Search Results (7,692)

To address the strongly nonlinear hydrodynamic coupling and complex maneuvering challenges encountered by large ships during berthing operations in restricted waters, this paper proposes a high-precision autonomous berthing control system incorporating four-quadrant propeller hydrodynamics. Based on an improved Mathematical Maneuvering Group (MMG) framework, a three-degree-of-freedom (3-DOF) dynamic model is established to accurately capture the transient thrust and torque mappings of the propeller over all four quadrants. A dynamic line-of-sight (LOS) guidance system with a nonlinearly decaying acceptance radius is tightly coupled with PD/PI controllers to coordinate and regulate the rudder angle and propeller rotational speed. The numerical solver was rigorously validated against turning-test data for the S-175 container ship, with the errors of the key parameters all controlled within 15%. Subsequently, under the environmental conditions of Yangshan Port, full-condition path-planning and berthing simulations were conducted for the novel B-573 container ship under steady-current disturbances with multiple intensity levels (0 to 1.5 m/s) and multiple flow directions. Quantitative evaluation shows that, under the highly challenging current condition of 1.0 m/s, the dynamic corrective mechanism effectively drives the global mean absolute error (MAE) to converge to 85.50 m, representing a 62% statistical reduction relative to the transient peak value. In addition, a parameter sensitivity analysis based on the cumulative cross-track error confirms that, when subject to variations in the underlying hydrodynamic parameters, the proposed system can suppress fluctuations in trajectory error to a very low level, thereby demonstrating a certain degree of control robustness. During the terminal berthing stage, the vessel smoothly completed an extreme deceleration from an initial speed of 6.4 m/s to a full stop within 588 s, while constraining the maximum astern rotational speed to −2 rps and seamlessly passing through all four propeller quadrants. The results confirm that the proposed autopilot framework possesses a certain degree of engineering feasibility in complex maritime environments. Full article

Offshore wind turbine operation and maintenance in complex sea states is influenced by the coupled effects of low-frequency vessel drift and high-frequency wave-induced disturbances. In practical operations, the ship dynamic positioning system primarily regulates low-frequency motion through vessel position control, whereas a boarding compensation system is required to attenuate high-frequency six-degrees-of-freedom motions to ensure safe personnel transfer. This study establishes coupled kinematic mapping among the ship dynamic positioning system, the Stewart platform, and a three-degrees-of-freedom gangway and proposes a hierarchical cooperative control architecture. At the upper layer, an extended Kalman filter and an exponential moving average low-pass filter are employed for online state estimation and for separating low-frequency and high-frequency components. A Kalman filter lookahead predictor is then used to generate a short-horizon prediction of the high-frequency component and to construct a feedforward reference signal. At the middle layer, the feedforward reference and the gangway end error feedback are coordinated at the velocity level, and a quadratic programming-based allocation strategy distributes compensation tasks between the Stewart platform and the gangway under safety-related constraints, including actuator stroke limits and singularity avoidance. At the lower layer, a robust feedback controller is designed for the gangway to mitigate modeling uncertainties and environmental disturbances and to ensure stable tracking. MATLAB R2024a-based simulations under representative wave conditions demonstrate that the proposed architecture improves end effector tracking accuracy and closed-loop stability compared with baseline strategies, providing a feasible engineering solution for shipboard boarding operations in complex sea states. Full article

Synthetic aperture radar (SAR) ship detection is severely limited by the artifacts caused by motion. Due to the complex six-degree-of-freedom (6-DOF) motion of ships, the ship imaging exhibits aberration phenomena including spatial blurring, discrete ghosting, and Lorentz linear blurring. Traditional detectors rely on the identification of static spatial features. When the phase coherence is disrupted, they tend to fail. To overcome this problem, we propose a multimodal fusion framework based on physical principles. This framework establishes a theoretical connection between the ship hydrodynamic response and imaging degradation through short, long, and ultra-long coherence processing intervals (CPI). The framework adopts a cascaded architecture: first, a lightweight YOLOv8 performs rapid global screening, followed by a signal backtracking mechanism that extracts high-fidelity time-frequency domain (TFD) and range instantaneous Doppler (RID) features from the original distance compressed data. In the second-level detection, these physical features are adaptively fused with spatial intensity through a YOLOv8 network integrated with the convolutional block attention module (CBAM) to reduce the false detection rate. The validation on high-fidelity simulations and real GF-3 datasets shows that this method consistently achieves an average precision (mAP) of over 95%, outperforming several widely used detectors, and demonstrates strong generalization ability in extreme imaging conditions, suitable for maritime detection scenarios. Full article

