Fractional Chebyshev functional link neural network-optimization method for solving delay fractional optimal control problems with Atangana-Baleanu derivative

In this article, we propose a higher order neural network, namely the functional link neural network (FLNN), for the model of linear and nonlinear delay fractional optimal control problems (DFOCPs) with mixed control-state constraints. We consider DFOCPs using a new fractional derivative with nonlocal and nonsingular kernel that was recently proposed by Atangana and Baleanu. The derivative possesses more important characteristics that are very useful in modelling. In the proposed method, a fractional Chebyshev FLNN is developed. At the first step, the delay problem is transformed to a nondelay problem, using a Padé approximation. The necessary optimality condition is stated in a form of fractional two-point boundary value problem. By applying the fractional integration by parts and by constructing an error function, we then define an unconstrained minimization problem. In the optimization problem, trial solutions for state, co-state and control functions are utilized where these trial solutions are constructed by using single-layer fractional Chebyshev neural network model. We then minimize the error function using an unconstrained optimization scheme based on the gradient descent algorithm for updating the network parameters (weights and bias) associated with all neurons. To show the effectiveness of the proposed neural network, some numerical results are provided.     

Model predictive control of a collaborative manipulator considering dynamic obstacles

Collaborative robots have to adapt its motion plan to a dynamic environment and variation of task constraints. Currently, they detect collisions and interrupt or postpone their motion plan to prevent harm to humans or objects. The more advanced strategy proposed in this article uses online trajectory optimization to anticipate potential collisions, task variations, and to adapt the motion plan accordingly. The online trajectory planner pursues a model predictive control approach to account for dynamic motion objectives and constraints during task execution. The prediction model relates reference joint velocities to actual joint positions as an approximation of built-in robot tracking controllers. The optimal control problem is solved with direct collocation based on a hypergraph structure, which represents the nonlinear program and allows to efficiently adapt to structural changes in the optimization problem caused by moving obstacles. To demonstrate the effectiveness of the approach, the robot imitates pick-and-place tasks while avoiding self-collisions, semistatic, and dynamic obstacles, including a person. The analysis of the approach concerns computation time, constraint violations, and smoothness. It shows that after model identification, order reduction, and validation on the real robot, parallel integrators with compensation for input delays exhibit the best compromise between accuracy and computational complexity. The model predictive controller can successfully approach a moving target configuration without prior knowledge of the reference motion. The results show that pure hard constraints are not sufficient and lead to nonsmooth controls. In combination with soft constraints, which evaluate the proximity of obstacles, smooth and safe trajectories are planned.     

Adaptive optimal tracking control for multi-joint manipulator on space robot

This paper aims to address the tracking control problem for the multi-joint manipulator on a space robot subject to model uncertainties and external disturbances. A Gauss-Newton interactive optimization algorithm is used to obtain the desired joint angle for each joint. In order to formulate the optimization problem, the Denaait-Hartenberg (D-H) method is employed to describe the model of the multi-joint manipulator. Subsequently, an adaptive controller is developed to achieve tracking control, where controller parameters updated in real time are introduced to handle the nondeterminacy of the multi-joint manipulator. Moreover, a fuzzy control strategy is composed such that our designed controller is robust against the complex environment as well. The controller design is performed by means of the Lyapunov techniques. Meanwhile, its effectiveness is verified through numerical simulations. Finally, some concluding remarks close the paper.     

桡骨远端骨折锁定钢板刚度的拓扑优化研究

目的对桡骨远端骨折锁定钢板结构进行优化设计,以应对骨折内固定个性化刚度需求。方法运用三维建模和计算机辅助设计软件完成桡骨远端骨折模型和常规钢板的模型构建,基于初始有限元分析结果,以轴向刚度下调33.33%且保留扭转刚度的90.00%以上作为优化目标,对常规钢板进行拓扑优化和重设计;通过有限元分析计算,对比常规钢板和优化钢板在轴向压缩和扭转工况下的内固定刚度和产生的骨折区应变。结果所获得的优化钢板轴向刚度为636.5 N/mm,下调幅度为19.7%,基本接近既定的目标刚度,优化后的扭转刚度为634.12 Nmm/°,下调幅度为8.8%,并未超出既定的目标限值;而骨折区应变变化方面,轴向应变相比切向应变呈现出更为显著的增加趋势,与刚度调控效果基本一致。结论通过拓扑优化的方法从钢板结构层面进行重设计,可实现骨折愈合的个性化内固定刚度调控。     

