Advances of phononics in 2012—2022

Due to its great potential applications in thermal management, heat control, and quantum information, phononics has gained increasing attentions since the first publication in Rev. Mod. Phys. 84 1045 (2012). Many theoretical and experimental progresses have been achieved in the past decade. In this paper, we first give a critical review of the progress in thermal diodes and transistors, especially in classical regime. Then, we give a brief introduction to the new developing research directions such as topological phononics and quantum phononics. In the third part, we discuss the potential applications. Last but not least, we point out the outlook and challenges ahead.     

Stability analysis of fractional order fuzzy cellular neural networks with leakage delay and time varying delays

In this paper we investigated the stability of fractional order fuzzy cellular neural networks with leakage delay and time varying delays. Based on Lyapunov theory and applying bounded techniques of fractional calculation, sufficient criterion are established to guarantee the stability. Hybrid feedback control is applied to derive the proposed results. Finally, numerical examples with simulation results are given to illustrate the effectiveness of the proposed method.     

电机驱动微装配在双光子制备微结构中的应用

对微结构的制作、微装配系统进行了研究. 采用飞秒激光双光子聚合微加工技术制作有底座、精细的三维立体“拱形”微结构, 其高250μm、长300μm、厚50μm. 将此微结构与实验室自主搭建的二维微装配平台相结合, 利用自主编程的人机交互界面驱动步进电机, 远程操控微装配设备; 将荧光闪烁陶瓷粉末装配到微结构中, 对装配后的微结构进行荧光光谱表征发现, 纯荧光粉末和微结构中的荧光粉末的发射光谱在测量误差范围内基本一致, 表明荧光粉末的光学性质未发生改变. 利用该装置可以将各类微纳米级材料和微结构进行装配, 形成含有不同材料的微结构系统.     

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.     

A Closed‐Loop Control Strategy for Producing Nitrile Rubber of Uniform Chemical Composition in a Semibatch Reactor: A Simulation Study

To improve the quality of industrial nitrile rubbers, the copolymer chemical composition, p_A(t), should ideally be kept constant along the reaction. This work proposes a closed‐loop control strategy for the semibatch operation of the reactor with the aim of regulating p_A(t) within a reduced range of variability. The proposed strategy is evaluated by simulating a mathematical model of the process. To this effect, a simplified mathematical model of the reaction is first derived and then utilized to obtain a suboptimal control law and a soft‐sensor that estimates the polymerization rates. The suboptimal control law is compensated by adding a term proportional to errors in p_A(t). The simulated example considers the production of the low‐composition AJLT grade, with the copolymerization reaction represented by a detailed mathematical model adjusted to an industrial plant. Due to the high performance of the soft‐sensor, the simulation results suggest that the proposed closed‐loop strategy is efficient to adequately regulate p_A(t) in spite of structural and parametric uncertainties, while other quality variables remained practically unaffected.     

Wave-based vibration control of large cable net structures

Large cable net structures have been widely applied in aerospace engineering due to the feature of light-weight, high packaging efficiency, and high thermal stability. Structural vibrations induced by a variety of disturbances are inevitable in the space environment, resulting in the requirement of effective vibration control strategies for large cable net structures. Since the large cable net structures have many closely spaced vibrational modes in the range of low frequencies, traditional modal based control may cause modal truncation and spillover problems. In this paper, a wave-based boundary control strategy is adopted and its effectiveness to control the vibration of cable net structures is investigated, by transfer function analysis and numerical methods. It is found that the structural vibration can be absolutely resisted by applying the wave-based boundary controllers onto all the exterior nodes, when disturbances come from the external boundaries of the cable net. Our results in this paper can provide a theoretical basis for the vibration control of large cable net structures.     

On the Relative Gain Array (RGA) with singular and rectangular matrices

This paper identifies a significant deficiency in the literature on the application of the Relative Gain Array (RGA) formalism in the case of singular matrices. Specifically, it is shown that the conventional use of the Moore–Penrose pseudoinverse is inappropriate because it fails to preserve critical properties that can be assumed in the nonsingular case. It is then shown that such properties can be rigorously preserved using an alternative generalized matrix inverse.     

Nonintrusive data-based learning of a switched control heating system using POD,DMD and ANN

The aim of this work is to derive an accurate model of two-dimensional switched control heating system from data generated by a Finite Element solver. The nonintrusive approach should be able to capture both temperature fields, dynamics and the underlying switching control rule. To achieve this goal, the algorithm proposed in this paper will make use of three main ingredients: proper orthogonal decomposition (POD), dynamic mode decomposition (DMD) and artificial neural networks (ANN). Some numerical results will be presented and compared to the high-fidelity numerical solutions to demonstrate the capability of the method to reproduce the dynamics.