The paper examines the poetics of graphomania as a productive aesthetic device within the Russian literary tradition, focusing primarily on Velimir Khlebnikov and extending the analysis to figures such as Fedor Dostoevsky’s Captain Lebyadkin and real authors such as Eduard Limonov, Dmitrii Prigov, and Sasha Sokolov. Building on the article’s central insight that Khlebnikov’s “bad writing,” stylistic shifts, and violations of canonical norms constitute not a defect but a sui generis artistic strategy, the study situates these techniques within broader historical and theoretical frameworks, including the Formalist concepts of parody, junior branch, and heteroglossic subcodes of poetic culture. The article traces the way Khlebnikov’s dynamic alternation of heterogeneous linguistic, prosodic, and generic registers produces a complex, unstable but grandstanding authorial “I” aligned with the traditional figure of the poet-as-character and the culturally embedded myth of the Poet–Tsar. Furthermore, it maps a genealogy of “graphomaniac” writing from the avant-garde to postmodernism, demonstrating how later authors transform Khlebnikov’s innovations—alternately amplifying, parodying, or ironizing them. Through close readings and extensive intertextual contextualization, the article argues that graphomania functions as a critical mechanism for destabilizing aesthetic orthodoxies, exposing, performing and producing literary authority, and redefining the boundaries between norm and deviation, author and character, poetic freedom and canonical constraint. Full article

A graph-theoretical approach to the analysis of motion and rest in many-body systems is developed. Point bodies are represented as vertices of a complete bi-colored graph, termed the motion–rest graph (MRG). Two vertices are connected by a rust-colored edge when the corresponding bodies are at rest relative to each other; that is, when their mutual distance remains constant in time, bodies moving relative to each other are connected by a cyan edge. It is shown that the logical structure of the relation “to be at rest relative to each other” determines the combinatorial structure of the graph. For one-dimensional motion in classical mechanics and special relativity, this relation is reflexive, symmetric, and transitive, and therefore defines an equivalence relation. As a result, rust edges form disjoint complete cliques corresponding to rest-clusters, and the MRG becomes a semi-transitive complete bi-colored graph that is completely determined by the partition of the bodies into equivalence classes. It is proven that any such graph on five vertices necessarily contains a monochromatic triangle. For two- and three-dimensional motion, the transitivity of relative rest generally fails because constant mutual distance does not imply an equality of velocities in the presence of rotational degrees of freedom. In this case, the MRG is non-transitive, and the Ramsey threshold becomes the classical value R(3,3) = 6. The approach is extended to mixed sets containing moving bodies and reference points, including the center of mass of the system. Generalizations to general relativity and quantum mechanics are also discussed. In general relativity, transitivity of relative rest is generically lost because global rigid congruences do not generally exist. In quantum mechanics, exact transitivity survives only at the level of idealized delocalized eigenstates, whereas for physically realizable localized states, the notion of mutual rest becomes only approximate. The results demonstrate that the interplay between kinematics, logical properties of relational motion, and Ramsey-type combinatorial constraints gives rise to unavoidable ordered substructures in many-body systems. Full article

