Global Attitude Research Articles

A novel smooth quaternion-based attitude tracking control

The fact that two antipodal points in the quaternion characterize the same physical attitude depicts that the design of the global attitude control system is uneasy. This study deals with a smooth quaternion-based attitude tracking control system that is composed of a differential equation known as the augmented dynamical system. The augmented dynamical system plays such an important role that it is possible to conduct a novel perspective on viewing the set containing all possible motions as not a manifold. Therefore, the topological obstruction does not exist. The designed attitude tracking control system has a guarantee of stability in the large within a set containing all possible motions. It is able to avoid the unwinding phenomenon, and it is noise-induced chattering-free since there is no discontinuity. Furthermore, we show that the smooth attitude tracking control system has an integral input-to-state stability (iISS) guarantee in the presence of uncertainties in the moment of inertia and environmental disturbance. Simulations carried out show the effectiveness of the designed attitude tracking control system.

Construction and kinematic performance analysis of a suspension support for wind tunnel tests of spinning projectiles based on wire-driven parallel robot with kinematic redundancy

This paper presents a novel suspension support tailored for wind tunnel tests of spinning projectiles based on Wire-Driven Parallel Robot (WDPR), uniquely characterized by an SPM (Spinning Projectile Model)-centered mobile platform. First, an SPM-centered mobile platform, featuring two redundant and another unconstrained Degree of Freedom (DOF), and its suspension support mechanism are designed together, collectively constructing a WDPR endowed with kinematic redundancy. Afterward, the kinematics of the mechanism, boundary equations for the redundant DOFs, and relevant kinematic performance indices are then proposed and formulated. The results from both prototype experiments and numerical assessments are presented. The capability of the support mechanism to replicate the complex coupled motions of the SPM is verified by the experimental results, while the proposed kinematics and boundary equations are also validated. Furthermore, it is revealed by numerical assessments that the redundant DOFs of the mobile platform exert a minimal impact on the kinematic performance of the suspension support. Finally, the optimal global attitude performance is obtained when these DOFs are set to zero if they are restricted to constants. However, local attitude performance can be further improved by the variable values.

Utilizing Crushed Limestone as a Sustainable Alternative in Shotcrete Applications.

Solving the challenges facing the mining industry is crucial for shaping the global attitude towards clean energy technologies associated with critical minerals extracted from depth. One of these challenges is the well-known explosion-like fractures (rockbursts) or spalling failures associated with the initiation of internal cracks. To prevent such catastrophic failure, shotcrete, as a cement grout, is widely used in tunnel support applications. In areas where the tunnels are constructed within the limestone strata using tunnel boring machines (TBM), drilling, and/or blasting, millions of cubic meters of crushed limestone (CL) in powder form are extracted and landfilled as waste. Given the fact that natural sand consumption as a raw material in the construction industry exceeds previous records, recycling of such excavation material is now becoming increasingly needed. From this perspective, this study aims to utilize crushed limestone as a potentially sustainable alternative to natural sand in shotcrete applications in deep tunnels. Accordingly, several strength characterization and crack initiation determinations through various stress-strain-based models were carried out on cylindrical samples containing different proportions of crushed limestone. By increasing the crushed limestone content in the shotcrete mix, the crack initiation stress (as a measure of the in situ spalling strength) increased as well. The results suggest that the crushed limestone has good potential to replace the natural sand in the shotcrete mixture used in tunnel support applications.

Global Stabilization of Antipodal Points on $n$-Sphere With Application to Attitude Tracking

Existing approaches to robust global asymptotic stabilization of a pair of antipodal points on unit $n$-sphere $\mathbb{S}^n$ typically involve the non-centrally synergistic hybrid controllers for attitude tracking on unit quaternion space. However, when switching faults occur due to parameter errors, the non-centrally synergistic property can lead to the unwinding problem or in some cases, destabilize the desired set. In this work, a hybrid controller is first proposed based on a novel centrally synergistic family of potential functions on $\mathbb{S}^n$, which is generated from a basic potential function through angular warping. The synergistic parameter can be explicitly expressed if the warping angle has a positive lower bound at the undesired critical points of the family. Next, the proposed approach induces a new quaternion-based controller for global attitude tracking. It has three advantageous features over existing synergistic designs: 1) it is consistent, i.e., free from the ambiguity of unit quaternion representation; 2) it is switching-fault-tolerant, i.e., the desired closed-loop equilibria remain asymptotically stable even when the switching mechanism does not work; 3) it relaxes the assumption on the parameter of the basic potential function in literature. Comprehensive simulation confirms the high robustness of the proposed centrally synergistic approach compared with existing non-centrally synergistic approaches.

