A design of linear matrix inequality (LMI)-based fractional-order surface for sliding-mode controller of a class of uncertain fractional-order nonlinear systems (FO-NSs) is proposed in this paper. A new switching law is achieved guaranteeing the reachability condition. This control law is established to obtain a sliding-mode controller (SMC) capable of deriving the state trajectories onto the fractional-order integral switching surface and maintain the sliding motion. Using LMIs, a sufficient condition for existence of the sliding surface is derived which ensures the $t−α$ asymptotical stability on the sliding surface. Through a numerical example, the superior performance of the new fractional-order sliding mode controller is illustrated in comparison with a previously proposed method.

Aerospace has become an indispensable part of exploring the universe. To guarantee the safety of the materials on aerospace, the recognition and the detection of hypervelocity impact (HVI) damage is needed. Processing bottlenecks and the lack of precision acquisition tools have restricted detection to the HVI damage of space debris for on-orbit spacecraft. This paper proposes an optimal multi-target image segmentation based feature extraction method to detect the HVI damage. For the collected infrared data, an improved mean shift clustering algorithm is given to adaptively classify the temperature change characteristics in the sampled data of the infrared video stream and reconstruct the image to obtain the infrared reconstruction image reflecting the damage characteristics. Moreover, a multi-objective optimization segmentation model is proposed to segment the defects of infrared reconstructed images to further extract the geometric shape, depth and other features of various defects. To obtain accurate segmentation results of the infrared reconstructed thermal images, the segmentation objective functions are set with respect to noise elimination and detail reservation. A weight vectors adjustment algorithm is developed to further improve the accuracy of damage segmentation in the multi-objective optimization segmentation model, to derive better balance between detail retention and noise removal. The experimental results of the algorithm verify the effectiveness and benefits of the proposed method.

This article proposes a real-time light-energy saving control technique to reduce unnecessary light-energy consumption (LEC) for varying lighting environment, through regulating brightness of illuminative lamps while providing the expect illumination level. Considering the influence of environmental conditions, a fractional-order Newton-based extremum seeking control (ESC) method in the proposed technique is developed to enhance the tracking accuracy and convergence speed. It can result in the high efficient lighting system and the rapid track of minimum LEC. Moreover, it significantly reduces the impact of selecting an arbitrary Hessian matrix on tracking speed of the algorithm, which is the main drawback in the most conventional ESC algorithms. Experimental results reveal that the proposed method has the ability to track the available minimum LEC under changing environmental conditions.

As the number of space debris has increased rapidly in recent years, it poses a major threat to the safety of spacecraft in space, and damage assessment for space debris hypervelocity impact is very important. In order to more comprehensively and accurately describe the damage defects in the infrared inspection data collected by infrared thermal imaging technology, this paper proposes an ultra-high-speed impact damage detection algorithm based on infrared reconstruction image fusion. The algorithm first preprocesses the obtained infrared thermal response image sequence and separates the damage features, and then applies a multi-objective evolutionary optimization algorithm to extract the typical transient thermal response, and then reconstructs the feature infrared images. Finally, image fusion based on guided filtering is performed on the damage reconstruction infrared images. In this paper, several reconstruction images that represent different types of impact damage defect are merged together to improve the detection ability of the algorithm. Infrared detection experiments on damaged specimens obtained from actual hypervelocity impacts verify the effectiveness of the proposed algorithm.