Hiding an arbitrary object with a cloak at a distance from an object is of great significance in scientific research, but remains unrealized as a practical device. In this paper, we propose the first experimental realization of a remote cloaking device that makes any object located at a certain distance invisible at direct current (DC) frequency. A negative resistor network with active elements is used to achieve the remote function of the DC cloak. Based on this network, the cloak can remotely generate a hidden region without distorting the currents far from the cloaked region. The experimental results show that any object in the hidden region is invisible to a DC detector. Our cloak does not require any knowledge of the hidden object. The experimental demonstration shows the superiority of this remote cloaking device, which may find potential applications in medical or geologic research.

Electromagnetic (EM) waves that bypass obstacles to achieve focus at arbitrary positions are of immense significance to communication and radar technologies. Small-sized and low-cost metasurfaces enable the accomplishment of this function. However, the magnitude-phase characteristics are challenging to analyze when there are obstacles between the metasurface and the EM wave. In this study, we creatively combined the deep reinforcement learning algorithm soft actor–critic (SAC) with a reconfigurable metasurface to construct an SAC-driven metasurface architecture that realizes focusing at any position under obstacles using real-time simulation data. The agent learns the optimal policy to achieve focus while interacting with a complex environment, and the framework proves to be effective even in complex scenes with multiple objects. Driven by real-time reinforcement learning, the knowledge learned from one environment can be flexibly transferred to another environment to maximize information utilization and save considerable iteration time. In the context of future 6G communications development, the proposed method may significantly reduce the path loss of users in an occluded state, thereby solving the open challenge of poor signal penetration. Our study may also inspire the implementation of other intelligent devices.

Holograms are a promising state-of-the-art technique that are able to reproduce fully three-dimensional images. However, most elementary holograms only recover a nonadjustable image restricted by a certain amplitude and phase. Recently, the concept of the reconfigurable metasurface has come into sight. The reconfigurable metasurfaces can be tuned dynamically through a physics control signal from outside. Here we design and realize a series of novel, to the best of our knowledge, reconfigurable metasurfaces. Using these devices, an advanced metasurface hologram effect could be easier to achieve. Moreover, the reconfigurable property of such tunable metasurface enables independent control of advanced multiplexed channel functionalities to exist in comparison with the conventional static metasurface holograms. Our method creates unprecedented display and virtual effects, and it opens a novel way to a more flexible methodology of dynamic control of electromagnetic waves.

By virtue of eliminating the characteristic signals of physical objects, invisibility cloaks can also prevent the objects from being detected by instruments using electrical current. However, most existing designs of direct current cloaks cannot be directly applied in the natural environment. In this paper, we present a three-dimensional direct current cloak by solving Laplace equation in electric conduction. The cloak is composed of a bilayer structure with homogeneous and isotropic bulk materials. The designed structure, having withstood both conventional electrical potential measurements and tests by a commercially-available detector, is highly effective in suppressing current characteristic signals in close simulation of natural environmental conditions. The cloak is expected to facilitate the study of characteristic signal control in medical and geological research in the field of current detection, such as tumor diagnosis and mineral exploration.

This paper provides systematic analysis and controller design methods for high-performance two-mass drive systems. A non-parametric method is introduced to identify dynamics of two-mass drive system, especially the resonance and anti-resonance frequencies. Compared with the conventional Fast Fourier Transform (FFT) approach, the non-parametric method can easily recognize anti-resonance frequency and tolerate lower Signal-to-Noise Ratio (SNR) of measured signals. Two notch filters are tuned using the identified characters to suppress resonance, and together with simple Proportional-Integral (PI) controllers to improve the position tracking performance. Simulation and experimental results are presented to demonstrate performance improvement obtained by the proposed method.

The satisfactory speed tracking performance of a permanent magnet synchronous motor (PMSM) is hard to achieve due to the unknown disturbances, time-varying parameters, and actuator saturation. In this paper, an adaptive fuzzy PI controller with robust updating rules is proposed to improve the dynamic response of the PMSM servo system and reduce the impacts of disturbances. This controller can regulate conventional PI controller gains online with a fuzzy tuner. The scaling factors of the fuzzy tuner are online optimized by a fuzzy regulator when initial information of the dynamic non-linear system isn’t enough for designing fixed parameters fuzzy tuner in advance. Meanwhile, the robust updating rules are designed to ensure the stability and robustness of the optimization process. Through real-time PMSM speed control experiments, it is found that the proposed adaptive fuzzy PI controller is effective, and the speed-tracking and anti-disturbance performance can be improved comparing to a conventional PI controller.