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Inspired by buckle-induced structural deformation, a new type of tensegrity robot using bending bars is proposed. First, a combination of numerical calculation and the finite-element simulation method was adopted to determine the influence of geometric parameters on equivalent stiffness, and the basic configuration parameters were determined. Then, the tensegrity dynamical model and the ground contact model were established using a nonlinear finite-element method, and four rolling gaits of the robot were realized by driving diagonal cables. Finally, an experimental prototype of the bending bar tensegrity robot was built for rolling gait experiments. The results show that the experimental rolling motion is in good agreement with the theoretical model. Through continuous curve path rolling, the minimum turning radius of the robot was determined, and the motion mode of the prismatic tensegrity robot was enriched. Practical Applications: Tensegrity structure is a self-balancing system composed of compression bars and tension cables, which has aroused numerous scholars' research interest in civil architecture, mechanical engineering, aerospace, biomedical, and other fields. The results cover model design, form-finding analysis, static equilibrium stability analysis, optimization design, dynamic response analysis, and so on. In fact, when the tensegrity mechanism is applied to a mobile robot, a change in shape can be achieved by shortening some cables with the actuator, so the system's stiffness contradicts the ability to deform. The focus of this work is to propose a new type of bending bar design that can replace the spring to meet the needs of large deformation and avoid weakening the structure's overall stiffness. This design realizes the rolling motion mode of the robot and can be applied to the motion mode of other prismatic tensegrity robots. [ABSTRACT FROM AUTHOR]

Background: Green manure is an important source of organic fertilizer. Exploring green fertilizer and nitrogen fertilizer reduction is important for agricultural production. However, few studies have been conducted, especially on the effects of different green fertilizers along with reduced nitrogen fertilizer application on soil ammonia volatilization emissions, rice yield, and nitrogen fertilizer uptake and utilization. Methods: In this study, the effects of different types of green manure and reduced nitrogen fertilizer application on soil ammonia volatilization emissions, aboveground population characteristics of rice, and nitrogen fertilizer uptake and utilization were explored. This study was based on a field-positioning experiment conducted between 2020 and 2022. Six treatments were established: no nitrogen fertilizer application (CK), conventional fertilization in wheat-rice (WR), villous villosa-rice (VvR), vetch sativa-rice (VsR), rapeseed seed-rice (RR), and milk vetch-rice (GR), with a 20% reduction in nitrogen fertilizer application. The amounts of phosphorus and potassium fertilizers remained unchanged. The characteristics of ammonia volatilization loss in rice fields, agronomic traits of rice, yield traits, and nitrogen uptake and utilization were investigated. Results: The results indicated a significant difference (P < 0.05) in the impact of different treatments on ammonia volatilization emissions from rice in the two-year experiment. Compared with WR treatment, VvR, VsR, RR, and GR treatments reduced the total ammonia volatilization loss by 23.58 to 39.21 kg ha−1, respectively. Compared with the conventional WR treatment, other treatments increased rice yield by 0.09 to 0.83 t ha−1. GR treatment was significantly higher than other green fertilizer treatments, except for VsR (P < 0.05). It increased the nitrogen uptake of rice by an average of 4.24%–22.24% and 13.08%–33.21% over the two years, respectively. The impact of different types of green manure on the nitrogen uptake and utilization of rice varied greatly, indicating that the combination of green manure and fertilizer is a sustainable fertilization model for crops to achieve high yields. In particular, the Chinese milk vetch as green manure was more beneficial for ammonia volatilization reduction in paddy field and stable grain production of rice. [ABSTRACT FROM AUTHOR]

A robust control strategy based on Adaboost prediction was proposed for the effects of dynamic uncertainty, parameter perturbation and nonlinear factors such as friction and leakage on the robustness and low-speed performance of the electro-hydraulic servo system. Based on the establishment of the Pol-Ind friction model, according to the mathematical model of the continuous rotary electro-hydraulic servo motor, the structural uncertainty model of the system under parameter perturbation and external perturbation and the generalized state equation of the system are established. The robust controller is designed according to the H ∞ control theory. The system feedback mechanism is designed by using the AdaBoost based on the RBF neural network algorithm. The real-time input and output of the system are used as the training sample set for repeated training, and the multiple weak neural network predictors obtained by training are used to form a strong predictor to calculate the forecast output and error of the electro-hydraulic servo system, and the robust controller was used for real-time control. Simulation and experiment show that: compared with the wavelet neural network control, the robust controller based on AdaBoost prediction has a good tracking performance to the slope signal with an input signal of 0.001°/s, and has a high response speed to sinusoidal signal. Under the condition of satisfying the requirement of double 10 index, the maximum response frequency reaches 15 Hz. It can effectively improve the low-speed performance and anti-interference ability of the electro-hydraulic servo system, greatly improve the robustness of the system and expand the frequency band of the system. [ABSTRACT FROM AUTHOR]