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The purpose of this paper is to design and develop an IR and sprinkler based embedded controller operated robotic arm for automatic dust removal system to mitigate the dust effect on the solar panel surface, since dust accumulation normally affected by real weather conditions is one of the serious concern for the deterioration of photovoltaic (PV) system output.

The system is a wet cleaning device which provides a cheap silicon rubber-based wiping operation controlled by the pulse width modulation-operated motors of robotic arm. The IEEE 1149.1-compliant mixed signal-embedded platform of C8051F226DK is involved to command the complete system.

A prototype of 30 W_P system is capable of producing an inspiring average value of 11.26 per cent in energy increase, 13.63 per cent in PV module efficiency and 85.20 per cent in performance ratio of the system after 73 days of cleaning in summer season. In addition, a total of 1,617.93 W power; 1,0516.55 Wh energy; and 350.55 KWh/KW_P final yield was found during the entire cleaning period.

A novel technique of the implementation of IR sensor and sprinkler in dust mitigation is proposed in this paper. The IR sensor is used as a versatile object which can manage the robotic arm setting and control the automatic switching between cleaning and charging, as well as identify the thermal condition of solar panel for overheating.

This paper aims to determine the optimal preview length for the preview state feedback controller and to design the static preview gains for the controller.

The design methodology is based on LMI formulations and Bisection Approach to determine the optimal preview length for the preview state feedback controller that achieves robust H∞ performance. The determination of the optimal preview length is such that the performance of the optimized controller is similar (within bounds) to the maximum length controller, in terms of transient and frequency response along with the H∞ performance.

The proposed algorithm is implemented for two benchmark design examples that verify its ability and applicability. The results show that the optimal preview length controller designed using the proposed method performs similar to the maximum length preview controller (within bounds) and better than reported in literature.

The paper discusses the novel algorithm formulation and its proof as no such method is available to determine the optimal preview length.