Stability Of Trajectories Research Articles

Design of 2-DOF Thrust Vector Control System for Rockets and Missiles

This paper outlines the development and implementation of a Thrust Vector Control (TVC) system specifically designed for solid propellant rocket engines, aiming to enhance the portability of hybrid and liquid propellant rocket systems. The proposed system ensures trajectory stability and rapid response to flight emergencies by effectively counteracting external perturbations such as wind. Key components include gyroscopic (GYRO) sensors, a high-performance microcontroller, and servo motors, collectively referred to as thrust vectoring components, which dynamically adjust thrust direction opposite to the rocket’s trajectory to maintain stability. Drawing from an extensive literature review of existing TVC system designs, with a focus on thrust characteristics and engine combustion timing, the design integrates geometric properties, kinematics, forces, energy requirements, safety, cost, and control methods, aligning with both mechanical and avionic design principles. The anticipated outcome is an advancement in rocket propulsion technology, characterized by improved angular speed control, trajectory linearity, and rapid response capabilities.

Quaternion-Based Robust Sliding-Mode Controller for Quadrotor Operation Under Wind Disturbance

This paper presents a quaternion-based robust sliding-mode controller for quadrotors operating under significant wind disturbances. The proposed control method improves the reliability and efficiency of quadrotor control by eliminating the singularity problem inherent in the Euler angle method. The quadrotor dynamics and wind environment are modeled, and dynamic analysis is performed via numerical simulation. A realistic wind model is used, similar to a combination of deterministic and statistical models. The Lyapunov stability theory is utilized to prove the convergence and stability of the proposed control system. The simulation results demonstrate that the quaternion-based controller enables the quadrotor to follow the desired path and remain stable, even under external wind disturbances. Specifically, both position and attitude converge to the desired values within 10 s, demonstrating stable performance despite the challenging wind disturbances in both scenarios. Scenario 1 features turbulence with an average wind speed of 12 m/s and changing wind directions, while Scenario 2 models an environment with wind speeds that change abruptly and discretely over time, coupled with temporal variations in wind direction. Additionally, a comparative analysis with the conventional PD controller highlights the superior performance of the proposed RSMC controller in terms of trajectory tracking, stability, and energy efficiency. The rotor speeds remain within a reasonable and hardware-feasible range, ensuring practical applicability.

Application of machine learning algorithms for optimizing the trajectory of inclined wells

Machine learning, a subset of artificial intelligence, allows computers to learn and improve from data without explicit programming. Machine learning algorithms are categorized into supervised, unsupervised, and reinforcement learning, each serving different applications such as classification, clustering, and decision-making. In the oil and gas industry, machine learning is applied to drilling processes, reservoir characterization, and exploration. It improves efficiency in predicting reservoir properties, optimizing drilling parameters, and detecting anomalies. The methodology for analyzing well trajectory includes evaluating survey data with calculation methods like tangential, balanced tangential, average angle, radius of curvature, and minimum curvature. These methods help optimize wellbore paths. This study outlines control criteria essential for optimizing borehole trajectory management in oil and gas well drilling. The deviation correction criterion aims to maintain the borehole path within a designated trajectory, minimizing deviation from the planned design profile. Optimal control conditions are defined through mathematical criteria involving radius vectors and design trajectory alignment. The control framework incorporates efficiency measures, calculating the trajectory's costeffectiveness and operational constraints. Machine learning algorithms facilitate these control strategies, focusing particularly on zenith angle correction for trajectory stabilization. These methods provide adaptable options for deflector angle and correction length, ensuring alignment with target intervals. The approach enhances trajectory accuracy, minimizes costs, and complies with technical, geological, and technological constraints inherent to drilling. Software incorporating machine learning and these methods was developed and tested, demonstrating improvements in analyzing survey data and optimizing well trajectory, contributing to more efficient drilling operations and reduced costs. Keywords: machine learning; mathematical models; control criteria; well trajectory optimization; survey data analysis; calculation methods.