To address the strong nonlinearity of aerodynamic loads during projectile exterior ballistic flight and the difficulty in accurately modeling fuze dynamic responses, this paper proposes a data-driven modeling and simulation method for fuze exterior ballistic dynamics. A high-fidelity aerodynamic database covering a range of Mach numbers and angles of attack is constructed based on CFD (Computational Fluid Dynamics) simulations. An MLP (Multilayer Perceptron) neural network is then employed to develop an aerodynamic surrogate model, enabling continuous representation of aerodynamic loads within the given sample space. The results show that, within the data coverage range, the proposed model is able to capture the nonlinear variation in aerodynamic parameters and shows improved prediction accuracy compared with the polynomial fitting method. Specifically, for typical aerodynamic parameters, the RMSE (Root Mean Square Error) is reduced from 5.758 to 0.223, the MAE (Mean Absolute Error) is reduced to 0.099, and the R² (Coefficient of Determination) approaches 1. On this basis, the aerodynamic surrogate model is embedded into a six-degree-of-freedom projectile–fuze exterior ballistic dynamics model via the secondary development interface of ADAMS 2020 (Automated Dynamic Analysis of Mechanical Systems), enabling coupled simulation between aerodynamic loads and multibody dynamics. Comparison with firing table data indicates that, under typical operating conditions, the relative deviation of ballistic parameters is generally better than 94%, demonstrating that the proposed method can reasonably reproduce the projectile exterior ballistic characteristics. Furthermore, based on the coupled dynamics model, the dynamic response characteristics of the fuze moving body during the exterior ballistic phase are analyzed. The results indicate that the axial forward overload of the moving body increases significantly with the initial nutation angle, and the variation in the axial projection of gravity induced by nutation plays an important role in its transient response. The proposed approach provides a useful reference for the dynamic response analysis and safety evaluation of fuzes. Full article

This paper presents a novel hybrid learning-based control scheme for position control of robot manipulators whose structure is based on a closed-kinematic-chain mechanism (CKCM). The developed control scheme integrates two complementary control components: the feedback controller and the learning controller. The feedback controller is designed using linearization about a desired trajectory and a PID control law whose gains are selected by a tuning algorithm to guarantee semi-global stability of the linearized closed-loop feedback system. The learning controller incorporates PID-type iterative learning strategy to generate additional control inputs to compensate for modeling uncertainties and unmodeled dynamics. By updating the control input iteratively from trial to trial, the learning controller progressively improves the overall control performance. The effectiveness of the developed control scheme is demonstrated through computer simulations conducted on a six-degree-of-freedom CKCM robot manipulator. Simulation results are presented and discussed to evaluate the tracking accuracy of the developed approach. Full article

The manual handling of poultry is an essential part of raising and caring for birds. The different manual catching methods have various impacts on the bird’s welfare and health, the well-being and work satisfaction of the people who are handling the birds, and the economic and logistical requirements of everyone involved. The traditional approach of using the Five Freedoms for investigating animal well-being has been amended with animal-based measures (ABMs) as well as the evaluation of five welfare domains, which consider the subjective response of an animal towards its environment. The assessment of single individual animal welfare parameters without context can be non-specific, only partially informative, or even misleading when considered in isolation. The objective measurement of suitable parameters for the evaluation of the various steps of poultry catching and transport is complex and should be carried out in a differentiated manner. This review summarizes the current knowledge about the manual catching of poultry, with special focus on the upright and inverted handling of chicken and current considerations in Europe. The implementation of consistent, transparent, and traceable central data collection on animal health and welfare at various critical control points of bird transportation would allow systematic evaluation of the multifactorial welfare assessment in the future. Full article

For AUVs operating under large-rudder-angle yaw maneuvering conditions, linearized hydrodynamic-derivative models often fail to accurately capture strongly nonlinear flow effects, and the applicability of control parameters becomes limited. To address these issues, this paper proposes a CFD-in-the-loop control simulation and parameter optimization framework for large-rudder-angle yaw maneuvers. Based on a coupled hull–propeller–rudder solution method, an unsteady CFD motion simulation model is developed that simultaneously accounts for propeller wake, rudder inflow, and hull-flow interaction, thereby enabling a strongly coupled solution of flow-field evolution and the six-degree-of-freedom motion of the vehicle. On this basis, a CFD-in-the-loop closed-loop control simulation framework is established by integrating the controller, actuator dynamic model, virtual sensors, and CFD motion simulation module into a unified framework, thereby realizing closed-loop computation of control input, flow response, motion update, and state feedback. Furthermore, under the same controller structure and parameter settings, the large-rudder-angle yaw responses predicted by the linearized hydrodynamic-derivative model and the CFD-in-the-loop simulation framework are compared and analyzed. This comparison reveals the dependence of control parameters on the underlying dynamic model and highlights their limited applicability under strongly nonlinear operating conditions. Finally, to address the high computational cost of CFD-in-the-loop simulations, a surrogate-model-based control parameter optimization method is developed to improve parameter tuning efficiency and enhance closed-loop control performance. The results show that the proposed CFD-in-the-loop control simulation framework can effectively characterize the nonlinear hydrodynamic effects arising during large-rudder-angle maneuvers, and provides a more physically consistent basis for control parameter optimization, analysis, and design. Full article

