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A proportional plus derivative (PD) adaptive tracking control strategy based on neural sliding mode is proposed for the interference of unknown factors in the mathematical model of four-wheel omnidirectional robots. Firstly, the dynamics model of the robot is analyzed. Secondly, the backstepping trajectory tracking controller is used to obtain the virtual velocity, and the PD controller is designed based on the error between the virtual input and the actual input. Then, the neural network is used to approximate the uncertainty in the dynamics model, and the stability of the system is proved by the Lyapunov theorem. Simulation and experimental results show that the control strategy is effective.

We developed a triazatruxene-based hole transport material (HTM), 3Ka-DBT-3Ka, aiming to enhance band alignment and augment charge generation and collection in devices, as an alternative for 1,2-ethanedithiol (EDT). The PbS CQD solar cells employing 3Ka-DBT-3Ka as the HTM achieve a peak efficiency of 11.4%, surpassing devices employing the conventional PbS-EDT HTM (8.9%). [ABSTRACT FROM AUTHOR]

Increasing the N-doping concentration has been recognized as one of the most effective strategies to improve the potential properties of carbonaceous materials in energy, the environment, and other fields. However, the instability of N dopants at high temperatures makes the N-doping concentration far from the theoretical upper limit. Herein, we prepared bamboo-like carbon nanotubes (BCNTs) with a theoretically upper-limited N-doping concentration via one-step pyrolysis of zinc cyanamide in the presence of Ni ions. The N-doping concentration of optimized BCNT-5 reached 12.45 atom %, approximate to the theoretical upper limit of 12.50 atom % at a carbonization temperature of 1000 °C. By using peroxymonosulfate-based advanced oxidation processes as an example, BCNT-5 exhibited excellent catalytic performance for nonradical tetracycline degradation with good versatility and adaptability. Graphitic N was demonstrated to be the active site for nonradical peroxymonosulfate activation. Our work provided a facile and effective strategy for ultrahigh N-doping and morphology regulation in carbonaceous materials toward different applications. [ABSTRACT FROM AUTHOR]

The rotor attitude detection of spherical motors usually requires the installation of position sensors on the rotor shaft or stator to achieve, which occupy a large space and cause negative effects for the practical installation and application of spherical motors. In this paper, a sensorless position detection method for reluctance spherical motors based on the structure and operating characteristics of reluctance spherical motors is proposed. By detecting the stator coil inductance data at different rotor attitude angles, the position prediction model is constructed using the extreme learning machine algorithm. Through comparison and validation, it is demonstrated that the rotor attitude angle obtained by the method is highly accurate, providing a feasible idea for the control and application of reluctance spherical motors. [ABSTRACT FROM AUTHOR]

A spherical motor has multiple degrees of freedom. Its motion control requires an accurate attitude detection system. This study proposes a low‐cost microelectromechanical system (MEMS) inertial measurement sensor to detect the attitude of the spherical motor. The proposed sensor combines a three‐axis gyroscope and a three‐axis accelerometer to obtain raw position data of spherical motors to estimate rotor's attitude. To improve the accuracy of the estimated attitude from the raw position data, the authors reduce the inclination angle error between the motor's rotor and MEMS sensor's coordinate systems by compensating axial angle error. A high‐speed camera that generally provides high accuracy of the attitude is used as a calibration device for comparison and validation. Experimental results show that the MEMS inertial measurement sensor can achieve accurate attitude estimation that is suitable for motion control of a spherical motor. [ABSTRACT FROM AUTHOR]