This article explores an adaptive robust control scheme for satellite formation-containment flying in a way of constraint following. For safe flight and uncertainty suppression, both collision avoidance and uncertainty suppression are addressed. First, for uncertainty suppression, (possibly fast) time-varying but bounded uncertainty is considered, and then an adaptive law is proposed to estimate the comprehensive uncertainty bounds online. Second, the problem of formation-containment control with collision avoidance is converted into another problem of constraint-following control by taking the objectives of collision avoidance, formation, and containment, respectively, as the collision-avoidance constraint, formation constraint, and containment constraint. Third, an η -measure is introduced to gauge the constraint-following error, and then an adaptive robust control is proposed to render the error to be uniformly bounded and uniformly ultimately bounded, regardless of the uncertainty. By this, the satellites can follow the above collision-avoidance constraint, formation constraint, and containment constraint approximately. As a result, satellite formation-containment control emphasis on collision avoidance and uncertainty suppression is achieved.
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http://dx.doi.org/10.1109/TCYB.2022.3173683 | DOI Listing |
Mass Spectrom (Tokyo)
December 2024
Department of Applied Chemistry for Environment, School of Science and Technology, Kwansei Gakuin University, Gakuen-Uegahara-1, Sanda, Hyogo 669-1330, Japan.
A simple and rapid analytical method was developed for the simultaneous determination of two chromium species, Cr(III) and Cr(VI), in the environmental waters by high-performance liquid chromatography-inductively coupled plasma-mass spectrometry (HPLC-ICP-MS). This study incorporated a chelating pretreatment with 2,6-pyridinedicarboxylic acid (PDCA) to convert Cr(III) species into a stable Cr(III)-PDCA anion complex, which was then separated from Cr(VI) oxyanion using an anion exchange column. Building on the fundamental analytical approach proposed by Shigeta .
View Article and Find Full Text PDFAppl Ergon
December 2024
Ageing Futures Institute, University of New South Wales, Sydney, NSW, Australia; School of Optometry and Vision Science, University of New South Wales, Sydney, NSW, Australia.
Background: Fall injuries resulting from trips are a major health concern. Virtual reality (VR) offers an effective way of training obstacle avoidance while walking due to its ability to provide safe and meaningful real-time feedback during rehabilitation. This proof-of-concept study examined the benefit of providing physical feedback during obstacle avoidance gait training using VR.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Electrical and Photonics Engineering Automation and Control, Technical University of Denmark, Elektrovej, 2800 Kongens Lyngby, Denmark.
Obstacle contact detection is not commonly employed in autonomous robots, which mainly depend on avoidance algorithms, limiting their effectiveness in cluttered environments. Current contact-detection techniques suffer from blind spots or discretized detection points, and rigid platforms further limit performance by merely detecting the presence of a collision without providing detailed feedback. To address these challenges, we propose an innovative contact sensor design that improves autonomous navigation through physical contact detection.
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December 2024
College of Computer and Information Science, Southwest University, Chongqing 400715, China.
In this paper, we propose an algorithm based on the Rapidly-exploring Random Trees* (RRT*) algorithm for the path planning of mobile robots under kinematic constraints, aiming to generate efficient and smooth paths quickly. Compared to other algorithms, the main contributions of our proposed algorithm are as follows: First, we introduce a bidirectional expansion strategy that quickly identifies a direct path to the goal point in a short time. Second, a node reconnection strategy is used to eliminate unnecessary nodes, thereby reducing the path length and saving memory.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Faculty of Engineering and Applied Sciences, Cranfield University, College Road, Bedford MK43 0AL, UK.
The use of drones or Unmanned Aerial Vehicles (UAVs) and other flying vehicles has increased exponentially in the last decade. These devices pose a serious threat to helicopter pilots who constantly seek to maintain situational awareness while flying to avoid objects that might lead to a collision. In this paper, an Airborne Visual Artificial Intelligence System is proposed that seeks to improve helicopter pilots' situational awareness (SA) under UAV-congested environments.
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