Trajectory Stabilization of Nonlocal Continuity Equations by Localized Controls

Trajectory Stabilization of Nonlocal Continuity Equations by Localized Controls

Research on the flow field and trajectory characteristics of high-speed projectile entry water in waves

The high velocity of supercavitating projectiles in a wave environment alters the flow characteristics and water entry stability, which significantly impacts the development and application of supercavitating weapons. This paper, investigates the effects of waves on the oblique water entry of high-speed supercavitating projectiles using computational fluid dynamics, with Stokes' second-order wave theory as the foundation for wave simulations. The numerical simulation method is validated through high-speed water entry experiments. The analysis explores the impact of wave inclination on cavity formation and the forces acting on the projectile. The results reveal that variations in wave inclination change the actual water-entry angles, affecting the cavitation structure near the free surface, modifying the impact intensity on the tail fins during water contact, and ultimately influencing the hydrodynamic forces acting on the projectile. When the actual water-entry angles are similar, the forces on the projectile during entry remain consistent under different conditions, with the trajectory being determined by the entry angle. Additionally, a reduction in the actual water-entry angle improves the projectile's entry stability but increases the amplitude and frequency of tail slap, ultimately affecting the stability of the projectile's trajectory after water entry.

ON THE GENERALIZED ALGORITHM FOR OPTIMAL CONTROL OF SYSTEMS OF LINEAR DIFFERENTIAL-DIFFERENCE EQUATIONS

This article presents a model for optimizing the number of control function parameters for objects with delay, which are expressed by a system of differential equations. It also discusses the model of the stability of the robot's motion trajectory after the practical process of a specific object, as well as algorithms for improving positional accuracy.

Enhancing stability and safety: A novel multi‐constraint model predictive control approach for forklift trajectory

AbstractThe advancements in intelligent manufacturing have made high‐precision trajectory tracking technology crucial for improving the efficiency and safety of in‐factory cargo transportation. This study addresses the limitations of current forklift navigation systems in trajectory control accuracy and stability by proposing the Enhanced Stability and Safety Model Predictive Control (ESS‐MPC) method. This approach includes a multi‐constraint strategy for improved stability and safety. The kinematic model for a single front steering‐wheel forklift vehicle is constructed with all known state quantities, including the steering angle, resulting in a more accurate model description and trajectory prediction. To ensure vehicle safety, the spatial safety boundary obtained from the trajectory planning module is established as a hard constraint for ESS‐MPC tracking. The optimisation constraints are also updated with the key kinematic and dynamic parameters of the forklift. The ESS‐MPC method improved the position and pose accuracy and stability by 57.93%, 37.83%, and 57.51%, respectively, as demonstrated through experimental validation using simulation and real‐world environments. This study provides significant support for the development of autonomous navigation systems for industrial forklifts.

Trajectory tracking and stabilization of two-wheeled balancing mobile robot with hierarchical and sliding mode control

Trajectory tracking and stabilization of two-wheeled balancing mobile robot with hierarchical and sliding mode control

Quadrotor trajectory tracking using combined stochastic model-free position and DDPG-based attitude control

This article presents a cascade controller for the quadrotor to track the desired trajectory effectively. Unlike previous approaches, this method avoids simplification and linearization assumptions, making it applicable in a wider range of scenarios. A novel linear quadratic tracking method is utilized, which takes into account both process noise and measurement noise while maintaining a model-free nature. Furthermore, the stability analysis of this stochastic method is thoroughly investigated. In terms of attitude control, a model-free approach is adopted. The Deep Deterministic Policy Gradient (DDPG) algorithm is implemented, leveraging an actor-critic network to handle the nonlinearities associated with attitude control. This model-free approach eliminates the need for an accurate model of the quadrotor's dynamics. Simulations are conducted to evaluate the performance of the proposed controller, and the results demonstrate its ability to effectively control the quadrotor, ensuring accurate trajectory tracking and stability.

Research on trajectory tracking of wheeled mobile robots using fuzzy PID based on TD3

Abstract This study addresses the issues and limitations of trajectory tracking for Non-holonomic wheeled mobile robot (NWMR) under traditional PID control, including low accuracy, high response delay, poor robustness, and stability concerns. We propose a strategy that combines the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm with fuzzy PID control to optimize PID parameter tuning for more precise robot trajectory tracking. Fuzzy logic is introduced to adjust the PID controller parameters, making them more adaptive and robust. The bidirectional long short-term memory (BiLSTM) network enhances the time series processing capability of the Actor-Critic network, improving the system’s state representation and prediction abilities. A curiosity-driven exploration method is employed to increase policy diversity and avoid premature convergence. Simulation experiments using the ROS Noetic and Gazebo platforms demonstrate that this method significantly outperforms traditional PID and TD3 algorithms in terms of trajectory alignment, training time, accuracy, and stability.

