Nanjing University of Science and Technology

About: Nanjing University of Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Control theory & Catalysis. The organization has 31581 authors who have published 36390 publications receiving 525474 citations. The organization is also known as: Nánjīng Lǐgōng Dàxué & Nánlǐgōng.

Active Disturbance Rejection Adaptive Control of Hydraulic Servo Systems

Abstract: This paper presents an active disturbance rejection adaptive control scheme via full state feedback for motion control of hydraulic servo systems subjected to both parametric uncertainties and uncertain nonlinearities. The proposed controller is derived by effectively integrating adaptive control with extended state observer via backstepping method. The adaptive law is synthesized to handle parametric uncertainties and the remaining uncertainties are estimated by the extended state observer and then compensated in a feedforward way. The unique features of the proposed controller are that not only the matched uncertainties but also unmatched uncertainties are estimated by constructing two extended state observers, and the parameter adaptation law is driven by both tracking errors and state estimation errors. Since the majority of parametric uncertainties can be reduced by the parameter adaptation, the task of the extended state observer is much alleviated. Consequently, high-gain feedback is avoided and improved tracking performance can be expected. The proposed controller theoretically achieves an asymptotic tracking performance in the presence of parametric uncertainties and constant disturbances. In addition, prescribed transient tracking performance and final tracking accuracy can also be guaranteed when existing time-variant uncertain nonlinearities. Comparative experimental results are obtained to verify the high tracking performance nature of the proposed control strategy.

Healing All-Inorganic Perovskite Films via Recyclable Dissolution–Recyrstallization for Compact and Smooth Carrier Channels of Optoelectronic Devices with High Stability

Abstract: The strong ionic character endows all-inorganic CsPbX3 (X = Cl, Br, I) perovskite nanocrystals (NCs) with different chemical features from classical Cd-based NCs, especially when considering their interaction with polar solvents and surfactants. This has aroused intensive interest, but is still short of comprehensive understanding. More significantly, above characteristic may be used to improve the quality of perovskite thin films, which is crucial for the carrier transport inside optoelectronic devices. Here, an interesting recyclable dissolution–recyrstallization phenomenon of all-inorganic pervoskite, as well as its application on room temperature (RT) self-healing of compact and smooth carrier channels in ambient atmosphere for high-performance PDs with high stability is reported. First, according to solubility equilibrium principle, the size of CsPbBr3 crystals can be reversibly tuned in the range of 10 nm–1 μm through washing with polar solvent or stirring with assistance of surfactants at RT. Second, such phenomenon is applied for significant film quality improvement by forming a liquid circumstance within films, which can transport matter at surface and sharp parts into the gaps, healing themselves at RT. This strategy results in large-area, crack-free, low-roughness perovskite thin films. Obviously, such improvement facilitates transport and extraction of carriers in the channels of devices, which has been evidenced by the improvement of performances of the corresponding PDs at ambient condition.

Neural-Network-Based Decentralized Adaptive Output-Feedback Control for Large-Scale Stochastic Nonlinear Systems

Abstract: This paper focuses on the problem of neural-network-based decentralized adaptive output-feedback control for a class of nonlinear strict-feedback large-scale stochastic systems. The dynamic surface control technique is used to avoid the explosion of computational complexity in the backstepping design process. A novel direct adaptive neural network approximation method is proposed to approximate the unknown and desired control input signals instead of the unknown nonlinear functions. It is shown that the designed controller can guarantee all the signals in the closed-loop system to be semiglobally uniformly ultimately bounded in a mean square. Simulation results are provided to demonstrate the effectiveness of the developed control design approach.

Giant Rashba splitting in 2D organic-inorganic halide perovskites measured by transient spectroscopies

Abstract: Two-dimensional (2D) layered hybrid organic-inorganic halide perovskite semiconductors form natural "multiple quantum wells" that have strong spin-orbit coupling due to the heavy elements in their building blocks. This may lead to "Rashba splitting" close to the extrema in the electron bands. We have used a plethora of ultrafast transient, nonlinear optical spectroscopies and theoretical calculations to study the primary (excitons) and long-lived (free carriers) photoexcitations in thin films of 2D perovskite, namely, (C6H5C2H4NH3)2PbI4. The density functional theory calculation shows the occurrence of Rashba splitting in the plane perpendicular to the 2D barrier. From the electroabsorption spectrum and photoinduced absorption spectra from excitons and free carriers, we obtain a giant Rashba splitting in this compound, with energy splitting of (40 ± 5) meV and Rashba parameter of (1.6 ± 0.1) eV·A, which are among the highest Rashba splitting size parameters reported so far. This finding shows that 2D hybrid perovskites have great promise for potential applications in spintronics.