Search Results (29)

This paper proposes a modular control framework for high-order nonlinear multi-agent systems (MASs) to achieve distributed finite-time formation tracking with a prescribed performance. The design integrates two modules to address uncertainties and safety constraints simultaneously. Module I—Prescribed Performance-Based Trajectory Generation: A virtual signal generator constructs collision/connectivity-aware reference trajectories by encoding time-varying performance bounds into formation errors. It ensures network rigidity and optimal formation convergence through dynamic error transformation. Module II—Anti-disturbance Tracking Control: A finite-time extended state observer (FTESO) estimates and compensates for uncertainties within a finite time, while a time-varying surface controller drives tracking errors into predefined performance funnels. This module guarantees rapid error convergence without violating the transient constraints from Module I. The simulations verified the accelerated formation reconfiguration under disturbances, and thus, demonstrated improved robustness and convergence over asymptotic approaches. The framework offers a systematic solution for safety-critical MAS coordination with heterogeneous high-order dynamics. Full article

Active magnetic bearings (AMBs) are a class of electromechanical equipment that effectively integrate Magnetic Bearing technology with PMSM technology, particularly for applications involving high-power and high-speed permanent magnet motors. However, as the rotor operates in a suspended state, the motor’s trajectory changes continuously. The installation of a speed sensor poses a risk of collisions with the shaft, which inevitably leads to rotor damage due to imbalance, shaft wear, or other mechanical effects. Consequently, for the rotor control system of PMSM, it is crucial to adopt a sensorless speed estimation method to achieve high-performance speed and position closed-loop control. This study uses the rotor system of a 75 kW AMB high-speed motor as a case study to provide a detailed analysis of the principles of high-frequency square wave signal injection (HFSWSII) and current signal injection for speed estimation. The high-frequency current response signal is derived, and a speed observer is designed based on signal extraction and processing methods. Subsequently, a speed estimation model for PMSM is constructed based on HFSWSII, and the issue of “filter bandwidth limitations and lagging effects in signal processing” within the observer is analyzed. A scheme based on the high-frequency pulse array current injection method is then proposed to enhance the observer’s performance. Finally, to assess the system’s anti-interference capability as well as the motor’s static and dynamic tracking performance, its dynamic behavior is tested under conditions of increasing and decreasing speed and load. Simulation and experimental results demonstrate that the PMSM control system based on HFSWSII achieves accurate speed estimation and shows excellent static and dynamic performance. Full article

Current methods for designing three-dimensional trajectories rarely account for complex formation constraints, focusing primarily on geometric relationships. However, trajectory adjustments are often necessary during drilling operations. These field adjustments typically lack systematic optimization, resulting in suboptimal trajectories. This study introduces a novel trajectory optimization framework that integrates formation fitness for curve construction and proactive anti-collision trajectory adjustment (PACTA). The framework begins by incorporating PACTA and optimizing the initial trajectory to minimize total measured depth (TMD) using a genetic algorithm. Subsequently, a second optimization phase identifies curve sections passing through formations with low build-up fitness, automatically splitting them into combinations of curves and straight lines. Dynamic trajectory equations are then constructed based on these adjustments, and the final trajectory is optimized accordingly. Case studies demonstrate that the proposed method effectively adjusts curve positions in the presence of multiple formations with low build-up fitness while avoiding wellbore collisions. The approach achieves an average 10% reduction in total drilling time when minimizing TMD and an average 19.7% reduction in drillstring torque when torque minimization is prioritized. This new trajectory design method is expected to significantly reduce well construction costs. Full article

The installation distance between the speed sensor of the traditional rolling or sliding bearing permanent magnet synchronous motor and the rotor was very close, and the rotor of the magnetic levitation motor supported by Active Magnetic Bearings (AMBs) was in suspension. When the motor was running at high speed, the radial trajectory of the rotor changed all the time. The same frequency vibration caused by the unbalanced mass of the rotor made it easy to cause mechanical collision between the sensor and the rotor, resulting in direct damage of the sensor. Therefore, the sensorless speed estimation method was needed for the rotor control system of the magnetic levitation motor (MLM) to achieve high performance closed-loop control of speed and position. More importantly, in order to control or compensate the unbalanced force of the electromagnetic bearing rotor system, the rotor rotation speed signal should be obtained as accurately as possible. Therefore, the principle of adaptive sliding mode observer (SMO) was analyzed in detail by taking the rotor system of MLM as an example. Then, the sliding mode surface was designed, the speed estimation algorithm based on adaptive SMO was derived, and the stability analysis was completed. Finally, in order to verify the anti-disturbance performance of the system and the static and dynamic tracking performance of the motor, the dynamic performance was verified by increasing and decreasing the speed and load. The results showed that the speed estimation method based on adaptive SMO could achieve accurate speed estimation and had good static and dynamic performance. Full article

