Search Results (993)

Current liquid crystal (LC) lenses cannot achieve lossless arbitrary movement of the optical axis without mechanical movement. This article designs a novel bottom electrode through simulation and optimization, which forms a special LC lens with an Archimedean spiral electrode, realizing a 3D LC wedge and an arbitrarily movable LC lens. When only the bottom electrode is controlled, it achieves a maximum beam steering angle of 0.164°, which is nearly an order of magnitude larger than the current design. When the top and bottom electrodes are controlled jointly, a 0.164° movement of the lens optical axis is achieved. With focal length varies, the movement of the optical axis ranges from zero to infinity, and the lens surface remains unchanged during movement. The focus can move in a 3D conical area. When the thickness of the LC layer is 30 μm, the fastest response time reaches only 0.635 s, much faster than now. Full article

Amphibious robots have broad prospects in the fields of industry, defense, and transportation. To improve the propulsion performance and reduce operation complexity, a novel bionic amphibious robot, namely AmphiFinbot-II, is presented in this paper. The swimming and walking components adopt a compound drive mechanism, enabling simultaneous control for the rotation of the track and the wave-like motion of the undulating fin. The robot employs different propulsion methods but utilizes the same operation strategy, eliminating the need for mode switching. The structure and the locomotion principle are introduced. The performance of the robot in different motion patterns was analyzed via computational fluid dynamics simulation. The simulation results verified the feasibility of the wave-like swimming mechanism. Physical experiments were conducted for both land and underwater motion, and the results were consistent with the simulation regulation. Both the underwater linear and angular velocity were proportional to the undulating frequency. The robot’s maximum linear speed and steering speed on land were 2.26 m/s (2.79 BL/s) and 442°/s, respectively, while the maximum speeds underwater were 0.54 m/s (0.67 BL/s) and 84°/s, respectively. The research findings indicate that the robot possesses outstanding amphibious motion capabilities and a simplistic yet unified control approach, thereby validating the feasibility of the robot’s design scheme, and offering a novel concept for the development of high-performance and self-contained amphibious robots. Full article

Currently, key factors hindering application of steer-by-wire systems are their inadequate safety and reliability, which are significant criteria for evaluating automotive active safety. Based on the steer-by-wire platform, a dual-redundant steering motor control system is proposed, featuring dual three-phase permanent magnet synchronous motors as execution motors, achieving redundancy from hardware. A torque vector-space-decoupling control method is introduced for these motors to ensure balanced and stable torque output. Upon a fault, fault-tolerant measures are taken by disconnecting power supply to the affected motor, which, despite reducing system functionality, allows for normal steering control. This research starts with modeling the dual three-phase motors to construct a simulation model. It then proceeds with hardware-in-the-loop testing integrated with the dual-redundancy steer-by-wire control system, conducting tests under dual-lane-change trajectory conditions. Finally, a steering system fault is simulated to assess fault handling and functional degradation. These experiments confirmed that the proposed method enabled balanced torque output from the dual three-phase motors in the redundant steering control and facilitated fault-tolerant processing post fault, ensuring the vehicle’s steering functions were maintained. Full article

Aiming at the problem of multiple constraints and low solving efficiency in the process of vehicle path tracking, an improved hp-adaptive Radau pseudospectral method (I-hp-ARPM) which uses a double-layer optimization iteration strategy and the residual of differential algebraic constraints at sampling points with a Gaussian distribution as the error evaluation criterion is proposed. Firstly, a four-DOF vehicle motion model is established. Secondly, on the basis of establishing algebraic differential constraints and path constraints and satisfying the optimization objective function, the I-hp-ARPM is used to transform the optimal control problem (OCP) into a general nonlinear programming problem for solution. Finally, the effectiveness of the proposed method is verified compared with the traditional hp-adaptive pseudospectral method. The simulation results and the virtual test show that there are peak values at 3.5 s and 4.8 s, as well as 6 s, for both the steering wheel angle and the sideslip angle with the condition of $\mu$ = 0.8. And also, there are peak values at the times of 3.5 s and 5.5 s, as well as 7.5 s, with the condition of $\mu$ = 0.4. This indicates the vehicle can track the reference path well with the control of the proposed algorithm. Both the initial and final constraints, as well as the path constraint, meet the requirements. The proposed method can generate the optimal trajectory that meets various constraint requirements. This method provides a design basis for path tracking of autonomous vehicles and has significance in engineering. Full article