Rapid and robust trajectory planning for the Terminal Area Energy Management (TAEM) phase of horizontal-landing Reusable Launch Vehicles (RLVs) is critical but challenging due to large initial deviations, stringent terminal constraints, and strong model nonlinearities. To address the limitations of existing methods in convergence reliability and computational speed, this paper proposes a novel online trajectory optimization framework based on analytical lateral planning and equivalent dynamic decoupling. First, a cubic Bézier curve is employed to parameterize the lateral ground track, enabling the rapid generation of analytical expressions for the lateral states that strictly satisfy boundary constraints. Leveraging these analytical solutions, the original six-degree-of-freedom dynamics are exactly decoupled and reduced to a lower-dimensional model governing only the longitudinal motion. To further mitigate nonlinearity, the third derivative of height with respect to range is introduced as a virtual control variable, transforming the problem into a smoother form. The resulting equivalent longitudinal optimization problem is then efficiently solved using the Gauss Pseudospectral Method. Numerical simulations demonstrate that the proposed method significantly outperforms traditional approaches in computational efficiency: it generates feasible trajectories satisfying all constraints within 0.26 s (3$\sigma$ value). Furthermore, the method exhibits remarkable insensitivity to initial guesses, achieving stable convergence even with simple linear initialization. This approach provides a robust and real-time capable solution for complex TAEM trajectory optimization problems characterized by high nonlinearity and multiple constraints. Full article

Robust control, adaptive control, and adaptive control allocation methods can create resilient systems that are able to handle uncertainties as well as unknown deficiencies in actuator effectiveness. The capabilities of these methods can further enable advanced missions for autonomous space systems. Thus, in this paper, a resilient control with an adaptive control allocation method is proposed and implemented on a vehicle with 3 degrees of freedom (DoF) that operates with eight thrusters to reduce the impact of external uncertainties as well as unknown effects of the actuator. Specifically, the method includes a combination of sliding mode and novel adaptive control design elements to ensure trajectory tracking in the presence of uncertainties. Moreover, an adaptive control allocation method is also introduced to obtain the desired forces and moments in the presence of unknown effects of the actuator. The boundedness of the closed-loop system is proven with Lyapunov stability analysis. The proposed controller results are compared to a baseline sliding mode controller without adaptive control and adaptive control allocation enhancement, where different uncertainties and unknown actuator degradation, as well as failure cases, are considered within several experimental cases under external fan-induced disturbances. The experimental metrics, including integral squared tracking error, maximum tracking error, actuator effort, actuator impulse, and settling time, are provided. Across all cases, the proposed method reduces the integral squared tracking error, improves settling time, and significantly improves yaw regulation compared to a baseline sliding mode controller. This, in turn, yields a slightly increased control effort for the proposed method. Full article