磁外科理念能使疝与腹壁外科技术再优化

磁外科是一门新型的外科技术体系,按照临床应用及原理的不同可以将磁外科技术分为以下5类:磁压榨技术、磁导航技术、磁锚定技术、磁悬浮技术以及磁示踪技术。不同的磁外科技术以其独特的优势创新了多种新型外科诊断和治疗方法,同时也优化了众多传统的外科诊疗手段。目前,磁外科技术已经在管腔重建、组织牵引暴露以及病变追踪等领域应用并展现出了良好的应用前景。在疝和腹壁外科手术中,磁外科技术具备优化某些手术操作的潜质,如在腔镜疝修补手术中利用磁力导航可以使得疝补片术中移动和固定更灵活,磁力锚定可以使得腔镜手术更微创,磁力牵引可以使腹壁组织游离更便捷,而磁力吻合可以使得腹腔感染控制和减容更安全。     

Linear Wavefield Optimization Using a Modified Source

Recorded seismic data are sensitive to the Earth's elastic properties, and thus, they carry information of such properties in their waveforms. The sensitivity of such waveforms to the properties is nonlinear causing all kinds of difficulties to the inversion of such properties. Inverting directly for the components forming the wave equation, which includes the wave equation operator (or its perturbation), and the wavefield, as independent parameters enhances the convexity of the inverse problem. The optimization in this case is provided by an objective function that maximizes the data fitting and the wave equation fidelity, simultaneously. To enhance the practicality and efficiency of the optimization, I recast the velocity perturbations as secondary sources in a modified source function, and invert for the wavefield and the modified source function, as independent parameters. The optimization in this case corresponds to a linear problem. The inverted functions can be used directly to extract the velocity perturbation. Unlike gradient methods, this optimization problem is free of the Born approximation limitations in the update, including single scattering and cross talk that may arise for example in the case of multi sources. These specific features are shown for a simple synthetic example, as well as the Marmousi model.     