Direct yaw moment control (DYC) and differential drive-assist steering (DDAS) for distributed-drive vehicles are both realized by allocating the in-wheel motor torque. To address the interference caused by overlapping control objectives, this paper proposes a multilayer control strategy that integrates DYC and DDAS, consisting of an upper controller, a coordinated decision layer, and a torque distribution layer. The upper controller, designed based on the vehicle’s dynamic characteristics, incorporates an adaptive fuzzy control DYC system and a dual PID control DDAS system. The coordinated decision layer is developed utilizing a phase-plane dynamic weighting method, delineating region boundaries by applying the double-line and limit cycle methods. The torque distribution strategy is formulated considering motor peak torque and road adhesion conditions. Multi-condition joint simulation experiments indicate that the proposed multilayer control strategy, integrating the advantages of DYC and DDAS, reduces peak steering wheel torque by approximately 10%, peak yaw rate by around 25%, peak sideslip angle by roughly 29%, and peak sideslip angle rate by about 19%, significantly improving driving stability and maneuvering flexibility. Full article

The development of autonomous agricultural robots using a global navigation satellite system aided by real-time kinematics and an inertial measurement unit for position and orientation determination must address the accuracy, reliability, and cost of these components. This study aims to develop and evaluate a robotic platform with autonomous navigation using low-cost components. A navigation algorithm was developed based on the kinematics of a differential vehicle, combined with a proportional and integral steering controller that followed a point-to-point route until the desired route was completed. Two route mapping methods were tested. The performance of the platform control algorithm was evaluated by following a predefined route and calculating metrics such as the maximum cross-track error, mean absolute error, standard deviation of the error, and root mean squared error. The strategy of planning routes with closer waypoints reduces cross-track errors. The results showed that when adopting waypoints every 3 m, better performance was obtained compared to waypoints only at the vertices, with maximum cross-track error being 44.4% lower, MAE 64.1% lower, SD 39.4% lower, and RMSE 52.5% lower. This study demonstrates the feasibility of developing autonomous agricultural robots with low-cost components and highlights the importance of careful route planning to optimize navigation accuracy. Full article

The study proposes an active trailer steering control method for tractor semitrailers to promote the path tracking effect of the trailer portion as well as lateral stability during lane changing. Firstly, a simplified model of a tractor semitrailer is constructed, and the MAP map is formed based on the genetic algorithm for the identification of the key parameters, which improves the model’s accuracy. Then the tractor and trailer’s yaw rate and sideslip angle at CG are tracked as the control objective and the trailer angle distribution strategy is given. Then the LQR-based corner controller is designed to control the steering actuators of each axle of the trailer. Finally, the effectiveness of the designed control strategy is verified based on the Trucksim/Simulink joint simulation platform and the semi-physical HiL test platform. The simulation results show that the designed controller can effectively improve the path tracking effect of the tractor and the trailer, and at the same time, the lateral stability parameters of the tractor and the trailer are also significantly improved, which improves the driving stability of the tractor semitrailer. Full article

Autonomous vehicles frequently encounter performance degradation during high-speed cornering due to excessive speed and lateral acceleration, potentially leading to collisions or rollovers. This paper proposes a novel curve-passing control approach that first estimates the curve radius and then controls the steer and speed for smooth and comfortable handling. In particular, the curve radius is innovatively estimated using a combination of a camera-based lane detection model and a steering wheel dynamic model. The curve-passing control approach is validated on high-speed ramps and curves, demonstrating its robustness and intelligence to adapt to dynamic changes in curve curvature. The model effectively prevents vehicles from entering curves at dangerously high speeds from straight roads and mitigates sudden accelerations or decelerations when entering curves. Experimental results indicate that the vehicle speed is reduced to around 50 km/h and the corresponding acceleration is −0.6 m/s² upon entering curves with a minimum radius of 150 m. This demonstrates that the proposed control model can ensure a comfortable and safe driving experience by autonomously decelerating the vehicle before entering various types of curves. Full article