With the continuous advancement of marine development, underwater operational tasks are becoming increasingly diverse and complex. Addressing the limitations of traditional methods and intelligent planning—which focus solely on acquiring task skills while separating grasp planning from force planning—this paper proposes a modeling approach integrating impedance control with deep reinforcement learning. Using a five-finger humanoid underwater dexterous hand as the grasping execution platform, this method achieves collaborative decision-making between grasp planning and force control for underwater dexterous hands. First, a modular underwater dexterous grasping scenario is established. Its kinematic model and inverse solution are analyzed, and the grasping problem is modeled as a Markov decision process. Second, based on the dexterous fingertip impedance control model for simulation, a grasping strategy learning method grounded in deep reinforcement learning is constructed to address the complex control challenges posed by the high degrees of freedom of the dexterous manipulator. Finally, the Proximal Policy Optimization (PPO) algorithm is employed for grasping strategy learning. An underwater dexterous grasping parallel training and testing environment is established using the Isaac Lab simulation platform to rapidly validate the learning method. Simulation results demonstrate the proposed method’s excellent dexterous compliant control performance and strong robustness to underwater variable environments: the PPO-based impedance control scheme reduces contact force variance by 56% compared to pure position control. The average maximum contact force is suppressed to 3.26 N, representing a 60.4% reduction compared to pure position control. This study achieves the organic integration of underwater hydrodynamic compensation, adaptive impedance control, and grasping strategy learning, providing a novel and effective solution for compliant grasping control of underwater dexterous manipulators. Full article

Assistive bathing for the elderly and disabled presents significant challenges regarding caregiver workload and safety. This paper presents the design and verification of a multi-module integrated intelligent bathing assistance system. The system automates the entire bathing sequence through four coordinated modules: a robotic scrubbing unit, a climate-controlled cabin, a passive multifunctional wheelchair, and a multi-degree-of-freedom transfer device. A key innovation is the wheelchair’s passive design with an automated docking mechanism, ensuring safety in wet environments. Unlike existing commercial solutions and the existing literature, which primarily focus on fragmented, singular functionalities (such as transfer-only devices or fixed-spray cabins), the core advantage of the developed system lies in its holistic integration of safe physical transfer, adaptive robotic scrubbing, and microenvironment control into a seamless, unified architecture. Employing a modular and ergonomic approach, the system executes a predefined 12-step automated workflow. Experimental validation demonstrates an average bathing time of 16.6 min and a quantifiable 69.8% reduction in caregiver workload, confirming the system’s high efficiency and practical utility in alleviating caregiver burden. Full article

This paper investigates the secrecy energy efficiency (SEE) maximization problem in a downlink multiple-input single-output (MISO) wireless communication system assisted by an intelligent reflecting surface with movable elements (ME-IRS). Unlike a conventional IRS, which has fixed-position elements, the proposed ME-IRS enables dynamic adjustment of element positions to exploit additional spatial degrees of freedom for performance enhancement. However, such flexibility introduces new challenges due to the strong coupling among transmit beamforming, IRS phase shifts, and element positions, as well as the additional power consumption caused by element movement. To address these issues, we formulate an SEE maximization problem by jointly optimizing the transmit beamforming, phase shift matrix, and element positions. The resulting problem is highly non-convex owing to the fractional objective function and coupled variables. To address this challenge, an efficient alternating optimization (AO) framework is developed by leveraging semidefinite relaxation (SDR), successive convex approximation (SCA), and gradient-based methods. Simulation results demonstrate that the proposed ME-IRS configuration significantly outperforms conventional fixed-position and discrete-position IRS configurations in terms of SEE, providing valuable insights into the impact of movable region size and system parameters. Full article

The jacket platform has been widely used in offshore oil and gas development during the past several decades and faces the problem of decommissioning now due to approaching the design life. During the decommissioning process of a jacket platform, cutting the pile chords is one of the most important steps for removing the jacket. In the process of cutting, the freedom of the bottom of the jacket increases, decreasing its stability and potentially causing structure damage or failure. In this paper, the influence of the cutting sequences (cross-circulation cutting and clockwise-circulation cutting), offshore environmental conditions, and the overall weight of the jacket on the mechanical responses of the jacket platform during the cutting operation was investigated by using the commercial finite element package, SACS. The numerical results show that (1) during the circular cutting process, there is a negative correlation between the unit check (UC) values of the diagonal leg chords: the UC value of the leg chord at diagonal positions decreases by approximately 10%, and the final round of cutting is critical because the jacket platform has a high risk of failure with the UC value being likely to exceed 1.0; (2) the UC value of the piles downstream is 0.2 or much larger than that of the piles upstream, which controls the stability of the jacket during the cutting process; (3) the UC value at the skirt pile of the jacket roughly increases linearly with the weight of the jacket. Full article