Quantized-states-based adaptive control against unknown slippage effects of uncertain mobile robots with input and state quantization

An adaptive tracking design strategy based on quantized state feedback is developed for uncertain nonholonomic mobile robots with unknown wheel slippage effects. All state variables and control torques are assumed to be quantized by the state and input quantizers, respectively, in a network control environment. Thus, the quantized state feedback information is only available for the tracking control design. An approximation-based adaptive controller using quantized states is recursively designed to ensure the robust adaptive tracking against unknown wheel slippage effects where the quantized-states-based adaptive mechanism is derived to compensate for unknown wheel slippage effects, system nonlinearities, and quantization errors. The boundedness of the quantization errors and estimated parameters in the closed-loop system is analyzed by presenting some theoretical lemmas. Based on these lemmas, we prove the uniform ultimate boundedness of closed-loop signals and the convergence of the trajectory tracking error in the presence of wheel slippage effects. Simulations verify the effectiveness of the resulting tracking scheme.     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

基于贝叶斯参数优化的无模型自适应硅单晶直径控制

直拉硅单晶的生长过程涉及多场多相耦合与复杂的物理化学变化,其中工艺参数的波动是导致晶体直径不均匀的重要原因,如何实现工艺参数的控制以获得理想的、均匀的晶体直径具有重要的研究意义。本文分析现有控制方法存在不稳定以及控制效果不佳的问题后,提出基于贝叶斯参数优化的无模型自适应控制模型来控制硅单晶生长过程中的晶体直径。首先以坩埚上升速度与加热器的功率作为控制输入参数,晶体直径作为输出,搭建无模型自适应控制模型,并分析算法的稳定性。其次将控制模型进行仿真实验,发现硅单晶直径控制模型中不同的超参数设定会影响控制过程的迭代次数以及控制效果。最后,利用贝叶斯优化超参数的取值范围,并进行最终的仿真实验,结果表明,经贝叶斯参数优化后的控制模型计算快、迭代次数少,输出的晶体直径稳定,同时将生长工艺参数控制在实际生产要求范围内。因此,基于贝叶斯参数优化的无模型自适应控制实现了硅单晶直径均匀稳定的有效控制,具有结合工程背景的实际应用前景。     

A control volume finite element method for three-dimensional three-phase flows

A novel control volume finite element method with adaptive anisotropic unstructured meshes is presented for three-dimensional three-phase flows with interfacial tension. The numerical framework consists of a mixed control volume and finite element formulation with a new P₁DG-P₂ elements (linear discontinuous velocity between elements and quadratic continuous pressure between elements). A “volume of fluid” type method is used for the interface capturing, which is based on compressive control volume advection and second-order finite element methods. A force-balanced continuum surface force model is employed for the interfacial tension on unstructured meshes. The interfacial tension coefficient decomposition method is also used to deal with interfacial tension pairings between different phases. Numerical examples of benchmark tests and the dynamics of three-dimensional three-phase rising bubble, and droplet impact are presented. The results are compared with the analytical solutions and previously published experimental data, demonstrating the capability of the present method.     

Two-Photon Absorption Enhancement by the Inclusion of a Tropone Ring in Distorted Nanographene Ribbons

A new family of distorted ribbon-shaped nanographenes was designed, synthesized, and their optical and electrochemical properties were evaluated, pointing out an unprecedented correlation between their structural characteristics and the two-photon absorption (TPA) responses and electrochemical band gaps. Three nanographene ribbons have been prepared: a seven-membered-ring-containing nanographene presenting a tropone moiety at the edge, its full-carbon analogue, and a purely hexagonal one. We have found that the TPA cross-sections and the electrochemical band gaps of the seven-membered-ring-containing compounds are higher and lower, respectively, than those of the fully hexagonal polycyclic aromatic hydrocarbon (PAH). Interestingly, the inclusion of additional curvature has a positive effect in terms of non-linear optical properties of those ribbons.     

原子分子光子系统的耗散相互作用和退相干

原子分子系统与量子化的电磁场或光子模式耦合的系统是非相对论量子力学理论研究和实验研究的主要对象和模型. 现实系统必然与外界环境耦合，且即便原子隔绝较好、光学腔壁品质因子足够高，原子系统也不等价于少数几个能级构成的简单模型：它仍然有不为零的几率跃迁到不可控的能级空间、与原子相互作用的自由空间真空场的量子效应也必须考虑. 本文将结合开放量子系统理论的基本要素与原子光子的基本模型，对原子分子系统在电磁场中发生的耗散以及量子退相干过程做简单综述，并重点介绍描述量子系统退相干过程的主流理论工具——主方程.     

Self-trapped dynamics of a hollow Gaussian beam in metamaterials

We present a systematic investigation on the dynamics of a hollow Gaussian beam (HGB) in metamaterials. We predict self-trapped propagation of HGBs and evolution of the beam is highly influenced by dimensionless dispersion coefficient (κ), which determines the strength of dispersion over diffraction. The evolutions of HGBs such as disappearance of single ringed intensity pattern and appearance of patterns with a central bright spot are achievable with less propagation distance in metamaterials with higher values of κ. On the other hand, metamaterials with low values of κ can preserve single ring intensity distribution over a long propagation distance without focusing. When the strength of dispersion over diffraction increases, it significantly influences the evolution of the beam and may lead to the formation of tightly focussed beam with high peak intensity at the center. The phenomenon of tight focussing is found to have some applications in trapping of nanosized particles.