Trajectory prediction is critical for ensuring the safety, reliability, and scalability of Unmanned Aerial Vehicle (UAV) in urban environments. Despite advances in deep learning, existing methods often struggle with dynamic UAV conditions, such as rapid directional changes and limited forecasting horizons, while lacking comprehensive real-time validation and generalization capabilities. This study addresses these challenges by proposing a gated recurrent unit (GRU)-based deep learning framework optimized through Look_Back and Forward_Length labeling to capture complex temporal patterns. The model demonstrated state-of-the-art performance, surpassing existing unmanned aerial vehicles (UAV) and aircraft trajectory prediction approaches, including FlightBERT++, in terms of both accuracy and robustness. It achieved reliable long-range predictions up to 4 s, and its real-time feasibility was validated due to its efficient resource utilization. The model’s generalization capability was confirmed through evaluations on two independent UAV datasets, where it consistently predicted unseen trajectories with high accuracy. These findings highlight the model’s ability to handle rapid maneuvers, extend prediction horizons, and generalize across platforms. This work establishes a robust trajectory prediction framework with practical applications in collision avoidance, mission planning, and anti-drone systems, paving the way for safer and more scalable UAV operations. Full article

For multi-obstacle complex scenarios, the traditional artificial potential field method suffers from the defects of potential field imbalance, its capability to easily fall into the local minima, and encounter unreachable targets in complex navigation environments. Therefore, this paper proposes a three-dimensional adaptive potential field algorithm (SAPF) based on multi-agent reinforcement learning. First, in this paper, the gravitational function in the artificial potential field (APF) is modified to weaken the gravitational effect on the UAV in the region far away from the target point in order to reduce the risk of collision between the UAV and the obstacles during the moving process. Second, in the region close to the target point, this paper improves the artificial potential field function to ensure that the UAV can reach the target point smoothly and realize path convergence by considering the relative distance between the UAV’s current position and the target point. Finally, for the characteristics of UAV trajectory planning, a 3D state space is designed based on the 3D coordinates of the UAV, the distance between the UAV and the nearest obstacle, and the distance between the UAV and the target point; an action space is designed based on the displacement increment of the UAV in the three coordinate axes; and the specific formulas for collision penalties and path optimization rewards are re-designed, which effectively avoids the UAV from entering the local minimal points. The experimental results show that the artificial potential field method designed with reinforcement learning can plan shorter paths and exhibit better planning results. In addition, the method is more adaptable in complex scenes and has better anti-interference. Full article

The robotic arm is a critical component of modern industrial manufacturing. However, its positioning performance can be hindered by overshooting and oscillation. External disturbances, including collisions or impacts with other objects, can also affect its accuracy and precision. To resolve this problem, this work integrates a compact magnetorheological (MR) bearing, which is capable of switching between locking and unlocking states utilizing the MR effect, into the gearbox of the actuation system of the robotic arm. This integration enables the gearbox (referred to as the MR gearbox) to exhibit variable damping characteristics. This controllable damping property will play an important role in improving the positioning accuracy by offering additional damping. In this study, the MR gearbox was first designed and prototyped. A characterization test was then conducted to verify its variable damping property. The classic Bouc–Wen model was used to describe the MR gearbox and then a mathematical model was established for the whole robotic arm. Additionally, a new variable damping control method was proposed for further improving the positioning precision and reducing energy consumption. As follows, the positioning and the anti-disturbance performances of the robotic arm system installed with the MR gearbox were assessed through numerical simulations and experimental tests. The result shows that the robotic arm under the new control method achieves reductions of 11.76% in overshoot, 14.73% in settling time, and 26.1% in energy consumption compared to the uncontrolled case under the step trajectory, indicating improved positioning performance. Full article