Measurement and Dynamic Analysis of the Centroid Trajectories of Angular-Contact Ball Bearing Cages

When a high-speed rolling bearing cage comes into contact with rollers, it experiences random movement due to friction and collision, which significantly impacts the overall performance of the bearing. To further investigate the motion law of cages, a test bench for a 7010C angular-contact bearing cage was constructed. This setup utilized laser sensors to obtain changes in attitude and displacement during operation. After analyzing how cage deflection errors influenced trajectory measurements, corrections were applied to the measurement results. Additionally, an investigation was conducted into the effects of varying rotational speeds on the dynamic performance of the cage. Simulations were performed using ADAMS software, which verified both the effectiveness of the measuring method and the testing results. The findings indicated that within the tested range of rotational speeds, the centroid trajectory stability of the cage gradually improved as rotational speed increased and then began to show a tendency to deteriorate. Furthermore, there existed a negative correlation between the deflection error of the cage and the centroid trajectory stability.

Lingering shadows of childhood corporal punishment: Family trajectories across decades

AbstractObjectiveCorporal punishment is the most common form of violence against children worldwide. This study adopts a life course perspective to examine associations between childhood corporal punishment and distinct multi‐decade family trajectories from young adulthood to middle adulthood in China. Specifically, it examines how childhood parental punishment shapes later family life course trajectory patterns, incorporating partnership, marriage, and fertility outcomes, and considers different sources of punishment (maternal and paternal) and potential gender differences (sons and daughters).BackgroundAccumulating evidence reveals that corporal punishment is not only unnecessary as a disciplinary technique but also harmful to children. This evidence has led to a worldwide movement to eliminate any non‐accidental use of physical force against children. However, previous research often assesses isolated family outcomes without considering family development as a dynamic and interconnected process, resulting in an ambiguous understanding of childhood corporal punishment's long‐reaching influence on unfolding family pathways.ResultsResults uncovered both stability and diversity in Chinese family trajectories, with the majority following stable marital norms. Experiencing childhood corporal punishment increased the odds of an early unstable trajectory characterized by divorce and remarriage. Moreover, the implications of childhood paternal punishment appeared more wide‐ranging than maternal punishment in terms of sorting into normative versus atypical family trajectory patterns. Childhood maltreatment also overrides influences of child gender, similarly impacting future family trajectories across genders.ConclusionThis research highlights the profoundly disruptive effects of corporal punishment on family development throughout the lifespan, carrying important implications for fostering healthier and more resilient families.

Output-feedback control design for Takagi-Sugeno fuzzy systems through Lyapunov functions depending polynomially on the states

This paper proposes a new strategy based on linear matrix inequalities (LMIs) for the synthesis of state- and output-feedback controllers through parallel distributed compensation for continuous-time Takagi-Sugeno fuzzy systems. The main novelty of the proposed design technique is the use of homogeneous polynomial Lyapunov functions of degree larger than two on the states, generalizing the results based on quadratic functions. Parametrized in terms of a constant matrix, those homogeneous polynomial Lyapunov functions provide less conservative results in terms of stability and decay rate of trajectories when dealing with membership functions whose time-derivatives have unknown bounds. The synthesis procedure is formulated in terms of a locally convergent iterative algorithm, where a set of LMIs defined in an augmented parameter space is solved at each iteration. Numerical examples are used to compare the proposed method with quadratic stabilizability techniques available in the literature, illustrating the advantages of higher degree Lyapunov functions.

Coordinated strategy for path tracking and dynamic stability considering extreme obstacle avoidance in distributed drive electric vehicles

PurposeThis research aims to investigate the trajectory tracking problem for a four-wheel independent drive autonomous vehicle (4WID) and propose an integrated, coordinated control strategy to address the mutual interference between trajectory tracking and stability control in extreme cases.Design/methodology/approachThe authors establish an adaptive preview model that modifies the preview distance based on vehicle speed. They utilize a three-degrees-of-freedom vehicle model and employ model predictive control to calculate the necessary front wheel angle for trajectory tracking. In terms of longitudinal control, a longitudinal coordinated control mechanism is established to achieve the two conflicting objectives of trajectory tracking accuracy and dynamic stability through early deceleration. A stability controller based on sliding mode control (SMC) is designed, considering tire constraints and tracking the optimal yaw angle and sideslip angle. Furthermore, a lateral coordinated control strategy is developed, considering the weight coefficient of stability control, and the yaw moment is calculated and distributed based on the vehicle torque requirements.FindingsThe proposed integrated, coordinated control strategy successfully addresses the mutual interference between trajectory tracking and stability control in extreme cases for the 4WID vehicle. The strategy achieves trajectory tracking accuracy, dynamic stability and reduced energy consumption while taking into account tire constraints.Originality/valueWe have proposed a cooperative control strategy for the trajectory tracking problem of autonomous driving vehicles. This strategy is different from previous methods in that we have taken into account the integrated dynamic control in both longitudinal and lateral directions, balancing the conflicting control requirements and reducing energy consumption, improving trajectory tracking accuracy and vehicle dynamic stability. We have verified the feasibility of this strategy through joint simulation under different driving conditions.

