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.     

Bandgaps and vibration isolation of local resonance sandwich-like plate with simply supported overhanging beam

Applied Mathematics and Mechanics - The concept of local resonance phononic crystals proposed in recent years provides a new chance for theoretical and technical breakthroughs in the structural...     

Porous Molybdenum Carbide Nanostructures Synthesized on Carbon Cloth by CVD for Efficient Hydrogen Production

Molybdenum carbide (Mo₂C) is a promising noble-metal-free electrocatalyst for the hydrogen evolution reaction (HER), due to its structural and electronic merits, such as high conductivity, metallic band states and wide pH applicability. Here, a simple CVD process was developed for synthesis of a Mo₂C on carbon cloth (Mo₂C@CC) electrode with carbon cloth as carbon source and MoO₃ as the Mo precursor. XRD, Raman, XPS and SEM results of Mo₂C@CC with different amounts of MoO₃ and growth temperatures suggested a two-step synthetic mechanism, and porous Mo₂C nanostructures were obtained on carbon cloth with 50 mg MoO₃ at 850 °C (Mo₂C-850(50)). With the merits of unique porous nanostructures, a low overpotential of 72 mV at current density of 10 mA cm⁻² and a small Tafel slope of 52.8 mV dec⁻¹ was achieved for Mo₂C-850(50) in 1.0 m KOH. The dual role of carbon cloth as electrode and carbon source resulted into intimate adhesion of Mo₂C on carbon cloth, offering fast electron transfer at the interface. Cyclic voltammetry measurements for 5000 cycles revealed that Mo₂C@CC had excellent electrochemical stability. This work provides a novel strategy for synthesizing Mo₂C and other efficient carbide electrocatalysts for HER and other applications, such as supercapacitors and lithium-ion batteries.     

Advanced Li-Ion Batteries with High Rate,Stability, and Mass Loading Based on Graphene Ribbon Hybrid Networks

To optimize the cycle life and rate performance of lithium-ion batteries (LIBs), ultra-fine Fe₂O₃ nanowires with a diameter of approximately 2 nm uniformly anchored on a cross-linked graphene ribbon network are fabricated. The unique three-dimensional structure can effectively improve the electrical conductivity and facilitate ion diffusion, especially cross-plane diffusion. Moreover, Fe₂O₃ nanowires on graphene ribbons (Fe₂O₃/GR) are easily accessible for lithium ions compared with the traditional graphene sheets (Fe₂O₃/GS). In addition, the well-developed elastic network can not only undergo the drastic volume expansion during repetitive cycling, but also protect the bulk electrode from further pulverization. As a result, the Fe₂O₃/GR hybrid exhibits high rate and long cycle life Li storage performance (632 mAh g⁻¹ at 5 A g⁻¹, and 471 mAh g⁻¹ capacity maintained even after 3000 cycles). Especially at high mass loading (≈4 mg cm⁻²), the Fe₂O₃/GR can still deliver higher reversible capacity (223 mAh g⁻¹ even at 2 A g⁻¹) compared with the Fe₂O₃/GS (37 mAh g⁻¹) for LIBs.     

HFIP-Functionalized Co3O4 Micro-Nano-Octahedra/rGO as a Double-Layer Sensing Material for Chemical Warfare Agents

Semiconductor metal oxides (SMO)-based gas-sensing materials suffer from insufficient detection of a specific target gas. Reliable selectivity, high sensitivity, and rapid response–recovery times under various working conditions are the main requirements for optimal gas sensors. Chemical warfare agents (CWA) such as sarin are fatal inhibitors of acetylcholinesterase in the nerve system. So, sensing materials with high sensitivity and selectivity toward CWA are urgently needed. Herein, micro-nano octahedral Co₃O₄ functionalized with hexafluoroisopropanol (HFIP) were deposited on a layer of reduced graphene oxide (rGO) as a double-layer sensing materials. The Co₃O₄ micro-nano octahedra were synthesized by direct growth from electrospun fiber templates calcined in ambient air. The double-layer rGO/Co₃O₄-HFIP sensing materials presented high selectivity toward DMMP (sarin agent simulant, dimethyl methyl phosphonate) versus rGO/Co₃O₄ and Co₃O₄ sensors after the exposure to various gases owing to hydrogen bonding between the DMMP molecules and Co₃O₄-HFIP. The rGO/Co₃O₄-HFIP sensors showed high stability with a response signal around 11.8 toward 0.5 ppm DMMP at 125 °C, and more than 75 % of the initial response was maintained under a saturated humid environment (85 % relative humidity). These results prove that these double-layer inorganic–organic composite sensing materials are excellent candidates to serve as optimal gas-sensing materials.     

Noise-induced phenomena in a versatile class of prototype dynamical system with time delay

Nonlinear Dynamics - This work presents a general class of prototype birhythmic dynamical systems, which can be extensively used to study the generation of complex bifurcation of limit cycles....     

Experimental studies on the effect of ultrasonic treatment and hydrogen donors on residual oil characteristics

Residual oil, the residue after the distillation of crude oil, imposes deleterious effects on refinery due to its high viscosity and asphaltene content. In this context, ultrasonic technology has been widely applied in refining processes given its high efficiency and minimal environmental impacts. To guide the selection of operation parameters, in this work, we probed the effect of treatment duration, power, and hydrogen donor on the characteristics of residual oil under ultrasonic treatments. Underlying mechanisms of ultrasonic treatments, in the absence and presence of hydrogen donors, were verified through systematically analyzing viscosity, component conversion, molecular weight, hydrogen distribution, and functional groups of residual oil. While viscosity reductions under low-power density treatment are caused by colloidal system disaggregation, high-power density treatment can bring in both chemical bond cleavage and colloidal system disaggregation. In addition, adding hydrogen donor can effectively prevent radical recombination, and thus increases the yield of saturate. These results provide fundamental understandings on the effects of ultrasonic treatments.     

The Applications of Order Reduction Methods in Nonlinear Dynamic Systems

Two different order reduction methods of the deterministic and stochastic systems are discussed in this paper. First, the transient proper orthogonal decomposition (T-POD) method is introduced based on the high-dimensional nonlinear dynamic system. The optimal order reduction conditions of the T-POD method are provided by analyzing the rotor-bearing system with pedestal looseness fault at both ends. The efficiency of the T-POD method is verified via comparing with the results of the original system. Second, the polynomial dimensional decomposition (PDD) method is applied to the 2 DOFs spring system considering the uncertain stiffness to study the amplitude-frequency response. The numerical results obtained by the PDD method agree well with the Monte Carlo simulation (MCS) method. The results of the PDD method can approximate to MCS better with the increasing of the polynomial order. Meanwhile, the Uniform-Legendre polynomials can eliminate perturbation of the PDD method to a certain extent via comparing it with the Gaussian-Hermite polynomials.