A plasmonic refractive index nanosensor structure consisting of a metal-insulator-metal (MIM) waveguide with two symmetrical rectangle baffles coupled with a connected-concentric-double rings resonator (CCDRR) is presented. In this study, its transmission characteristics were investigated using the finite element method (FEM). The consequences, studied via simulation, revealed that the transmission spectrum of the system presents a sharp asymmetric Fano profile due to the destructive interference between the wide-band mode of two rectangle baffles on the bus waveguide and the narrow-band mode of the CCDRR. The effects of the geometric parameters of the structure on the transmission characteristics were investigated comprehensively. A sensitivity of 2260 nm/RIU and figure of merit (FOM) of 56.5 were the best levels of performance that the designed structure could achieve. In addition, the system could act as a sensor for use for temperature sensing, with a sensitivity that could reach 1.48 nm/°C. The designed structure advances with technology with new detection positions and has good application prospects in other high-sensitivity nanosensor fields, for example, acting as a biosensor to detect the hemoglobin level in the blood.

A nanostructure comprising the metal-insulator-metal (MIM) bus waveguide with a stub coupled with a racetrack ring resonator is designed. The spectral characteristics of the proposed structure are analyzed via the finite element method (FEM). The results show that there is a sharp Fano resonance profile and electromagnetically induced transparency (EIT)-like effect, which are excited by a coupling between the MIM bus waveguide with a stub and the racetrack ring resonator. The normalized H_Z field is affected by the displacement of the ring from the stub x greatly. The influence of the geometric parameters of the sensor design on the sensing performance is discussed. The sensitivity of the proposed structure can reach 1774 nm/RIU with a figure of merit of 61. The proposed structure has potential in nanophotonic sensing applications.

The online measurement of ground water quality, as one important area of water resource protection, can provide real-time measured water quality parameters and send out warning information in a timely manner when the water resource is polluted. Based on ultraviolet (UV) spectrophotometry, a remote online measurement method is proposed and used to measure the ground water quality parameters chemical oxygen demand (COD), total organic carbon (TOC), nitrate nitrogen (NO₃–N), and turbidity (TURB). The principle of UV spectrophotometry and the data processing method are discussed in detail, the correlated mathematical modeling of COD and TOC is given, and a confirmatory experiment is carried out. Turbidity-compensated mathematical modeling is proposed to improve the COD measurement accuracy and a confirmatory experiment is finished with turbidity that ranges from 0 to 100 NTU (Nephelometric Turbidity Unit). The development of a measurement instrument to detect the ground water COD, TOC, NO₃–N, and TURB is accomplished; the test experiments are completed according to the standard specification of China’s technical requirement for water quality online automatic monitoring of UV, and the absolute measuring errors of COD, TOC, and NO₃–N are smaller than 5.0%, while that of TURB is smaller than 5.4%, which meets the requirements for the online measurement of ground water quality.

In this paper, an adaptive iterative learning control scheme is proposed to solve the trajectory-tracking problem for tank gun servo systems with input deadzone and arbitrary initial states. A time-varying boundary layer is constructed to deal with the nonzero initial error during the iterative learning controller design. Neural network control and robust control are jointly used to compensate uncertainties and deadzone nonlinearity. The ideal weight of neural network and the upper bound of noncontinuous uncertainties are estimated by using difference learning method. As the iteration number increases, the filtering error can converge to the time-varying boundary layer. All signal are guaranteed to be bounded. A simulation example is presented to verify the effectiveness of the proposed scheme.

The detection of methane has always been an important part of coal mine safety. In order to improve the methane measurement accuracy in coal mines and to determine the influence of environmental interference factors on the measurement results, we designed a spherical, experimental chamber simulating the on-site environment of an underground coal mine containing methane, in which various environmental interference factors can be superimposed. The simulation chamber can generate a uniform and controllable dust environment, a controllable methane environment with concentrations below that which would trigger an alarm, controllable humidity, and environments characterized by other interference factors. Based on computational simulations of the experimental chamber with varying dust-particle-concentration distributions using a single particle size, an optimal design for the chamber has been realized in terms of the rapid mixing of dust and the flow field. Finally, we constructed an underground methane concentration measurement system for coal mines and assessed the influences of different dust concentrations and relative humidity values on the performance of methane measurements, providing a means for improving the measurement accuracy of underground coal mine, spectral, absorption-type methane sensors.

This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial problem of iterative learning control. Robust control technique and adaptive learning control technique are synthesized to handle nonlinear uncertainties and external disturbances. The unknown parameters are estimated according to the full saturation difference learning strategy. As the iteration number increases, the system state can accurately track the reference signal over the whole time interval, and all signal are guaranteed to be bounded.