Flow disturbances generated by feeding and swimming zooplankton

Interactions between planktonic organisms, such as detection of prey, predators, and mates, are often mediated by fluid signals. Consequently, many plankton predators perceive their prey from the fluid disturbances that it generates when it feeds and swims. Zooplankton should therefore seek to minimize the fluid disturbance that they produce. By means of particle image velocimetry, we describe the fluid disturbances produced by feeding and swimming in zooplankton with diverse propulsion mechanisms and ranging from 10-µm flagellates to greater than millimeter-sized copepods. We show that zooplankton, in which feeding and swimming are separate processes, produce flow disturbances during swimming with a much faster spatial attenuation (velocity u varies with distance r as u ∝ r⁻³ to r⁻⁴) than that produced by zooplankton for which feeding and propulsion are the same process (u ∝ r⁻¹ to r⁻²). As a result, the spatial extension of the fluid disturbance produced by swimmers is an order of magnitude smaller than that produced by feeders at similar Reynolds numbers. The “quiet” propulsion of swimmers is achieved either through swimming erratically by short-lasting power strokes, generating viscous vortex rings, or by “breast-stroke swimming.” Both produce rapidly attenuating flows. The more “noisy” swimming of those that are constrained by a need to simultaneously feed is due to constantly beating flagella or appendages that are positioned either anteriorly or posteriorly on the (cell) body. These patterns transcend differences in size and taxonomy and have thus evolved multiple times, suggesting a strong selective pressure to minimize predation risk.Zooplankters move to feed, find food, and find mates, so moving is critical to the efficient execution of essential functions. However, moving comes at a predation risk: Swimming increases the predator encounter velocity (encounter rate increases with prey velocity to a power ≤1), and feeding and swimming generate fluid disturbances that may be perceived by rheotactic predators, thus increasing the predator’s detection distance (encounter rate increases with detection distance squared) (1–5). So, the advantages of moving and feeding must be traded off against the associated risks, and organisms should aim at moving and foraging in ways that reduce the predation risk and optimize the trade-off (6, 7). They may do so by moving in patterns that minimize encounter rates (8) and/or they may feed and propel themselves in ways that generate only small fluid disturbances (9). For example, theoretical models suggest that zooplankton that swim by a sequence of jumps may create a smaller fluid disturbance than similar-sized ones that swim smoothly (9), that a hovering zooplankter generates a larger fluid signal than one that cruises through the water (10, 11), and that a zooplankter moving at low Reynolds numbers will generate a relatively larger fluid signal than one moving at higher Reynolds numbers (11). Thus, motility patterns and propulsion modes may strongly influence predation risk and must be subject to strong selection pressure during evolution.Zooplankton span a huge taxonomic diversity and a large size range (from microns to centimeters) and their propulsion mechanisms vary substantially (12). Unicellular plankton may use one or more flagella or cilia, and the flagella may be smooth or plumose, which has implications for whether the cell is pulled or pushed by the beating flagellum (13). Ciliates may have the cilia rather evenly distributed on the cell surface or concentrated on certain parts of the cell, typically either anteriorly or as an equatorial band. Small animals may have an anterior “corona” of cilia (e.g., rotifers and many pelagic invertebrate larvae) to generate feeding currents and propulsion, or they may have beating or vibrating appendages that can be positioned anteriorly, ventrally, or laterally. The implications and potential adaptive value of this diversity of propulsion modes for feeding and survival are largely unexplored.Various idealized models, simplifying the swimming organisms to combinations of point forces acting on the water, have been used to describe the fluid disturbance generated by moving and feeding plankton. A self-propelled plankton is often described by a so-called stresslet (two oppositely directed point forces of equal magnitude), a hovering one by a stokeslet (a stationary point force), and a jumping animal by an impulsive stresslet (a stresslet working impulsively) (9, 11, 12). These highly idealized models yield very different predictions of the spatial attenuation of the fluid disturbance and, thus, of how far away the feeding and swimming animal can be detected. A few studies have compared observed flow patterns with those predicted from these simple models and in some cases found fair comparisons (4, 14–17). However, numerical simulations as well as observations of self-propelled microplankton have demonstrated that the distribution of propulsion forces, i.e., the position of flagella, cilia, or appendages on the (cell) body, may have a profound effect on the imposed fluid flow (18, 19). Also, most of the idealized models ignore the fact that swimming in most cases is unsteady, which leads to fluctuating flows at scales smaller than the Stokes length scale (ν/ω, where ν is the kinematic viscosity and ω is the beat frequency) (e.g., ref. 19). The simple, idealized models hitherto applied may be insufficient to represent the diverse propulsion modes observed in real organisms and to understand the associated trade-offs.Feeding and swimming are often part of the same process in zooplankton. Many zooplankton generate a feeding current that at the same time propels the animal through the water. In others, feeding and swimming are separate processes. For example, ambush feeding “sit-and-wait” zooplankters do not move as part of feeding but may swim to undertake vertical migration or to search for mates or patches of elevated food availability. Also, many of the plankton that generate a feeding current by vibrating appendages may in addition swim by using the same appendages in a different way (e.g., the nauplius larvae of most crustaceans) or by using other swimming appendages dedicated to propel themselves (most pelagic copepods and cladocerans).Whereas feeding and swimming may both compromise the survival of the organism, the trade-offs may be different. To get sufficient food, zooplankters need to daily clear a volume of water for prey that corresponds to about 10⁶ times their own body volume (20, 21) and hence, implicit in the feeding process is the need to examine or process large volumes of water. In contrast, dedicated swimming should translate the organism through the water as quietly as possible. Thus, we hypothesize that in microplankton, dedicated swimming produces flow fields that attenuate more readily and/or have a smaller spatial extension than the cases in which feeding and propulsion are intimately related.In this study we use particle image velocimetry (PIV) to describe the flow fields generated by micron- to millimeter-sized feeding and swimming zooplankton that use a variety of propulsion modes. We show that—across taxa and sizes—dedicated swimming produces flow fields with a much smaller spatial extension and a faster spatial attenuation than those produced by the plankton for which feeding and swimming are integrated, and we characterize the propulsion modes that minimize susceptibility to rheotactic predators.     

