Sampled-Data Control of Spacecraft Rendezvous with Discontinuous Lyapunov Approach

This paper investigates the sampled-data stabilization problem of spacecraft relative positional holding with improved Lyapunov function approach. The classical Clohessy-Wiltshire equation is adopted to describe the relative dynamic model. The relative position holding problem is converted into an output tracking control problem using sampling signals. A time-dependent discontinuous Lyapunov functionals approach is developed, which will lead to essentially less conservative results for the stability analysis and controller design of the corresponding closed-loop system. Sufficient conditions for the exponential stability analysis and the existence of the proposed controller are provided, respectively. Finally, a simulation result is established to illustrate the effectiveness of the proposed control scheme

Neural-Network-Based Adaptive Backstepping Control with Application to Spacecraft Attitude Regulation

Date of publication November 1, 2017This paper investigates the neural-network-based adaptive control problem for a class of continuous-time nonlinear systems with actuator faults and external disturbances. The model uncertainties in the system are not required to satisfy the norm-bounded assumption, and the exact information for components faults and external disturbance is totally unknown, which represents more general cases in practical systems. An indirect adaptive backstepping control strategy is proposed to cope with the stabilization problem, where the unknown nonlinearity is approximated by the adaptive neural-network scheme, and the loss of effectiveness of actuators faults and the norm bounds of exogenous disturbances are estimated via designed online adaptive updating laws. The developed adaptive backstepping control law can ensure the asymptotic stability of the fault closed-loop system despite of unknown nonlinear function, actuator faults, and disturbances. Finally, an application example based on spacecraft attitude regulation is provided to demonstrate the effectiveness and the potential of the developed new neural adaptive control approach.Xibin Cao, Peng Shi, Zhuoshi Li, and Ming Li

Observer-Based Stabilization of Spacecraft Rendezvous with Variable Sampling and Sensor Nonlinearity

This paper addresses the observer-based control problem of spacecraft rendezvous with nonuniform sampling period. The relative dynamic model is based on the classical Clohessy-Wiltshire equation, and sensor nonlinearity and sampling are considered together in a unified framework. The purpose of this paper is to perform an observer-based controller synthesis by using sampled and saturated output measurements, such that the resulting closed-loop system is exponentially stable. A time-dependent Lyapunov functional is developed which depends on time and the upper bound of the sampling period and also does not grow along the input update times. The controller design problem is solved in terms of the linear matrix inequality method, and the obtained results are less conservative than using the traditional Lyapunov functionals. Finally, a numerical simulation example is built to show the validity of the developed sampled-data control strategy

Diatom taxa and assemblages for establishing nutrient criteria of lakes with anthropogenic hydrologic alteration

Stressor-response models offer guidance for concentration-based nutrient criteria in lakes under human intervention. Diatom-based statistics from biological responses were incorporated to derive taxon-specific and community-level change points (thresholds) of phosphorous and nitrogen in 77 Yangtze floodplain lakes. Diatom metrics relating with conductivity were adopted as response variables, since conductivity explained the maximum variation (38.1%) in diatom assemblages via Bootstrapped regression trees. Nonparametric change-point analysis and Threshold Indicator Taxa ANalysis showed threshold responses of diatom community structure at 0.05-0.08 mg TP/L in connected lakes and 0.02-0.04 mgTP/L in isolated lakes. Distinct community change points of sensitive diatoms occurred at 0.96-1.63 mgTN/L in connected lakes and 0.52-0.63 mgTN/L in isolated lakes. Diatom community structures of tolerant taxa were substantially altered beyond 0.22-0.23 mg/L in connected lakes and 0.52-0.69 mg NOx/L in isolated lakes. Hydrological river-lake connectivity differed significantly in ecological nutrient criteria with more TN/TP criteria and less NOx criteria in connected lakes. Given the ecological significance and biological integrity, diatom-based statistics can provide more reliable change points (thresholds) for nutrient criteria than Chl alpha-nutrient relationships. (C) 2016 Elsevier Ltd. All rights reserved

CS2-Collector: A New Approach for Data Collection in Wireless Sensor Networks Based on Two-Dimensional Compressive Sensing

In this paper, we consider the problem of reconstructing the temporal and spatial profile of some physical phenomena monitored by large-scale Wireless Sensor Networks (WSNs) in an energy efficient manner. Compressive sensing is one of the popular choices to reduce the energy consumption of the data collection in WSNs. The existing solutions only consider sparsity of sensors’ data from either temporal or spatial dimensions. In this paper, we propose a novel data collection strategy, CS2-collector, for WSNs based on the theory of Two Dimensional Compressive Sensing (2DCS). It exploits both temporal and spatial sparsity, i.e., 2D-sparsity of WSNs and achieves significant gain on the tradeoff between the compression ratio and reconstruction accuracy as the numerical simulations and evaluations on different types of sensors’ data. More intuitively, with the same given energy budget, CS2-collector provides significantly more accurate reconstruction of the profile of the physical phenomena that are temporal-spatially sparse

Historical records of polycyclic aromatic hydrocarbon deposition in a shallow eutrophic lake: Impacts of sources and sedimentological conditions

Jedinice specijalnih snaga vojske osposobljene su za vođenje osjetljivih specijalnih operacija, uključujući nekonvencionalno ratovanje, protuterorizam, izravne akcije i strateške izviđačke misije. Mnoge jedinstvene vještine i sposobnosti koje posjeduju pripadnici u jedinicama specijalnih snaga imaju potencijalnu primjenu u operacijama domovinske sigurnosti. Specijalne snage čine posebno opremljene, uvježbane i organizirane manje jedinice koje nastupaju onda kada je problem previše kompleksan za konvencionalne snage. Pripadnici specijalnih snaga fizički moraju biti iznimno dobro pripremljeni kako bi mogli izdržati napore kojima su izloženi pri obavljanju svojih zadaća, kao i zbog lakšeg nošenja sa stresom. Pripadnik specijalnih snaga mora imati visoko razvijene funkcionalne sposobnosti, aerobne i anaerobne, mišićnu izdržljivost, snagu, brzinu i koordinaciju

High Bandwidth-Utilization Digital Holographic Reconstruction Using an Untrained Neural Network

Slightly off-axis digital holographic microscopy (DHM) is the extension of digital holography imaging technology toward high-throughput modern optical imaging technology. However, it is difficult for the method based on the conventional linear Fourier domain filtering to solve the imaging artifacts caused by the spectral aliasing problem. In this article, we propose a novel high-accuracy, artifacts-free, single-frame, digital holographic phase demodulation scheme for low-carrier-frequency holograms, which incorporates the physical model into a conventional deep neural network (DNN) without training beforehand based on a massive dataset. Although the conventional end-to-end deep learning (DL) method can achieve high-accuracy phase recovery directly from a single-frame hologram, the massive datasets and ground truth collection can be prohibitively laborious and time-consuming. Our method recognizes such a low-carrier frequency fringe demodulation process as a nonlinear optimization problem, which can reconstruct the artifact-free phase details gradually from a single-frame hologram. The phase resolution target and simulation experiment results quantitatively demonstrate that the proposed method possesses better artifact suppression and high-resolution imaging capabilities than the physical methods. In addition, the live-cell experiment also indicates the practicality of the technique in biological research