Attitude Control Research Articles

The Influence of Attitude, Subjective Norms, and Behavioral Control on the Purchase Intentions of Maybelline Cosmetics in Bandar Lampung

This study examines the influence of attitude, subjective norm, and perceived behavioral control on the purchase intention of Maybelline cosmetic products in Bandar Lampung. Using a descriptive quantitative approach, data was collected through surveys and interviews with Maybelline users in Bandar Lampung. The findings indicate that all three factors—attitude, subjective norm, and perceived behavioral control—positively and significantly affect consumers' purchase intentions. Consumers’ attitudes towards Maybelline are shaped by product quality, innovation, and its ability to meet beauty needs. Subjective norms, influenced by social factors such as recommendations from friends and influencers, also drive purchase decisions. Furthermore, behavioral control, based on consumers’ perception of their ability to afford and use Maybelline products, plays a critical role in their purchasing decisions. The study suggests that Maybelline can enhance its market position by focusing on sustainability, promoting transparent reviews, and offering affordable product bundles. Collaborations with influencers and popular figures can also strengthen emotional connections with consumers and further encourage purchase intentions. The research provides valuable insights into how attitude, social influence, and perceived control impact consumer behavior, offering practical implications for marketers in the cosmetics industry.

Deterministic Trajectory Design and Attitude Maneuvers of Gradient-Index Solar Sail in Interplanetary Transfers

A refractive sail is a special type of solar sail concept, whose membrane exposed to the Sun’s rays is covered with an advanced engineered film made of micro-prisms. Unlike the well-known reflective solar sail, an ideally flat refractive sail is able to generate a nonzero thrust component along the sail’s nominal plane even when the Sun’s rays strike that plane perpendicularly, that is, when the solar sail attitude is Sun-facing. This particular property of the refractive sail allows heliocentric orbital transfers between orbits with different values of the semilatus rectum while maintaining a Sun-facing attitude throughout the duration of the flight. In this case, the sail control is achieved by rotating the structure around the Sun–spacecraft line, thus reducing the size of the control vector to a single (scalar) parameter. A gradient-index solar sail (GIS) is a special type of refractive sail, in which the membrane film design is optimized though a transformation optics-based method. In this case, the membrane film is designed to achieve a desired refractive index distribution with the aid of a waveguide array to increase the sail efficiency. This paper analyzes the optimal transfer performance of a GIS with a Sun-facing attitude (SFGIS) in a series of typical heliocentric mission scenarios. In addition, this paper studies the attitude control of the Sun-facing GIS using a simplified mathematical model, in order to investigate the effective ability of the solar sail to follow the (optimal) variation law of the rotation angle around the radial direction.

USLC: Universal self‐learning control via physical performance policy‐optimization neural network

AbstractThis article proposes an online universal self‐learning control (USLC) algorithm based on a physical performance policy‐optimization neural network, which aims to solve the problem of universal self‐learning optimal control laws for nonlinear systems with various uncertain dynamics. As a key system characterization, this algorithm predicts the discrepancy between the optimal and current control laws by evaluating overall performance in each iterative learning cycle, leveraging an offline‐trained universal policy network. This approach is universal, as it does not rely on an exact system model and can adaptively control performance preferences across various tasks by customizing the physical performance cost weights. Using the established control law‐performance surface and contraction Lyapunov function, the necessary assumptions and proofs for the stable convergence of the system within a three‐dimensional manifold space are provided. To demonstrate the universality of USLC, simulation experiments are conducted on two different systems: a low‐order circuit system and a high‐order variable‐span aircraft attitude control system. The stable control achieved under varying initial values and boundary conditions in each system illustrates the effectiveness of the proposed method. Finally, the limitations of this study are discussed.