Trajectory optimization and stability control for a novel unmanned intelligent wheel-legged vehicles on unstructured terrains

The trend of intelligent vehicles is currently expanding, and a new class of unmanned intelligent vehicles known as wheel-legged vehicles (WLVs) is emerging. WLVs excel in transportation on unstructured terrain by offering a unique combination of the efficiency of wheels on flat ground and the versatility of legs to tackle obstacles. To enhance the locomotion performance of WLVs on unstructured terrains, this paper presents a novel framework for improving their locomotion through nonlinear programming-based (NLP) trajectory optimization and stability control. The framework optimizes the vehicle’s body and wheel positioning while incorporating terrain information and employs a linear rigid body dynamic model for efficient motion planning. The stability control framework combines feedforward control using ground reaction forces with feedback control through joint PD control and utilizes model predictive control (MPC) to adjust the wheel slip ratio to prevent slip on steep slopes. Experimental validation on the real vehicle with torque-controlled wheels demonstrated the capability of driving over a 1 m height with a 30°slope at an average speed of 0.7 m/s and a maximum speed of 1.03 m/s. Our approach also enables the WLV to overcome obstacles, such as inclines, while dynamically negotiating these challenging terrains.

Impact of Long-Term Depression on Employment Outcomes: A Systematic Review and Case Series From Iraq on Career Trajectory and Job Stability.

Background Long-term forms of depression, especially chronic and episodic, make it very hard for any individual to maintain a steady job or develop in his/her workplace, which reduces the ability to gain financial security. The purpose of this study is to investigate and thoroughly examine the impact oflong-term depression on career trajectories and job stability using a methodical evaluation of the literature supplemented with case studies. Methodology This study combined a systematic review of available literature with a detailed case series analysis. The literature search was conducted systematically in three major databases, namely, PubMed, PsycINFO, and Scopus. The systematic review synthesized findings from studies that assessed the relationship between chronic and episodic long-term depression and employment-related outcome measures, i.e., job stability, upward career mobility, and socioeconomic status. The studies published between 2000 and 2024 were included and qualified. The case series contributed qualitative depth using eight personal experiences illustrating how the use of self-workplace dynamics interacted with depressive symptoms to shape employment. Results The systematic review provided consistent evidence that depression negatively influences employment status, such as decreased income and an increased rate of unemployment and disability claims. The current investigation included 29 studies, which were chosen after a rigorous screening process that included identifying 10,651 records and removing irrelevant or duplicate entries. The case series underlined further that it is the role of support executed by the workplace and societal stigma that mitigates or exaggerates these outcomes. In cases, people whose careers were disrupted by depression (job loss, low productivity, and long-term financial pressure) evidenced a huge change. Conclusions The effects of chronic and episodic long-term depression interfered with employment and socioeconomic well-being and, in fact, expanded beyond the individual to affect larger societal factors. Healthcare providers should collaborate with employers to ensure affected individuals receive appropriate accommodations in the workplace along with responses to mental health concerns. Further, policymakers should create inclusive policy environments to address the demands of people concerning job security and access to mental health related to depression. In addition, they should promote anti-stigma campaigns targeted at the reduction of societal and workplace discrimination against mental health issues.