Steering wheel angle is an important and essential parameter of the navigation control of autonomous wheeled vehicles. At present, the combination of rotary angle sensors and four-link mechanisms is the main sensing approach for steering wheel angle with high measurement accuracy, which is widely adopted in autonomous agriculture vehicles. However, in a complex and challenging farmland environment, there are a series of prominent problems such as complicated installation and debugging, spattered mud blocking the parallel four-bar mechanism, breakage of the sensor wire during operation, and separate calibrations for different vehicles. To avoid the above problems, a novel dynamic measurement method for steering wheel angle is presented based on vehicle attitude information and a non-contact attitude sensor. First, the working principle of the proposed measurement method and the effect of zero position error on measurement accuracy and path tracking are analyzed. Then, an optimization algorithm for zero position error of steering wheel angle is proposed. The experimental platform is assembled based on a 2ZG-6DM rice transplanter by software design and hardware modification. Finally, comparative tests are conducted to demonstrate the effectiveness and priority of the proposed dynamic sensing method. Experimental results show that the average absolute error of the straight path is 0.057° and the corresponding standard deviation of the error is 0.483°. The average absolute error of the turning path is 0.686° and the standard deviation of the error is 0.931°. This implies the proposed dynamic sensing method can accurately realize the collection of the steering wheel angle. Compared to the traditional measurement method, the proposed dynamic sensing method greatly improves the measurement reliability of the steering wheel angle and avoids complicated installation and debugging of different vehicles. The separate calibrations for different vehicles are not needed since the proposed measurement method is not dependent on the kinematic models of the vehicles. Given that the attitude sensor can be installed at a higher position on the wheel, sensor damage from mud blocking and the sensor wire breaking is also avoided. Full article

This study investigated the impact of Rheum palmatum root (RP) for reducing methane and its impact on rumen fermentation and blood metabolites in cattle. Rumen fluid was collected from three cannulated steers (736 ± 15 kg) and mixed with buffer (1:3 ratio) for the in vitro trial. Treatments were divided into control and RP supplement groups (1%, 3%, and 5% of substrates), with each sample incubated at 39 °C for 24 and 48 hours. Methane was measured after incubation, showing a dose-dependent linear decrease after 48 hours. Quadratic changes were observed in total volatile fatty acids, acetate, and butyrate. Additionally, in vitro dry matter digestibility decreased linearly with RP inclusion. In vivo trials involved four Korean steers in a 2 × 2 crossover design over 3 weeks, with treatments including a control group and a group with 3% RP addition. Dry matter intake (DMI) tended to decrease in the RP group compared to the control. Methane emissions (g/kg DMI) were not affected by RP addition. Blood metabolites indicated higher lipase concentrations in the RP group. In conclusion, RP reduced methane production in the in vitro trial but had no effect in the in vivo trial, likely due to adaptation of ruminal bacteria to RP. Full article

With the popularity of carbon-free vehicle obstacle avoidance races, the requirements for the accuracy and reliability of vehicle motion control are getting higher and higher. Aiming at the problems of trajectory deviation and debugging difficulties of the carbon-free vehicle during the movement process, the Revolute-Slider-Slider-Revolute (RSSR) mechanism is adopted as the steering device, which is aimed at improving the motion control precision and obstacle avoidance ability of the vehicle. Firstly, from the kinematics point of view, a kinematics model based on the spatial four-link mechanism is established, and the influence of each parameter change on the trajectory of the vehicle is analyzed. On this basis, the influence of each key parameter on the motion process is further explored through practical debugging, so as to derive a general law of the vehicle’s motion under the drive of the RSSR mechanism. Through numerical simulation analysis, the accuracy of the theoretical model is verified, and the structural design of the vehicle is optimized accordingly. The actual debugging results show that the vehicle can realize smooth operation, which fully proves the practicality and effectiveness of the established mathematical model and the research of the RSSR mechanism. Full article

This research introduces an innovative approach for End-to-End steering angle prediction and its control in electric power steering (EPS) systems. The methodology integrates transfer learning-based computer vision techniques for prediction and control with fuzzy signatures-enhanced fuzzy systems. Fuzzy signatures are unique multidimensional data structures that represent data symbolically. This enhancement enables the fuzzy systems to effectively manage the inherent imprecision and uncertainty in various driving scenarios. The ultimate goal of this work is to assess the efficiency and performance of this combined approach by highlighting the pivotal role of steering angle prediction and control in the field of autonomous driving systems. Specifically, within EPS systems, the control of the motor directly influences the vehicle’s path and maneuverability. A significant breakthrough of this study is the successful application of transfer learning-based computer vision techniques to extract respective visual data without the need for large datasets. This represents an advancement in reducing the extensive data collection and computational load typically required. The findings of this research reveal the potential of this approach within EPS systems, with an MSE score of 0.0386 against 0.0476, by outperforming the existing NVIDIA model. This result provides a 22.63% better Mean Squared Error (MSE) score than NVIDIA’s model. The proposed model also showed better performance compared with all other three references found in the literature. Furthermore, we identify potential areas for refinement, such as decreasing model loss and simplifying the complex decision model of fuzzy systems, which can represent the symmetry and asymmetry of human decision-making systems. This study, therefore, contributes significantly to the ongoing evolution of autonomous driving systems. Full article

