Researchers are showing an increasing interest in high-performance flexible pressure sensors owing to their potential uses in wearable electronics, bionic skin, and human–machine interactions, etc. However, the vast majority of these flexible pressure sensors require extensive nano-architectural design, which both complicates their manufacturing and is time-consuming. Thus, a low-cost technology which can be applied on a large scale is highly desirable for the manufacture of flexible pressure-sensitive materials that have a high sensitivity over a wide range of pressures. This work is based on the use of a three-dimensional elastic porous carbon nanotubes (CNTs) sponge as the conductive layer to fabricate a novel flexible piezoresistive sensor. The synthesis of a CNTs sponge was achieved by chemical vapor deposition, the basic underlying principle governing the sensing behavior of the CNTs sponge-based pressure sensor and was illustrated by employing in situ scanning electron microscopy. The CNTs sponge-based sensor has a quick response time of ~105 ms, a high sensitivity extending across a broad pressure range (less than 10 kPa for 809 kPa−1) and possesses an outstanding permanence over 4,000 cycles. Furthermore, a 16-pixel wireless sensor system was designed and a series of applications have been demonstrated. Its potential applications in the visualizing pressure distribution and an example of human–machine communication were also demonstrated.
Analog metamaterials (MMs) manipulate their effective medium parameters difficultly while its geometrical architecture is composed of hybrid compositions. However, the genic algorithm as a calculation analogue search algorithm seeking for optimal solution can be applied to artificial metamaterials architecture construction. Herein, a novel encoding strategy of metamaterial architecture construction utilizing multi-parameter seeking optimization was proposed. Binary encoding and decoding of the geometrical layer-thickness enables form final dimension based the objective fitness function. The algorithm iteration optimizes initial geometrical dielectric-layer thicknesses. Then, combining the optimizing initial parameter with composite multi-loops metal spatial distribution built final metamaterials in numerical analysis software. Based on this co-simulation disposition, the proposed metamaterial presents broadband features of 2.5GHz at the physical high-absorption to spatial wave over 80%. The proposed metamaterial presents low radar cross-sections, wide polarization insensitivity, and dynamical flexibility simultaneously. Moreover, a disposition of the proposed metamaterial loaded on a referenced antenna exhibits a well real applicated capability in radar cross-sections reduction for the physical passive equipment invisibility. Numerical simulation and experiment results in MMs properties of the absorption and flexibility show good agreements, suggesting the advantage of genic algorithm optimizations in co-simulation for metamaterials architecture construction which shows a good potential application in spatial complicated geometry forming.
The brushless DC motor (BLDCM) speed control system has various kinds of uncertainties, such as reference speed mutation, noise and parameters change, etc. However, proportional integral (PI) control method used widely cannot handle the uncertainties in the control system well. A novel discrete adaptive control with Multiple-Step-Guess (MSG) estimation for BLDCM speed control system is proposed in this contribution. MSG estimation is firstly developed and applied in BLDCM speed control system, which estimate the BLDCM model parameters online with only five steps history information sampled from the input signal and output signal. The tracking adaptive control law is designed to ensure the speed can track reference speed rapidly and accurately. Compared with PI control and recursive least square adaptive control (RLSAC), extensive simulations verify that the BLDCM speed response under MSG adaptive control (MSGAC) has better dynamic and steady state performance in the case of reference speed mutation and BLDCM parameters change. Simulation results illustrate that the novel proposed method is effective and robust for uncertainties of BLDCM speed control system.
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