An improved whale optimization algorithm for UAV swarm trajectory planning

For the problem of trajectory planning in the small-scale unmanned aerial vehicle (UAV) swarms, classical intelligent algorithms and newly emerged bio-inspired algorithms often suffer from being trapped in local optima, leading to suboptimal solutions. Moreover, these algorithms fail to ensure optimal solutions and convergence speed in high-speed dynamic UAV networking scenarios. In response to these challenges, this paper proposes an Improved Whale Optimization Algorithm (IWOA) that considers the global perspective. To address the issue of initial solution diversity, an opposition-based learning method is introduced by constructing a reverse population, enhancing the diversity of the initial population. To overcome the problem of the algorithm getting trapped in local optima, random convergence factors, and end-point random neighborhood perturbations are incorporated to accelerate the global convergence speed of the IWOA and prevent it from getting stuck in local optima. Additionally, a grid digital elevation model is employed when constructing the experimental environment model, considering various physical constraints of the UAV swarm. This ensures that the simulation validation of the IWOA algorithm is closer to real-world scenarios. Simulation results indicate that, compared to commonly used algorithms, the IWOA can generate more optimal trajectories for drone swarm planning under constraints resembling real-world scenarios. It exhibits better performance in trajectory evaluation, convergence speed, and stability, thereby meeting the requirements of trajectory planning for small-scale UAV swarms. The proposed IWOA enhances UAV swarm coordination and efficiency, significantly impacting real-world applications in various fields.

BPNN-based prediction for the shapes of a petal hole induced by hydrodynamic ram

The attitude angles of a projectile moving through a liquid are important factors that influence the dynamic failure of liquid-filled structures induced by hydrodynamic ram (HRAM). In this study, the effect of the attitude angles of a cylindrical projectile on the shapes of the petal hole in the rear plate of a kerosene-filled tank was investigated through ballistic impact experiments using three-dimensional digital image correlation, finite element simulations, and a back propagation neural network (BPNN). The inclination angle λ characterizing the shapes of the petal hole was related to the projection shapes of the projectile when impacting on the rear plate. The formation of petal-hole shapes was also accompanied by the formation of plastic hinge lines in the rear plate. Additionally, a method combining a BPNN and physical equations that accurately predict the drag coefficient and motion of a projectile moving through a liquid was proposed. A function describing the shapes of the petal hole was provided in the 2D space of the two initial attitude angles. The results provide offer insights into trajectory stability during liquid entry and aid in predicting the dynamic failure mode of a liquid-filled tank induced by HRAM.

(In)stability of the Professional Trajectories of Asylum Seekers and Refugees in Belgium

(In)stability of the Professional Trajectories of Asylum Seekers and Refugees in Belgium

Computational exploration of compounds in Xylocarpus granatum as a potential inhibitor of Plasmodium berghei using docking, molecular dynamics, and DFT studies

Malaria remains a global health concern, with the emergence of resistance to the antimalarial drug atovaquone through cytochrome b (cyt b) being well-documented. This study was prompted by the presence of this mutation in cyt b to enable new drug candidates capable of overcoming drug resistance. Our objective was to identify potential drug candidates from compounds of Xylocarpus granatum by computationally assessing their interactions with Plasmodium berghei cyt b. Using computational methods, we modeled cyt b (GenBank: AF146076.1), identified the binding cavity, and analyzed the Ramachandran plot against cyt b. Additionally, we conducted drug-likeness and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies, along with density functional theory (DFT) analysis of the compounds. Molecular docking and molecular dynamics simulation (MDS) were used to evaluate the binding energy and stability of the cyt b-ligand complex. Notably, our investigation highlighted kaempferol as a promising compound due to its high binding energy of 7.67 kcal/mol among all X. granatum compounds, coupled with favorable pharmacological properties (ADMET) and antiprotozoal properties at Pa 0.345 > Pi 0.009 (PASS value). DFT analysis showed that kaempferol has an energy gap of 4.514 eV. MDS indicated that all tested ligands caused changes in bonding and affected the structural conformation of cyt b, as observed before MDS (0 ns) and after MDS (100 ns). The most notable differences were observed in the types of hydrogen bonds between 0 and 100 ns. Nevertheles, MDS results from a 100 ns simulation revealed consistent behavior for kaempferol across various parameters including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), molecular mechanics-Poisson Boltzmann surface area (MM-PBSA), and hydrogen bonds. The cyt b-kaempferol complex demonstrated favorable energy stability, as supported by the internal energy distribution values observed in principal component analysis (PCA), which closely resembled those of the atovaquone control. Additionally, trajectory stability analysis indicated structural stability, with a cumulative eigenvalue of 24.7 %. Dynamic cross-correlation matrix (DCCM) analysis revealed a positive correlation among catalytic cytochrome residues within the amino acid residues range 119–268. The results of our research indicate that the structure of kaempferol holds promise as a potential candidate against Plasmodium.