Research on Quadrotor Control Based on Genetic Algorithm and Particle Swarm Optimization for PID Tuning and Fuzzy Control-Based Linear Active Disturbance Rejection Control

The control system of a quadrotor aircraft is characterized by nonlinearity, strong coupling, and underactuation, making it susceptible to external disturbances that can affect flight performance. To address this issue, this paper proposes a novel control system based on inner–outer loop architecture. In this system, the outer loop position control adopts a PID controller optimized by Genetic Algorithm-based Particle Swarm Optimization (GA-PSO), while the inner loop attitude control employs a Linear Active Disturbance Rejection Controller (LADRC) with fuzzy algorithm-based adaptive tuning, forming a dual-loop control structure. Comparisons with traditional dual-loop cascaded PID controllers, conventional PID in the outer loop with LADRC in the inner loop, and conventional PID in the outer loop with fuzzy algorithm-based adaptive tuning in the inner loop demonstrate that the proposed control system can stably track the desired position and attitude angles under certain external disturbances, exhibiting excellent anti-disturbance capability and stability.

The Analysis of Applied Innovative Mechatronics Technology in Intelligent Driving - A Case Study of New-Energy Vehicles' Development in Mainland China

Abstract. The interdisciplinary field of mechatronics, which amalgamates elements of mechanical, electrical, computer, and control engineering, has fundamentally transformed the automotive industry. This transformative influence is evident in the development of advanced vehicular functionalities such as Automatic Fuel Filling Systems, Car Attitude Control, Antilock Brake Systems (ABS), and Electronic Stability Programs (ESP), as well as in the advent of vehicles equipped with semi-active suspensions. The integration of mechatronics has not only enhanced vehicle safety, efficiency, and performance but has also positioned itself as a cornerstone for the burgeoning electric vehicle (EV) market, particularly in China. Chinese companies, leveraging extensive smart factory and automation technologies, have consequently secured a dominant stance in the global EV landscape, capturing a staggering 60% market share. This paper explores the multifaceted applications of mechatronics in the automobile industry of industrialized nations, with a special focus on its pivotal role in China's technological ascendancy in automotive manufacturing. Through an exploration of practical applications including IoT integration and collaborative robotics, this study underscores the transformative potential of mechatronics in redefining automotive production and operation, propelling the industry toward unprecedented levels of innovation and efficiency.

Time‐Varying Sliding Mode Based Fixed‐Time Missile Guidance and Attitude Control With Impact Angle Constraints

Time‐Varying Sliding Mode Based Fixed‐Time Missile Guidance and Attitude Control With Impact Angle Constraints

Enhancing postural stability in musculoskeletal quadrupedal locomotion through tension feedback for CPG-based controller

A central pattern generator (CPG)-based controller enhances the adaptability of quadrupedal locomotion, for example, by controlling the trunk posture. The conventional CPG-based controllers with attitude control often utilized the posture angle as feedback information. However, if the robot's body is as soft as a musculoskeletal structure, it can detect the over-tilting of the trunk based on proprioceptive information of the muscles. In general, proprioceptive information such as muscle tension changes more rapidly than posture angle information. Therefore, a feedback loop based on proprioceptive information has great potential to respond to sudden disturbances that occur during locomotion over uneven terrain. In this research, we proposed a CPG-based controller utilizing the tension of soft pneumatic artificial muscles (PAMs). Musculoskeletal quadruped robots driven by PAMs are so soft, which prevents over-tilting of the trunk because the soft leg acts like a suspension. In addition, tension, one of the proprioceptive information of PAMs, exhibits high sensitivity to changes in trunk posture because the soft body's motion easily is affected by over-tilting of the trunk. To validate the efficacy of the proposed controller, we conducted numerical simulations with a simple quadruped model and experiments with a musculoskeletal quadruped robot. As a result, the tension feedback is not effective for posture stabilization on flat terrain whereas it is effective on uneven terrain. Moreover, the tension feedback improved the running velocity over uneven terrain. These results will enhance the locomotion capability of musculoskeletal quadruped robots, advancing their practical application.

Attitude Control System for Quadrotor Using Robust Monte Carlo Model Predictive Control

Monte Carlo Model Predictive Control (MCMPC) is a kind of non-linear Model Predictive Control (MPC) that determines control inputs using the Monte Carlo method. The Monte Carlo method used in MCMPC can handle discontinuous phenomena, and there have been reports of its application in control systems for quadrotors, where the objective is to maintain the stability of the attitude during collisions. However, as with conventional MPC, concerns remain about control performance degradation due to modeling errors and external disturbances such as unexpected wind gusts. In this study, we propose a novel Robust Monte Carlo Model Predictive Control (RMCMPC), which improves the robustness of MCMPC by considering the hypersurface known from the Sliding Mode Control (SMC) theory. The proposed RMCMPC is applied to a quadrotor attitude control system, and its effectiveness is validated through numerical simulations.

