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An adaptive iterative learning control strategy is presented for a class of nonlinear pure-feedback systems with initial state error using RBF-neural network to solve the problem of non-uniform trajectory tracking. The proposed control scheme utilizes RBF-neural network to learn the behavior of the unknown plant dynamics. Filtered signals are employed to circumvent algebraic loop problems encountered in the implementation of the existing controllers. Backstepping design technique is applied to deal with system dynamics. Based on the Lyapunov-like synthesis, we show that all signals in the closed-loop system remain bounded over a pre-specified time interval [0, T ]. There even exist initial state errors, the norm of tracking error vector will asymptotically converge to a tunable residual set as iteration goes to infinity. A time-varying boundary layer is introduced to solve the problem of initial state error. A typical series is introduced in order to deal with the unknown bound of the approximation errors and complete the non-uniform trajectory tracking problem. Finally, the simulation example of one-link robot system shows the feasibility and effectiveness of the approach.

Piezoelectric semiconductors (PSs), possessing the characteristic of deformation-polarization-carrier multi-field coupling, have been widely used in energy harvesters, field-effect transistors, and other intelligent devices. It is very important to investigate the effect of the polarization field only induced by flexoelectricity on piezotronic behaviors of PS nanostructures. We propose a sandwich-type PS composite beam with bending deformation, and develop the one-dimensional model for PS composite beams with flexoelectricity. Through introducing the average electric field in the thickness, we can get rid of the contribution from piezoelectricity to the total induced polarization, as a result, the individual effect of flexoelectricity on the macroscopic multi-field coupling behaviors of the bending composite beam can be evaluated.

Terahertz electromagnetic waves have many important applications in the fields of material characterization, optical scanning imaging, security, biomedicine and communication. However, the research on terahertz elastic waves is quite limited. Based on the classical Love’s rod theory, we develop the one-dimensional theory for piezoelectric semiconductor rod by taking the lateral inertial effect into account. Using the derived model, we conduct an analysis of elastic longitudinal wave propagating in an in infinite piezoelectric semiconductor rod at terahertz frequencies, and investigate the effect of the rod’s radius and the initial electron concentration on phase speed and group speed. The numerical results show that within the terahertz region (THz) the lateral inertial effect plays a dominant role in wave propagation properties.

Piezoelectric semiconductors (PSs) have great potential applications in future multifunctional devices. The interaction among deformation, polarization, and carrier in PSs under an external load leads to a variety of innovative electronic, mechanical, and optical behaviors. Studying multi-field coupling mechanical behaviors of PSs plays a fundamental role in PS devices. However, the partial differential equations (PDEs) describing PSs are nonlinear. This brings rather a mathematical challenge to analysis of PSs. In this work, we propose a machine-learning-based approach to solving multi-field coupling problems of piezoelectric semiconductors. Based on the linear analytical solution, the physics-informed neural networks (PINNs) is trained to obtain the data-driven solutions for a static axial extensional PS rod.

We theoretically study the behaviors of a piezoelectric semiconductor (PS) fiber in the extensional deformation resulted from the two local thermal loads using the multi-field coupling theory for thermo-piezoelectric semiconductor. With the linearized method, the analytical results are obtained for small temperature changes. For large temperature changes, the linearized method is not valid. In this case, we conduct a nonlinear analysis by COMSOL. The numerical results show that the potential barrier and well produced by the temperature changes through a series of coupling effects could be used to manipulate the forward/reverse currents in the fiber simultaneously.

We study the extension of a piezoelectric semiconductor (PS) fiber containing a PN junction, focusing on the effective polarization charges which are fundamental to piezotronics. A one-dimensional model derived previously from the macroscopic theory of PSs is used for a linear theoretical and nonlinear numerical analysis by COMSOL. Both homogeneous and heterogeneous junctions are studied. In addition to the built-in electric potential and field as well as I-V curve, distributed effective polarization charge along the fiber and concentrated effective polarization charge on the junction interface are calculated and examined.

