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This paper presents a robust adaptive control scheme for a class of continuous-time linear systems with unknown non-smooth asymmetrical deadzone nonlinearity at the input of the plant. The methodology is applied to handle input deadzone as well as unmeasurable disturbances simultaneously in strictly matched systems. The proposed controller robustly cancels any residual distortion caused by the inaccurate deadzone cancellation scheme. The scheme is shown to successfully cancel the deadzone's deleterious effect as well as eliminate other unmeasurable disturbances within the span of the input. The new controller ensures the global stability of all states and adaptations, and achieves asymptotic tracking. The asymptotic stability of the closed-loop system is proven by Lyapunov arguments, and simulation results confirm the efficacy of the control methodology.

Dust and impurity accumulation has a significant effect on the efficiency and performance of PV panel output power. It influences the transmittance of solar radiation from the PV panels surface. Scheduling weekly or monthly cleaning periods requires complete knowledge of area's weather and environmental condition. In this study, an experimental-based investigation is conducted aiming for a proper scheduling cleaning periods by comparing the output power efficiency of two identical PV panels, the first being cleaned daily and the other cleaned monthly. Both are exposed to unstable weather condition with Sarayat season in April and May, winter and summer Shamal of Kuwait for one year. The results indicated a significant degradation of PV panel output power in April, May, October and December. A need for frequent weekly water washing is a necessity to maintain the power efficiency loss of 15.07%, 13.74%, 10.685% and 8.742% respectively, and frequent monthly water washing for the remaining months of the year.

BackgroundThe free-space broadband frequency-modulated near-infrared (NIR) photon transmission and backscattering mode technique has been used in this paper as an optical biosensor method.PurposeThe purpose is to measure, identify, and extract the optical properties of different blood types.Patients and methodsThe method depends on the measurements of broadband frequencies ranging from 30 up to 1,000 MHz to predict two important parameters related to the incident-modulated signal. Blind samples collected from 30 patients were examined using the optical NIR transmission mode system, and an additional 40 blood samples from random patients were examined using the optical NIR reflection mode system. The study is divided into two stages: The first stage is dedicated to measuring the insertion loss and insertion phase over 30–1,000 MHz in a transmission mode to characterize the behavior of modulated photons as they interact with the blood samples. The second stage is dedicated to performing noninvasive backscattering measurements using the optical band developed to match the first stage results.ResultsIn this paper, we have created an indexed database using optical transmission mode measurements, and then mapped it to a reflection noninvasive measurement to identify the blood types. Then for the purpose of device accuracy, we randomly selected 480 new human subjects to measure the false-negative error percentage. This method is novel in terms of using an optical system to measure and identify blood types without collecting blood samples.ConclusionThe novel approach shows a highly accurate method in identifying different blood types instantaneously using optical sensing for both in vitro and in vivo procedures, thereby saving time and effort.

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