基于最小方差的声线跟踪自适应分层算法

针对高精度水声定位系统中定位精度与计算量相互矛盾的问题,提出了基于最小方差的声线跟踪自适应分层算法。该算法根据声速在有限范围内规律变化的特点,对声速剖面全局搜索,通过各段声速散点到其拟合直线的总方差表示拟切分段与原始声速剖面的差别,利用最大差别找出最佳切分点,保留原始声速剖面特征,实现对声速剖面的简化。实验结果表明,该算法在保证定位精度的同时能够提高计算效率,具有良好的工程应用价值。     

Stabilisation of stochastic differential equations driven by G-Brownian motion via aperiodically intermittent control

ABSTRACT

As an emerging field, the G-Itô stochastic calculus plays an important role in describing the model uncertainty. Many interesting works have been done on stochastic differential equations driven by G-Brownian motion (G-SDEs). Among the theories and applications of G-SDEs, the stability is the vital important one. In this paper, we investigate the stabilisation for G-SDEs based on G-Lyapunov function and aperiodically adaptive intermittent controller. As an application, the sufficient conditions are established for the stabilisation of stochastic Cohen–Grossberg neural networks driven by G-Brownian motion (G-SCGNNs). Finally, an example is provided to illustrate the obtained results.     

宽带数字接收机IQ不平衡估计与自适应补偿算法

针对宽带调制解调技术中广泛存在的IQ不平衡问题,在IQ不平衡模型及补偿原理的分析基础上提出了一种宽带数字接收机IQ不平衡估计与自适应补偿算法。首先利用解调数据对IQ不平衡参数进行实时估计,然后利用估计参数对接收信号进行自适应补偿。实验结果表明,所提算法可以有效解决宽带调制解调系统中普遍存在的IQ不平衡问题,提升系统误码性能。     

Design and analysis adaptivity in multiresolution topology optimization

Multiresolution topology optimization (MTO) methods involve decoupling of the design and analysis discretizations, such that a high-resolution design can be obtained at relatively low analysis costs. Recent studies have shown that the MTO method can be approximately 3 and 30 times faster than the traditional topology optimization method for two-dimensional (2D) and three-dimensional (3D) problems, respectively. To further exploit the potential of decoupling analysis and design, we propose a dp-adaptive MTO method, which involves locally increasing/decreasing the polynomial degree of the shape functions (p) and the design resolution (d). The adaptive refinement/coarsening is performed using a composite refinement indicator that includes criteria based on analysis error, presence of intermediate densities, as well as the occurrence of design artifacts referred to as QR-patterns. While standard MTO must rely on filtering to suppress QR-patterns, the proposed adaptive method ensures efficiently that these artifacts are suppressed in the final design, without sacrificing the design resolution. The applicability of the dp-adaptive MTO method is demonstrated on several 2D mechanical design problems. For all the cases, significant speedups in computational time are obtained. In particular for design problems involving low material volume fractions, speedups of up to a factor of 10 can be obtained over the conventional MTO method.     

Effects of Different Short-Term UV-B Radiation Intensities on Metabolic Characteristics of Porphyra haitanensis

The effects of ultraviolet (UV) radiation, particularly UV-B on algae, have become an important issue as human-caused depletion of the protecting ozone layer has been reported. In this study, the effects of different short-term UV-B radiation on the growth, physiology, and metabolism of Porphyra haitanensis were examined. The growth of P. haitanensis decreased, and the bleaching phenomenon occurred in the thalli. The contents of total amino acids, soluble sugar, total protein, and mycosporine-like amino acids (MAAs) increased under different UV-B radiation intensities. The metabolic profiles of P. haitanensis differed between the control and UV-B radiation-treated groups. Most of the differential metabolites in P. haitanensis were significantly upregulated under UV-B exposure. Short-term enhanced UV-B irradiation significantly affected amino acid metabolism, carbohydrate metabolism, glutathione metabolism, and phenylpropane biosynthesis. The contents of phenylalanine, tyrosine, threonine, and serine were increased, suggesting that amino acid metabolism can promote the synthesis of UV-absorbing substances (such as phenols and MAAs) by providing precursor substances. The contents of sucrose, D-glucose-6-phosphate, and beta-D-fructose-6-phosphate were increased, suggesting that carbohydrate metabolism contributes to maintain energy supply for metabolic activity in response to UV-B exposure. Meanwhile, dehydroascorbic acid (DHA) was also significantly upregulated, denoting effective activation of the antioxidant system. To some extent, these results provide metabolic insights into the adaptive response mechanism of P. haitanensis to short-term enhanced UV-B radiation.     

