Multicolour tunable luminescence of thermal-stable Ce3+/Tb3+/Eu3+-triactivated Ca3Gd(GaO)3(BO3)4 phosphors via Ce3+ → Tb3+ → Eu3+ energy transfer for near-UV WLEDs applications

A series of single-component blue, green and red phosphors have been fabricated based on the Ca₃Gd(GaO)₃(BO₃)₄ host through doping of the Ce³⁺/Tb³⁺/Eu³⁺ ions, and their crystal structure and photoluminescence properties have been discussed in detail. A terbium bridge model via Ce³⁺ → Tb³⁺ → Eu³⁺ energy transfer has been studied. The emission colours of the phosphors can be tuned from blue (0.1661, 0.0686) to green (0.3263, 0.4791) and eventually to red (0.5284, 0.4040) under a single 344 nm UV excitation as the result of the Ce³⁺ → Tb³⁺ → Eu³⁺ energy transfer. The energy transfer mechanisms of Ce³⁺ → Tb³⁺ and Tb³⁺ → Eu³⁺ were found to be dipole-dipole interactions. Importantly, Ca₃Gd(GaO)₃(BO₃)_4:Ce³⁺,Tb³⁺,Eu³⁺ phosphors had high internal quantum efficiency. Moreover, the study on the temperature-dependent emission spectra revealed that the Ca₃Gd(GaO)₃(BO₃)_4:Ce³⁺,Tb³⁺,Eu³⁺ phosphors possessed good thermal stability. The above results indicate that the phosphors can be applied into white light-emitting diodes as single-component multi-colour phosphors.     

A low power and low phase-noise 91~96 GHz VCO in 90 nm CMOS

This paper reports a 94 GHz CMOS voltage-controlled oscillator (VCO) using both the negative capacitance (NC) technique and series-peaking output power and phase noise (PN) enhancement technique. NC is achieved by adding two variable LC networks to the source nodes of the active circuit of the VCO. NMOSFET varicaps are adopted as the required capacitors of the LC networks. In comparison with the conventional one, the proposed active circuit substantially decreases the input capacitance (C_in) to zero or even a negative value. This leads to operation (or oscillation) frequency (OF) increase and tuning range (TR) enhancement of the VCO. The VCO dissipates 8.3 mW at 1 V supply. The measured TR of the VCO is 91~96 GHz, close to the simulated (92.1~96.7 GHz) and the calculated one (92.2~98.2 GHz). In addition, at 1 MHz offset from 95.16 GHz, the VCO attains an excellent PN of – 98.3 dBc/Hz. This leads to a figure-of-merit (FOM) of ?188.5 dBc/Hz, a remarkable result for a V- or W-band CMOS VCO. The chip size of the VCO is 0.75 × 0.42 mm², i.e. 0.315 mm².     

Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems

This paper proposes an adaptive super-twisting decoupled terminal sliding mode control technique for a class of fourth-order systems. The adaptive-tuning law eliminates the requirement of the knowledge about the upper bounds of external perturbations. Using the proposed control procedure, the state variables of cart-pole system are converged to decoupled terminal sliding surfaces and their equilibrium points in the finite time. Moreover, via the super-twisting algorithm, the chattering phenomenon is avoided without affecting the control performance. The numerical results demonstrate the high stabilization accuracy and lower performance indices values of the suggested method over the other ones. The simulation results on the cart-pole system as well as experimental validations demonstrate that the proposed control technique exhibits a reasonable performance in comparison with the other methods.     

Two-stage optimization for machine learning workflow

Machine learning techniques play a preponderant role in dealing with massive amount of data and are employed in almost every possible domain. Building a high quality machine learning model to be deployed in production is a challenging task, from both, the subject matter experts and the machine learning practitioners.For a broader adoption and scalability of machine learning systems, the construction and configuration of machine learning workflow need to gain in automation. In the last few years, several techniques have been developed in this direction, known as AutoML.In this paper, we present a two-stage optimization process to build data pipelines and configure machine learning algorithms. First, we study the impact of data pipelines compared to algorithm configuration in order to show the importance of data preprocessing over hyperparameter tuning. The second part presents policies to efficiently allocate search time between data pipeline construction and algorithm configuration. Those policies are agnostic from the metaoptimizer. Last, we present a metric to determine if a data pipeline is specific or independent from the algorithm, enabling fine-grain pipeline pruning and meta-learning for the coldstart problem.     

