions can adaptively regulate the indoor temperature regardless of outdoor temperature variations. In addition, a cost function of multiple objectives, which consider both Coefficient of Performance (COP), and AC compressor weariness due to On-Off switching, is designed for the optimization target of minimum cost. Unlike conventional On-Off control methodologies, the proposed On-Off control technique can respond adaptively to match large-range (up to 20 ${}^{\circ }$ C) ambient temperature variations while overcoming the drawbacks of long-time online optimization due to heavy computational load. Finally, the Elman NN based outdoor temperature estimator is validated with an acceptable accuracy and various validations for AC control optimization under Qatar’s real outdoor temperature conditions, which include three hot seasons, are conducted and analyzed. The results demonstrate the effectiveness and robustness of the proposed optimal On-Off control solution.

A systematic fault tolerant control (FTC) scheme based on fault estimation for a quadrotor actuator, which integrates normal control, active and passive FTC and fault parking is proposed in this paper. Firstly, an adaptive Thau observer (ATO) is presented to estimate the quadrotor rotor fault magnitudes, and then faults with different magnitudes and time-varying natures are rated into corresponding fault severity levels based on the pre-defined fault-tolerant boundaries. Secondly, a systematic FTC strategy which can coordinate various FTC methods is designed to compensate for failures depending on the fault types and severity levels. Unlike former stand-alone passive FTC or active FTC, our proposed FTC scheme can compensate for faults in a way of condition-based maintenance (CBM), and especially consider the fatal failures that traditional FTC techniques cannot accommodate to avoid the crashing of UAVs. Finally, various simulations are carried out to show the performance and effectiveness of the proposed method