With the increase in population, it is increasingly necessary to produce food more efficiently. This has expanded the market for additives, which are products that directly (nutritional effect) or indirectly (effect on animal health) favor productivity. Guanidinoacetic acid (GAA) is a natural precursor of creatine. It acts as an energy reserve in skeletal muscle. In addition to being a compound with more significant bioavailability, it is more thermally stable and less expensive than creatine. Therefore, this study aimed to determine whether adding GAA to the cattle diet would alter the meat’s composition and fatty acid profile. We used 24 Holstein cattle males (409 ± 5.6 kg), approximately 15 months old, and separated them into four homogeneous groups, one being the control group and three groups with various dosages of GAA in the diets (3.3; 6.6, and 9.9 g/animal/day), for an experimental period of 60 days. Blood, rumen fluid, and animal weighing were performed at three points (days 1, 30, and 60), and daily feed consumption was measured. Steers fed with GAA (9.9 g/d) showed a 16.9% increase in average daily gain (ADG) compared to the control group. These same animals (T-9.9 group) fed with GAA showed a 20% increase in fed efficiency compared to the control group. Lower leukocyte, lymphocyte, and granulocyte counts and lower cholesterol levels were observed in animals that consumed 6.6 g and 9.9 g/d GAA compared to the control group. Animals from the T-6.6 and T-9.9 groups showed 30% and 27.6% reduced bacterial activity in the rumen compared to the control group, respectively. Steers from the T-6.6 and T-9.9 groups fed with GAA showed a 20% and 37% increase in short-chain fatty acids (SCFAs) compared to the control group, respectively. A higher concentration of acetic, propionic, and butyric acids in the ruminal fluid of cattle T-9.9 group was observed at day 60. The two highest doses of GAA showed lower fat levels in the meat, just as the cattle that received 9.9 g/d showed higher levels of total polyunsaturated fatty acids. Complementary data results draw attention to the dose of 9.9 g/d GAA in cattle diets, as anti-inflammatory action can be seen and combined with a higher concentration of SCFAs, consequently increases weight gain. We concluded that consuming this GAA increases the concentration of some unsaturated fatty acids (omegas) in the meat, which adds quality to the product for the consumer. Full article

This paper introduces a novel fuzzy logic switched model predictive control (MPC) algorithm for articulated steering vehicles, addressing significant path tracking challenges due to varying road conditions and vehicle speeds. Traditional single-model and parameter-based controllers struggle with tracking errors and computational inefficiencies under diverse operational conditions. Therefore, a kinematics-based MPC algorithm is first developed, showing strong real-time performance but encountering accuracy issues on low-adhesion surfaces and at high speeds. Then, a 4-DOF dynamics-based MPC algorithm is designed to enhance tracking accuracy and control stability. The proposed solution is a switched MPC strategy, integrating a fuzzy control system that dynamically switches between kinematics-based and dynamics-based MPC algorithms based on error, solution time, and heading angle indicators. Subsequently, simulation tests are conducted using SIMULINK and ADAMS to verify the performance of the proposed algorithm. The results confirm that this fuzzy-based MPC algorithm can effectively mitigate the drawbacks of single-model approaches, ensuring precise, stable, and efficient path tracking across diverse adhesion road conditions. Full article

This study employed the new generation Taiwan global forecast system (TGFS) to focus on its performance in forecasting the tracks of western North Pacific typhoons during 2022–2023. TGFS demonstrated better forecasting performance in typhoon track compared to central weather administration (CWA) GFS. For forecasts with large track errors by TGFS at the 120th h, it was found that most of them originated during the early stages of typhoon development when the typhoons were of mild intensity. The tracks deviated predominantly towards the northeast and occasionally towards the southwest, which were speculated to be due to inadequate environmental steering guidance resulting from the failure to capture synoptic environmental features. The tracks could be corrected by replacing the original new simplified Arakawa–Schubert (NSAS) scheme with the new Tiedtke (NTDK) scheme to change the synoptic environmental field, not only for Typhoon Khanun, which occurred in the typhoon season of 2023, but also for Typhoon Bolaven, which occurred after the typhoon season, in October 2023, under atypical circulation characteristics over the western Pacific. The diagnosis of vorticity budget primarily analyzed the periods where divergence in typhoon tracks between control (CTRL) and NTDK experiments occurred. The different synoptic environmental fields in the NTDK experiment affected the wavenumber-1 vorticity distribution in the horizontal advection term, thereby enhancing the accuracy of typhoon translation velocity forecasts. This preliminary study suggests that utilizing the NTDK scheme might improve the forecasting skill of TGFS for typhoon tracks. To gain a more comprehensive understanding of the impact of NTDK on typhoon tracks, further examination for more typhoons is still in need. Full article