Feature-weighted Random Forest with Boruta for Fault Diagnosis of Satellite Attitude Control Systems

The performance of random forest (RF) based satellite attitude control system (ACS) fault diagnosis methods is limited by uninformative features in high-dimensional data. To solve this problem, we proposed a feature-weighted random forest with Boruta (FWRFB) based fault diagnosis method is proposed for fault diagnosis of ACSs. Firstly, a Boruta feature selection algorithm is used to obtain a feature set and determine significant feature weights. Subsequently, a novel feature-weighted random forest (FWRF) algorithm is designed, which utilizes feature-weighted random sampling instead of simple random sampling to generate feature subsets in the RF. The FWRFB effectively utilizes the feature information while mitigating noise interference. Finally, a FWRFB-based diagnostic module is developed for online fault diagnosis of ACSs. The effectiveness of the proposed method is verified by the ACS data from a semi-physical simulation platform.

Nonlinear Extended State Observer and Prescribed Performance Fault-Tolerant Control of Quadrotor Unmanned Aerial Vehicles Against Compound Faults

Addressing trajectory and attitude control challenges in quadrotor UAVs amid compound faults and unknown external disturbances, this paper introduces a fault-tolerant control method predicated on nonlinear extended state observers. Initially, the UAV’s dynamic model is optimized and decoupled, forming a rapid non-singular terminal sliding mode surface that circumvents the singular phenomena typical in conventional terminal sliding mode controls. A nonlinear extended state observer is then deployed to estimate the unknown states triggered by compound faults and disturbances within the control system. Theoretical analysis shows that beyond accurately estimating faults and disturbances, the proposed controllers adaptively adjust the system’s dynamic and steady-state performances, ensuring rapid stabilization of all error responses. Numerical simulations indicate significant enhancements in control precision and robustness against compound faults and disturbances, with response times and energy consumption remaining within acceptable limits for practical applications.

Improved Adaptive Sensor Fault Recovery for an Attitude Control System Simulator Using a New Terminal Sliding Mode Controller with Faster Convergence and Guaranteed Performance

Improved Adaptive Sensor Fault Recovery for an Attitude Control System Simulator Using a New Terminal Sliding Mode Controller with Faster Convergence and Guaranteed Performance

Non-singular sliding mode control-based attitude control analysis of ELITE satellite with flywheel failures

Abstract This paper addresses the challenge of maintaining the attitude control of the ELITE satellite in the event of flywheel failures. Given the critical need for highly stable and precise attitude control during Time-Delay Integration (TDI) Imaging missions, a failure in any flywheels poses a significant threat to the satellite’s attitude control stability and accuracy. To tackle this issue, a Non-singular Sliding Mode Control (NSMC) method was proposed to ensure ELITE’s continued performance under flywheel failure conditions. The research involves a thorough analysis of ELITE’s attitude dynamics, followed by designing an NSMC tailored to its specifications. Theoretical validation of the NSMC’s finite-time stability was achieved using the Lyapunov function. Numerical simulations conducted demonstrate that the proposed NSMC method enables ELITE to maintain its attitude control stability and precision even in the presence of flywheel failures, thereby ensuring mission continuity and reliability.