During performing multiple tasks of a redundant manipulator, the obstacles affect the sequential order of task areas and the joint trajectories. The end-effector is constrained to visit multiple task areas with an optimal anti-collision path, while the joints are required to move smoothly and avoid predefined obstacles. A special encoding genetic algorithm (SEGA) is proposed for multitask-based anti-collision trajectory planning. Firstly, the spatial occupancy relationship between obstacles and manipulator is developed utilizing the theory of spherical enclosing box and spatial superposition. The obstacles are detected according to the relative position relationship between linear segments and spheres. Secondly, each joint trajectory between adjacent task areas is depicted with a sixth-degree polynomial. Additionally, each joint trajectory is improved via optimizing the unknown six-order coefficient. By searching for optimal sequential order of task areas, optimal collision detection results, and optimal joint trajectories, the multitask-based anti-collision trajectory planning problem is transformed into a parameter optimization problem. In SEGA, the cost function consists of two parts, including the end-effector path length and the variation of joint angles. Moreover, each chromosome consists of three categories of genes, including the sequential order of task areas, the sequential order of joint configurations corresponding to task areas, and the unknown coefficients for anti-collision joint trajectories. Finally, numerical simulations are carried out to verify the proposed method. Full article

The existing trajectory planning research mainly considers the safety of the obstacle avoidance process rather than the anti-rollover requirements of heavy vehicles. When there are driving risks such as rollover and collision, how to coordinate the game relationship between the two is the key technical problem to realizing the anti-rollover trajectory planning under the condition of driving risk triggering. Given the above problems, this paper studies the non-cooperative game model construction method of the obstacle avoidance process that integrates the vehicle driving risk in a complex traffic environment. Then it obtains the obstacle avoidance area that satisfies both the collision and rollover profit requirements based on the Nash equilibrium. A Kmeans-SMOTE risk clustering fusion is proposed in this paper, in which more sampling points are supplemented by the SMOTE oversampling method, and then the ideal obstacle avoidance area is obtained through clustering algorithm fusion to determine the optimal feasible area for obstacle avoidance trajectory planning. On this basis, to solve the convergence problems of the existing multi-objective particle swarm optimization algorithm and analyze the influence of weight parameters and the diversity of the optimization process, this paper proposes an anti-rollover trajectory planning method based on the improved cosine variable weight factor MOPSO algorithm. The simulation results show that the trajectory obtained based on the method proposed in this paper can effectively improve the anti-rollover performance of the controlled vehicle while avoiding obstacles. Full article

In this paper, with the frequent occurrence of ship–bridge collision accidents as the context and the collision accident of the Lixinsha Bridge in China as the background, the scenario of a ship impacting a pier was simulated using ANSYS-FLUENT software, and the practical application possibility of the high-pressure water jet interference (HPWJI) anti-collision method was thoroughly investigated. Through the simulation analysis, the effectiveness of a high-pressure water jet with a total flow rate of 45 m³/s in altering the navigation direction of large-tonnage (2000 t) ships and avoiding obstacles was verified. Additionally, its impact on the stress of the ship steel plates and navigation status was also explored. It was found that, with reasonable layout and parameter adjustment, the high-pressure water jet technology could effectively intervene in the ship’s navigation trajectory while ensuring the structural safety of the ship, with minimal impact on the ship’s navigation stability and passenger comfort. Furthermore, the injection angle of the high-pressure water jet had a significant impact on the deflection and deceleration of the ship. Specifically, when the water jet impacted the ship along its forward direction, it could effectively increase the ship’s deceleration and deflection time, reducing the speed from 2.55 m/s to 1.7 m/s, a decrease of approximately 33%, significantly enhancing collision prevention effectiveness. This research provides important guidance for the practical application of high-pressure water jet collision prevention technology and is of great significance for improving the safety of waterway transportation. Full article

The following article presents the task of optimizing the control of an autonomous object within a group of other passing objects using Pontryagin’s bounded maximum principle. The basis of this principle is a multidimensional nonlinear model of the control process, with state constraints reflecting the motion of passing objects. The analytical synthesis of optimal multi-object control became the basis for the algorithm for determining the optimal and safe object trajectory. Simulation tests of the algorithm on the example of real navigation situations with various numbers of objects illustrate their safe trajectories in changing environmental conditions. The optimal object trajectory obtained using Pontryagin’s maximum principle was compared with the trajectory calculated using the Bellman dynamic programming method. The analysis of the research allowed for the formulation of valuable conclusions and a plan for further research in the field of autonomous vehicle control optimization. The maximum principle algorithm allows one to take into account a larger number of objects whose data are derived from ARPA anti-collision radar systems. Full article

