No abstract

With the growing requirements for the renewability and sustainability of electronic products, environmentally friendly cellulosebased materials have attracted immense research interests and gained increasing prominence for electronic devices. Humidity sensors play an essential role in industries, agriculture, climatology, medical services, and daily life. Here, for the first time, we fabricate capacitive humidity sensors based on ionic conductive wood-derived cellulose nanopapers (WCNs). The WCN-based humidity sensors exhibited ultrahigh sensitivity, fast response, small hysteresis, and more importantly, a wide working range of relative humidity (RH). The sensors showed >10 4 times increase in the sensing signal over the 7−94% RH range at 20 Hz, while many reported humidity sensors with high sensitivity often have the working range limited to high RH levels. Our sensors can realize the distinction of nuances in humidity and exhibit outstanding noncontact skin humidity sensing properties. Flexible WCN-based humidity sensors were also fabricated, and they displayed excellent sensing properties with long-time stability, endowing them with multifunctional applications. The contrast humidity sensing experiment compared to the existing commercial humidity sensor further demonstrated the higher and faster response of our WCN-based sensors. Thus, this work provides effective guidance for the design of high-performance humidity sensors using nanopapers and opens a new dimension for a variety of future applications.

No abstract

No abstract

An adaptive dynamic special global sliding mode controller that is based on proportional integral derivative (PID) sliding surface using radial basis function (RBF) neural network (NN) for a three- phase active power filter (APF) was presented in this paper. To overcome the problems associated with the schemes of the conventional sliding mode control, a global PID sliding manifold is introduced to realize the whole process of robustness and inhibition of the steady state error, accelerating the system response meanwhile. In addition, the nested dynamic sliding mode controller can reduce the influence of chattering that may lead to malfunction of the insulated gate bipolar transistor (IGBT) caused by sign function in the control law, achieving a better property. Moreover, owing to the parameter uncertainties and the external disturbances, a RBF neural estimator is added to eliminate the chattering phenomenon that further optimizes the performance of the system. Eventually, simulation studies in the MATLAB/SimPower Systems Toolbox verify the outstanding performance of the designed RBFNN dynamic global PID sliding mode controller in three different conditions, and some comparisons are made at the same time to demonstrate the excellent properties of the raised control method.