Parameter identification of proton exchange membrane fuel cell via Levenberg-Marquardt backpropagation algorithm

It is essential to develop an accurate model of proton exchange membrane fuel cell (PEMFC) for a reliable operation and analysis, in which unknown parameters usually need to be determined. The inherent nonlinear, strong coupling, and diversification of PEMFC model seriously hinder traditional methods to identify the parameters. For the sake of overcoming these thorny obstacles, Levenberg-Marquardt backpropagation (LMBP) algorithm based on artificial neural networks (ANNs) is proposed for PEMFC parameter identification. Furthermore, the performance of LMBP is thoroughly evaluated and compared with four typical meta-heuristic algorithms under three cases. Simulation results indicate that LMBP performs a higher accuracy and faster speed for parameter identification. In particular, accuracy and convergence speed can achieve as much as 99.8% and 95.9% growth via LMBP, respectively.     

Tuning of Active Disturbance Rejection Control with application to power plant furnace regulation

Active Disturbance Rejection Control (ADRC) is emerging as a promising solution in dealing with the unmeasurable disturbances and unknown uncertainties, which are treated in a lumped manner and augmented as an extended state variable. Subsequently, an extended state observer (ESO) is designed to estimate and cancel the combined uncertain term in real time, modifying the uncertain plant to behave like a nominal model consisting of integrators. In the original ADRC formulation, the plant model is assumed to be of delay-free and its order is assumed to be equal to that of the real plant. However, a low-order ADRC is preferred and received a wide acceptance in practice because of its simplicity. Currently, the feasibility of such practice is not clearly revealed as well as its potential dangers. To this end, this paper analyzes the control mechanism from the perspective of the modified plant, which, in turn, would give guidance to parameter tuning. The effect of each parameter on the compensation efficiency and stability conditions of the modified plant is analyzed, based on which a complete tuning procedure for ADRC is developed where the initial settings is derived from the existing PI controller parameters. Finally, the proposed tuning method is experimentally used for a furnace pressure regulation of a 1000MW power plant, validating the feasibility of the low-order ADRC, even in the absence of both dynamic model and the information on the model order.     

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method. In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.      

半导体激光器温度调谐波长扫描技术

低成本、小型化的波长扫描半导体激光器在光纤传感系统中有着重要作用。设计了一种可进行温度调谐的半导体激光光源驱动电路。该电路系统以ARM单片机作为控制中心,利用热敏电阻采样激光工作温度,并通过半导体制冷器(TEC)进行温度调节,使得激光器能够根据温度调谐实现波长扫描；同时通过背向光探测器(PD)采样激光输出功率,并通过改变半导体激光驱动电流实现对激光输出功率的控制,使得激光器在温度变化时输出光功率保持稳定。实验结果表明,该电路能够长时间可靠地工作,激光器能够实现的最大波长调谐范围为5nm,且输出光功率在整个波长扫描过程中保持稳定。     

Environmental Control of Triplet Emission in Donor–Bridge–Acceptor Organometallics

Carbene‐metal‐amides (CMAs) are a promising family of donor–bridge–acceptor molecular charge‐transfer (CT) emitters for organic light‐emitting diodes. A universal approach is demonstrated to tune the energy of their CT emission. A blueshift of up to 210 meV is achievable in solid state via dilution in a polar host matrix. The origin of this shift has two components: constraint of thermally‐activated triplet diffusion, and electrostatic interactions between guest and polar host. This allows the emission of mid‐green CMA archetypes to be tuned to sky blue without chemical modifications. Monte‐Carlo simulations based on a Marcus‐type transfer integral successfully reproduce the concentration‐ and temperature‐dependent triplet diffusion process, revealing a substantial shift in the ensemble density of states in polar hosts. In gold‐bridged CMAs, this shift does not lead to a significant change in luminescence lifetime, thermal activation energy, reorganization energy, or intersystem crossing rate. These discoveries offer new insight into coupling between the singlet and triplet manifolds in CMA materials, revealing a dominant interaction between states of CT character. The same approach is employed using materials which have been chemically modified to alter the energy of their CT state directly, shifting the emission of sky‐blue chromophores into the practical blue range.