Development of Rail Camera for Bridge inspection with Attitude Control using Thrust of Rotors

A lot of concrete structures are deteriorating to dangerous levels throughout Japan. These concrete structures need to be inspected regularly to ensure they are safe enough to be used. According to national standards, a visual inspection of the bridge is required once every five years. In the visual inspection, the worker checks the bridge with their own eyes directly. So, it is necessary to set up scaffolding to access the bridge's underside for visual inspection. Alternatively, it is an essential aerial work platform. However, setting up of scaffolding and aerial work platforms is not economical in time and money. So, we developed an inspection device for the check of bridges called a Rail camera. This inspection device connects a rod and a rail and the connection has a rotational degree of freedom. Rotors are attached to the tip of the rod and it can be attitude controlled by thrust of rotors. So, half of the device's weight is lifted by the thrust of the rotors. And it can be taken with a camera mounted on an electric slider on the rail. The worker on the bridge can check the underside of the bridge safely by holding the rod with one hand and operating the rail camera with another hand. The rail camera developed had a rail length of 2 m and a weight of 2.5 kg. Magnesium was used for the rail and rod to reduce weight. Coaxial rotors were used to cancel the counter-torque caused by the rotation of the propeller. To verify the performance, a visual inspection was performed on the bridge. As a result, it was confirmed that the horizontal attitude was maintained by the rotor thrust.

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.

Adaptive Multi-Model Predictive Control with Optimal Model Bank Formation: Consideration of Local Models Uncertainty and Stability

The Multiple Model Control (MMC) structure comprises three main components: the model bank, controller bank, and supervisor algorithm. Precise design of these components is crucial for achieving high control performance within the MMC framework, albeit this effort is not without its challenges. These challenges involve optimizing the model and controller banks ensuring system stability when dealing with uncertainties in the local models and enabling smooth switching between model-controller pairs. This paper addresses these challenges by presenting a comprehensive approach. Firstly, the optimal model bank is designed using an automatic clustering approach. Then, the design of the adaptive multi-model predictive controller bank and a supervisor algorithm capable of performing soft switching are discussed. The proposed control system exhibits the capability to ensure closed-loop system stability within each individual subspace, as well as during the transitioning between distinct subspaces. This stability is preserved even in the face of inherent uncertainties associated with the local models comprising the model bank. To evaluate and validate the performance of the proposed control system, it is applied to a satellite attitude control system. The results confirm the effectiveness and performance of the control system. The proposed control system holds promise for controlling highly nonlinear, complex, or switched systems, ensuring closed-loop system stability, and achieving high control performance.

Research on robust fault-tolerant cooperative control for multi-stage satellites

Abstract The ultra-agile, ultra-stable, and ultra-pointing platform (ASP) is introduced on the basis of the satellite platform by using two-stage control to realize stable control and agile ability of the payload. In order to improve the reliability and attitude control capability of multi-stage satellites with a two-dimensional scanning motion mechanism, a robust fault-tolerant cooperative control algorithm for multi-stage satellites is proposed in this paper when the actuators of the ASP are faulty. Firstly, a dynamic model of a multi-stage satellite and typical fault models of actuators are established. The impact of faults on the multi-stage system is also analyzed in this paper. Secondly, a sliding mode fault observer is proposed for multi-stage satellites aiming at solving the problem of actuator failure. An adaptive sliding mode fault-tolerant control algorithm is designed, and the switch function is also improved which is chattering-free. The stability of the proposed controller is proved by using the Lyapunov stability principle. Finally, the effectiveness of the proposed control algorithm is verified through numerical simulations, and the comparison between four other fault-tolerant control algorithms demonstrates the superiority of the algorithm proposed in this paper.

Numerical simulation of influence of jet flow parameters on cone-cylinder-flare configuration

Abstract Reaction control system technology is used to realize attitude control or trajectory change. The hot jet effect should be considered to get more accurate aerodynamic characteristics as the flight vehicle develops. The simulation for hot jet flow needs more calculation resources, so it is important to research the suitable similarity parameters of jet flow. Then, we can use cold jet flow to simulate hot jet flow. In this paper, the influence of jet flow parameters is numerically studied on cone-cylinder-flare configuration. The numerical simulation method for hot jet flow is established, containing finite volume method, multi-component three-dimensional Reynolds Navier-Stokes equation with source terms, multi-block patched grid technique, and fully implicit processing method. The numerical method is verified by using experimental reference results, and the grid independence is assured. The numerical results reveal that the cold jet flowfield under the same mass flow ratio is more similar to the hot jet flowfield than the cold jet flowfield under the total temperature of 293 K. The maximum amplification factor difference between cold and hot jet flow is reduced from 14.1% to 1.2%.