A cellular solution to an information-processing problem

Signaling receptors on the cell surface are mobile and have evolved to efficiently sense and process mechanical or chemical information. We pose the problem of identifying the optimal strategy for placing a collection of distributed and mobile sensors to faithfully estimate a signal that varies in space and time. The optimal strategy has to balance two opposing objectives: the need to locally assemble sensors to reduce estimation noise and the need to spread them to reduce spatial error. This results in a phase transition in the space of strategies as a function of sensor density and efficiency. We show that these optimal strategies have been arrived at multiple times in diverse cell biology contexts, including the stationary lattice architecture of receptors on the bacterial cell surface and the active clustering of cell-surface signaling receptors in metazoan cells.The molecular characteristics of signaling receptors and their spatiotemporal organization have evolved to optimize different facets of information processing at the cell surface. A canonical information-processing problem involves designing strategies for a collection of distributed, noisy, mobile sensors to faithfully estimate a signal or function that varies in space and time (1). This problem appears naturally in many contexts, biological and nonbiological: (i) chemoattractant protein sensors on the bacteria cell surface (2, 3); (ii) galectin-glycoprotein assemblies designed for effective immune response on the surface of metazoan cells (4, 5); (iii) ligand-activated signaling protein receptors on the surface of eukaryotic cells (6–10); (iv) coclustering of integrin receptors to faithfully read and discriminate the rigidity and chemistry of a substrate (11); (v) clustering of e-cadherin receptors for effective adherence at cell–cell junctions (12); and even (vi) radio frequency (RF) sensor networks monitoring the environment or mobile targets (13). In the signal-processing community, this problem is known as data fusion or more generally information fusion (14, 15); however typical applications do not consider mobile sensors.In this paper we show how biology has, on multiple occasions, arrived at a solution to this optimization problem. The optimal solution needs to balance two opposing objectives, the need to locally assemble sensors to reduce estimation noise and the need to spread them out for broader spatial coverage. We show that in the space of strategies, this leads to a phase transition as a function of sensor density, sensor characteristics, and function properties. At very low sensor density, the optimal design corresponds to freely diffusing sensors. For sensor density above a threshold, there are two different optimal solutions as a function of a dimensionless parameter constructed from the sensor advection velocity and the correlation length and time of the incident signal. One optimal solution is that the sensors are static and located on a regular lattice grid. This is the strategy used in bacteria, such as Escherichia coli, to organize their chemoattractant receptors in a regular lattice array (3, 16), and in metazoan cells, where galectin-glycoproteins are organized in a lattice on the cell surface to effect an optimal immune response (4, 5). To realize this strategy, the cell needs to provide a rigid cortical scaffold that holds the receptors in place. Another optimal solution is to make the receptors mobile in such a way that a fraction of them form multiparticle nanoclusters, which then break up and reform randomly, the rest being uniformly distributed. Recent studies on the steady-state distribution of several cell-surface proteins reveal a stereotypical distribution of a fixed fraction of monomers and dynamic nanoclusters (6–9), and our information theoretic perspective could provide a general explanation for this. To realize this dynamic strategy, the cell surface needed to be relieved of the constraints imposed by the rigid scaffold and to be more regulatable. This strategy change needed the innovation of motor proteins and dynamic actin filaments, a regulated actomyosin machinery fueled by ATP, and a coupling of components of the cell surface to this cortical dynamic actin (17).     

基于CT影像的人体踝关节三维重建

以踝关节的生理解剖结构为理论依据,利用踝关节的CT图像作为二维数据源,通过医学图像处理软件Mimics建立踝关节的三维模型,然后使用3-matic对三维模型的网格进行优化,最后对优化前后的模型进行对比分析。结果发现经过优化后的踝关节三维模型在结构上与人体真实的踝关节结构并无明显的差异,精确程度满足要求,对于患者病情的分析及治疗方案的确立具有重要的指导意义。     

经络协调疗法治疗常见精神病临床观察研究

采用JXZ-1型经络协调诊疗系统测试手足井穴、会穴(奇经八脉)的热敏感度,了解经络平衡状态,判断经络失衡的虚实程度,确定病经,向病经穴位输入负反馈信息,进行虚补实泻,调节经络平衡状态,以达到治疗疾病的目的.以此法对391例精神病患者进行临床诊断治疗,其显效率为70%.取得了客观化数字化表达的良好效果.