An adaptive iterative learning control (AILC) strategy is presented for a class of nonlinear pure-feedback systems with initial state error using fuzzy logic systems (FLS) to solve the problem of non-uniform trajectory tracking. The proposed control scheme utilizes fuzzy logic system to learn the behavior of the unknown plant dynamics. Filtered signals are employed to circumvent algebraic loop problems encountered in the implementation of the existing controllers. Backstepping design technique is applied to deal with system dynamics. Based on the Lyapunov-like synthesis, we show that all signals in the closed-loop system remain bounded over a pre-specified time interval [0,T]. There even exist initial state errors, the norm of tracking error vector will asymptotically converge to a tunable residual set as iteration goes to infinity. A time-varying boundary layer is introduced to solve the problem of initial state error. A typical series is introduced in order to deal with the unknown bound of the approximation errors and complete the non-uniform trajectory tracking problem. Finally, the simulation example of one-link robot system shows the feasibility and effectiveness of the approach.

We present a one-dimensional model for a piezoelectric semiconductor (PS) rod with varying cross section subject to an axial loading. Using the linearized method, we obtain exact solutions for an n-type PS rod under static extension. Based on the obtained solutions, the effect of the initial concentration of electrons, the axial force, and the radius ratio of two cross sections at the two ends on the redistribution of electrons in the ZnO rod is investigated. Numerical results show that there are a larger variation of electrons near the two ends of the rod, and the piezotronic effect in the PS rod can be controlled through applying an axial force as well as changing the initial concentration of carriers and geometric shape of PS rods.

A magnetic energy harvester to collect the energy in an alternating magnetic field is proposed in this contribution. The multiferroic energy harvester presented here consists of a functionally graded piezomagnetic cylindrical layer for collecting magnetic energy and a functionally graded piezoelectric cylindrical layer for conversion to electric energy. A theoretical analysis is performed using the linear equations of piezomagnetic, piezoelectric, and elastic materials. The ME effect and output power of the magnetic energy harvester are investigated. The effects of various physical and geometricl parameters are also examined.

In order to solve the problem of personalized recommendation in social network, a collaborative filtering algorithm based on users' social relationship mining was proposed with the social network analysis method. Mobile devices and location-based-services have generated rich datasets of people's location information at a very high fidelity. In particular, we employed an entropy-based model (EBM) that not only infers social connections but also estimated the strength of social connections. And obtaining the most similar set of users based on the degree of similar relationship between the users and then calculating unrated items to prefill the original rating matrix. Then producing recommendation used user-based collaborative filtering on the basis of filled rating matrix. Experimental results showed that this algorithm could effectively alleviate data sparsity problem in collaborative filtering and had higher recommendation efficiency.

A novel high-ratio compound gearing which combines the worm gearing with Spiroid gearing is proposed. It is a type of spatial planetary worm gearing, and consists of the centre worm, planetary gear sets, the planetary carrier and the face worm gear. The construction figures of the compound gearing are given, and the design simulation based on SolidWorks is done in the paper. The new gearing can be considered to be used in communication, aerospace, military field, heavy-duty machines, industry automation and other civil machinery.

We perform a theoretical analysis on electrically forced, coupled thickness-shear and flexural vibrations of rectangular piezoelectric plates of monoclinic crystals. Mindlin's first-order theory for piezoelectric plates is used. Two types of boundary conditions are considered. Trigonometric series solutions are obtained. The motional capacitance of the plates and its frequency dependence under a time-harmonic driving voltage, an important property when the plates are used as piezoelectric resonators, is calculated and examined from the series solutions for quartz and langasite plates.

Two dimensional equations are derived for multiferroic circular cylindrical panels with small aspect ratio. The displacement, electrical potential and magnetic potential are assumed to be of zero-order of the radial thickness. The frequency equation is presented for a multiferroic cylindrical panel composed of CoFe2O3 and BaTiO3 with four edges simply supported. Numerical examples show clearly the effects of half-wave numbers in the axial and circumferential directions on the frequency parameters.

In the conventional models for the analysis of power system low-frequency oscillation, excitation systems are considered as the main components that cause the low-frequency oscillation, the effect of hydro-turbine and governor systems are usually ignored. In this paper, the low-frequency oscillation model is proposed considering hydro turbines and speed governors. The results obtained by using eigenvalue relativity and sensitivity analysis method show that the hydro-turbine and governor systems do have influence on the power system low-frequency oscillation mode, and discussions are done about the characteristics of low frequency oscillation modes considering the hydro-turbine and governor models.