自适应融合层级特征的混合退化图像复原算法

多种退化类型混合的图像比单一类型的退化图像降质更严重,很难建立精确模型对其复原,研究端到端的神经网络算法是复原的关键.现有的基于操作选择注意力网络的算法(operation-wiseattentionnetwork,OWAN)虽然有一定的性能提升,但是其网络过于复杂,运行较慢,复原图像缺乏高频细节,整体效果也有提升的空间.针对这些问题,提出一种基于层级特征融合的自适应复原算法.该算法直接融合不同感受野分支的特征,增强复原图像的结构;用注意力机制对不同层级的特征进行动态融合,增加模型的自适应性,降低了模型冗余;另外,结合L1损失和感知损失,增强了复原图像的视觉感知效果.在DIV2K,BSD500等数据集上的实验结果表明,该算法无论是在峰值信噪比和结构相似性上的定量分析,还是在主观视觉质量方面,均优于OWAN算法,充分证明了该算法的有效性.     

Adaptive compensation of persistent actuator failures of nonlinear systems

In this article, adaptive compensation designs are developed for nonlinear systems with uncertainties from the system functions and persistent actuator failures of characterizations that (i) some unknown system inputs are stuck at some unknown fixed or varying values at unknown time instants and (ii) the failure pattern always switches from one to another and the switching does not stop. Such a controlled plant is described by an uncertain time-varying nonlinear system, and some robust adaptive feedback linearization based failure compensation results are studied for closed-loop system stabilization and bounded output tracking for some specific conditions. To improve the tracking performance in the presence of persistent actuator failures, a new adaptive control scheme is developed, using the failure indicator function which contains the failure pattern and failure time in the formulation. Detailed stability and tracking performance are shown. Simulation results are shown to verify the effectiveness of the proposed adaptive actuator failure compensation method.     

Adaptive finite-time tracking control for parameterized nonlinear systems with full state constraints

In this article, the issue of adaptive finite-time dynamic surface control (DSC) is discussed for a class of parameterized nonlinear systems with full state constraints. Using the property of logarithmic function, a one-to-one nonlinear mapping is constructed to transform a constrained system into an unconstrained system with the same structure. The nonlinear filter is constructed to replace the first-order linear filter in the traditional DSC, and the demand on the filter time constant is reduced. Based on finite-time stable theory and using modified DSC, the finite-time controller is designed via DSC. Theoretical analysis shows that all the signals in the closed-loop system are semiglobal practical finite-time stable. Furthermore, none of the states are outside the defined open set. In the end, simulation results are presented to demonstrate the effectiveness of the proposed control schemes with both linear filters and nonlinear filters.     

Adaptive actuator failure compensation for cooperative robotic manipulators with parameter uncertainties

This article develops a new framework of adaptive actuator failure compensation control for cooperative manipulator systems with parameter uncertainties in addition to actuator failures, and designs and analyzes effective actuator failure compensation schemes for such robotic systems. The new adaptive control design uses an integration of multiple individual failure compensators and direct adaptation to handle various types of uncertainties in such robotic systems. The design can also be used for concurrent actuator failure cases, to expand the capability of adaptive actuator failure compensation. With a complete proof and performance analysis, it is shown that the proposed control scheme guarantees the desired closed-loop stability and asymptotic output tracking, despite actuator failures whose patterns, time instants and values are all unknown. Simulation results of a benchmark cooperative manipulator system are presented to verify the desired control performance of the system with both typical constant and square-wave actuator failure signals.     

Adaptive constraint control for flexible manipulator systems modeled by partial differential equations with dead-zone input

In this article, based on partial differential equations (PDEs), the flexible manipulator system with both dead-zone input and state constraints is studied. The dynamic model of the flexible manipulator system is described by PDEs. The parameters of the dead-zone input are unknown, and the state constraint problem is also considered. An adaptive approach is proposed to offset the effects caused by dead-zone input. Thus, to guarantee that all states remain within their respective constraint regions, the boundary control law based on the barrier Lyapunov function is given, and an adaptive controller is designed. According to the Lyapunov analysis method, the control method is given to ensure that all signals of the closed-loop system are bounded and all states satisfy the constraint conditions. Finally, simulation results show the effectiveness of the proposed control method in this article.