Compared to terrestrial transportation systems, the expansion of urban traffic into airspace can not only mitigate traffic congestion, but also foster establish eco-friendly transportation networks. Additionally, unmanned aerial vehicle (UAV) task allocation and trajectory planning are essential research topics for an Urban Air Mobility (UAM) scenario. However, heterogeneous tasks, temporary flight restriction zones, physical buildings, and environment prerequisites put forward challenges for the research. In this paper, multigene and improved anti-collision RRT* (IAC-RRT*) algorithms are proposed to address the challenge of task allocation and path planning problems in UAM scenarios by tailoring the chance of crossover and mutation. It is proved that multigene and IAC-RRT* algorithms can effectively minimize energy consumption and tasks’ completion duration of UAVs. Simulation results demonstrate that the strategy of this work surpasses traditional optimization algorithms, i.e., RRT algorithm and gene algorithm, in terms of numerical stability and convergence speed. Full article

The micromechanical mechanism of pipe instability under lateral force actions on sloping sandy seabeds is unclear. This study investigated the effects of slope angle and instability direction (upslope or downslope) on pipe–soil interaction instability for freely laid and anti-rolling pipes using coupled discrete element method and finite element method (DEM–FEM) simulations. The numerical results were analyzed at both macro- and microscales and compared with the experimental results. The findings revealed that the ultimate drag force on anti-rolling pipes increased with slope angle and was significantly larger than that on freely laid pipes for both downslope and upslope instabilities. Additionally, the rotation-induced upward traction force was proved to be the essential reason for the smaller soil deformation around freely laid pipes. Moreover, the shape differences in the motion trajectories of pipes were successfully explained by variations in the soil supporting force distributions under different slope conditions. Additionally, synchronous movement between the pipe and adjacent particles was identified as the underlying mechanism for the reduced particle collision and shear wear on pipe surfaces under a high interface coefficient. Furthermore, an investigation of particle-scale behaviors revealed conclusive mechanistic patterns of pipe–soil interaction instability under different slope conditions. This study could be useful for the design of pipelines in marine pipeline engineering. Full article

SiC devices have been typically subjected to extreme environments and complex stresses during operation, such as intense radiation and large diurnal amplitude differences on the lunar surface. Radiation displacement damage may lead to degradation or failure of the performance of semiconductor devices. In this paper, the effects of temperature and incidence angle on the irradiation cascade effect of 6H-SiC were investigated separately using the principles of molecular dynamics. Temperatures were set to 100 K, 150 K, 200 K, 250 K, 300 K, 350 K, 400 K and 450 K. The incidence direction was parallel to the specified crystal plane, with angles of 8°, 15°, 30°, 45°, 60° and 75° to the negative direction of the Z-axis. In this paper, the six types of defects were counted, and the microscopic distribution images and trajectories of each type of defect were extracted. The results show a linear relationship between the peak of the Frenkel pair and temperature. The recombination rate of Frenkel pairs depends on the local temperature and degree of aggregation at the center of the cascade collision. Increasing the angle of incidence first inhibits and then promotes the production of total defects and Frenkel pairs. The lowest number of total defects, Frenkel pairs and antisite defects are produced at a 45° incident angle. At an incidence angle of 75°, larger size hollow clusters and anti-clusters are more likely to appear in the 6H-SiC. Full article

This paper introduces a novel high-certainty visual servo algorithm for a space manipulator with flexible joints, which consists of a kinematic motion planner and a Lyapunov dynamics model reference adaptive controller. To enhance kinematic certainty, a three-stage motion planner is proposed in Cartesian space to control the intermediate states and minimize the relative position error between the manipulator and the target. Moreover, a planner in joint space based on the fast gradient descent algorithm is proposed to optimize the joint’s deviation from the centrality. To improve dynamic certainty, an adaptive control algorithm based on Lyapunov stability analysis is used to enhance the system’s anti-disturbance capability. As to the basic PBVS (position-based visual servo methods) algorithm, the proposed method aims to increase the certainty of the intermediate states to avoid collision. A physical experiment is designed to validate the effectiveness of the algorithm. The experiment shows that the visual servo motion state in Cartesian space is basically consistent with the planned three-stage motion state, the average joint deviation index from the centrality is less than 40%, and the motion trajectory consistency exceeds 90% under different inertial load disturbances. Overall, this method reduces the risk of collision by enhancing the certainty of the basic PBVS algorithm. Full article