Study of the features of angular stabilization of spacecraft with flexible struc-tural elements with the use mobile control methods

The development of space power engineering is one of the well-known lines in rocket and space science and innovative technologies which attracts the attention of many scientists and researchers. Engineering solutions in space-based solar power plant design and wireless space-to-Earth and satellite-to-satellite power transmission and power spacecraft control methods have been substantiated theoretically to sufficient depth. However, despite this, there is a need to improve methods for and approaches to the development of an optimal design methodology for power spacecraft. A way to improve existing approaches to the development of space-based solar power plants and power satellites may be the use of mobile control methods in the development of an attitude and orbit control system. Such methods allow one to reduce power consumption for control operations. The goal of this paper is to study the features of mobile control and construct a methodology for the development of solar power satellites’ attitude and orbit control system (AOCS) using mobile control algorithms. The paper considers the features of mobile control algorithm synthesis for the attitude control and stabilization of solar power spacecraft (solar power plants and power satellites). Power spacecraft control tasks are classified, and the expediency of using mobile control methods is justified. An analysis is made for the stability problem that arises in controlling power spacecraft with flexible elements. The paper presents methodological recommendations on determining the AOCS design parameters for space-based solar power plants and power spacecraft for wireless satellite-to-satellite power transmission. This methodology may be used in power satellite development.

Does Green-Label Influence Green Purchase Intention, Attitude, Subjective Norms, Behavioral Control, and Willingness To Pay as Moderation?

The purpose of this study was to test and analyze influenced eco-labels, attitudes, subjective norms, and behavioral control on green purchase intention, as well as willingness to pay as a mediator to strengthen the influence green purchase intention (GPI) on green purchase behavior (GPB). The population of this study were Millennials and Gen Z who had purchased green products in Jabodetabek. The number of samples was 181 samples, determined based on Hair's Theory which allows for an unknown population. The sampling technique used nonprobability sampling and purposive sampling. Data analysis used the Least Square Partial Structural Equation Model (PLS-SEM). The results showed that eco-labels did not influence green purchase intention, but influenced green attitude and behavioral control. Conversely, ecolabels did not influence subjective norms. Furthermore, willingness to pay was unable to moderate the influence of green purchase intention on green purchase behavior.

Swiftly Chasing Gravitational Waves across the Sky in Real Time

We introduce a new capability of the Neil Gehrels Swift Observatory, dubbed “continuous commanding,” that achieves 10 s latency response time on orbit to unscheduled target-of-opportunity requests received on the ground. We show that this will allow Swift to respond to premerger (early-warning) gravitational-wave (GW) detections, rapidly slewing the Burst Alert Telescope (BAT) across the sky to place the GW origin in the BAT field of view at or before merger time. This will dramatically increase the GW/gamma-ray burst (GRB) codetection rate and enable prompt arcminute localization of a neutron star merger. We simulate the full Swift response to a GW early-warning alert, including input sky maps produced at different early-warning times, a complete model of the Swift attitude control system, and a full accounting of the latency between the GW detectors and the spacecraft. 60 s of early warning can double the rate of a prompt GRB detection with arcminute localization, and 140 s guarantees observation anywhere on the unocculted sky, even with localization areas ≫1000 deg2. While 140 s is beyond current GW detector sensitivities, 30–70 s is achievable today. We show that the detection yield is now limited by the latency of LIGO/Virgo cyberinfrastructure and motivate a focus on its reduction. Continuous commanding has been integrated as a general capability of Swift, significantly increasing its versatility in response to the growing demands of time-domain astrophysics. We demonstrate this potential on an externally triggered fast radio burst (FRB), slewing 81° across the sky, and collecting X-ray and UV photons from the source position <150 s after the trigger was received from the Canadian Hydrogen Intensity Mapping Experiment, thereby setting the earliest and deepest such constraints on high-energy activity from nonrepeating FRBs. The Swift Team invites the community to consider and propose novel scientific applications of ultra-low-latency UV, X-ray, and gamma-ray observations.