VID-SLAM: Robust Pose Estimation with RGBD-Inertial Input for Indoor Robotic Localization

This study proposes a tightly coupled multi-sensor Simultaneous Localization and Mapping (SLAM) framework that integrates RGB-D and inertial measurements to achieve highly accurate 6 degree of freedom (6DOF) metric localization in a variety of environments. Through the consideration of geometric consistency, inertial measurement unit constraints, and visual re-projection errors, we present visual-inertial-depth odometry (called VIDO), an efficient state estimation back-end, to minimise the cascading losses of all factors. Existing visual-inertial odometers rely on visual feature-based constraints to eliminate the translational displacement and angular drift produced by Inertial Measurement Unit (IMU) noise. To mitigate these constraints, we introduce the iterative closest point error of adjacent frames and update the state vectors of observed frames through the minimisation of the estimation errors of all sensors. Moreover, the closed-loop module allows for further optimization of the global attitude map to correct the long-term drift. For experiments, we collect an RGBD-inertial data set for a comprehensive evaluation of VID-SLAM. The data set contains RGB-D image pairs, IMU measurements, and two types of ground truth data. The experimental results show that VID-SLAM achieves state-of-the-art positioning accuracy and outperforms mainstream vSLAM solutions, including ElasticFusion, ORB-SLAM2, and VINS-Mono.

The motion of three-dimensional fractal aggregates in homogeneous shear flow

A model for the motion of aggregates in low Reynolds number flow has been established by utilizing the Stokesian dynamics and applying the quaternion as global attitude parameter. The model has been validated by the theorical solution of sphere doublet in shear flow, the simple helical aggregates, and the experiment on the settling of some specific objects in still water. The motion of fractal aggregates has been further studied, aiming to get better understanding of the dynamic behavior of fine-grained sediment flocs in shear flow. The fractal aggregates have been generated using the diffusion-limited aggregation model, which has similar fractal dimension as natural flocs. The results illustrate that fractal aggregates undergo a complex rotation in shear flow, which exhibit a bi-periodic characteristic. The motion of a particle within the fractal aggregate shows three-dimensional trajectory in a simple shear flow, affected by its initial orientation. The major rotation period is approximately 4π/γ̇, which corresponds to the rotation period of a sphere with shear strength γ̇. The deviation decreases with the increase in the size of the fractal aggregate.

Data-driven real-time prediction for attitude and position of super-large diameter shield using a hybrid deep learning approach

The presented research introduces a novel hybrid deep learning approach for the dynamic prediction of the attitude and position of super-large diameter shields - a critical consideration for construction safety and tunnel lining quality. This study proposes a hybrid deep learning approach for predicting dynamic attitude and position prediction of super-large diameter shield. The approach consists of principal component analysis (PCA) and temporal convolutional network (TCN). The former is used for employing feature level fusion based on features of the shield data to reduce uncertainty, improve accuracy and the data effect, and 9 sets of required principal component characteristic data are obtained. The latter is adopted to process sequence data in predicting the dynamic attitude and position for the advantages and potential of convolution network. The approach’s effectiveness is exemplified using data from a tunnel construction project in China. The obtained results show remarkable accuracy in predicting the global attitude and position, with an average error ratio of less than 2 mm on four shield outputs in 97.30% of cases. Moreover, the approach displays strong performance in accurately predicting sudden fluctuations in shield attitude and position, with an average prediction accuracy of 89.68%. The proposed hybrid model demonstrates superiority over TCN, long short-term memory (LSTM), and recurrent neural network (RNN) in multiple indexes. Shapley additive exPlanations (SHAP) analysis is also performed to investigate the significance of different data features in the prediction process. This study provides a real-time warning for the shield driver to adjust the attitude and position of super-large diameter shields.

Is the Clinical Practicum in Addiction Treatment Facilities an Effective Educational Intervention to Improve Nursing Students' Attitudes Toward Alcohol Use Disorders?

The paucity of education and training on alcohol use disorders (AUDs) in nursing curricula is the main predictor of negative attitudes and results in limited knowledge access and delivery of health care for persons experiencing these problems. Although experts advocate increasing the time devoted to alcohol-related content in a crowded curriculum, didactic strategies for teaching about addiction in prequalifying nursing education have been discussed. This study aimed to verify the effectiveness of an educational experience that integrated clinical practicum experience in addiction treatment facilities for nursing students' attitudes. A quasi-experimental one-group study with pre-and-post 3-month follow-ups was carried out with 108 nursing students who answered the Attitudes Scale toward Alcohol, Alcohol Use Disorder, and Patients with Alcohol Use Disorders. The effect of the clinical practicum was apparent, with statistically significant changes to more positive global attitude scores in all measures. Previous educational intervention for AUDs during nursing education was a predictor of positive attitudes (OR = 7.21, p < .04). Students' self-perceived skills and professional preparation to deliver and direct care for patients with AUDs improved after the intervention, suggesting that clinical practice influenced students' skills for AUD identification across nursing practice. Previous contact with this population with lack of training in substance use disorder seems to favor negative attitude development. Clinical practicum experience in addiction treatment facilities improved nursing students' attitudes toward AUDs and patients with AUDs, and its effects were sustained 3 months later.

Robust Global Attitude Control: Random Reset Rule

In this paper, we propose a new random reset rule for attitude control systems, where a new Lyapunov-Foster function implies the robust global attitude control without adding any constraints on the random reset rule, except the support domain for the involved random variables. Compared with deterministic binary logic variables, random variables introduce an automatically adjusted hysteresis half-width for each reset process, thus bring a flexible tradeoff between the hysteresis-induced inefficiency for avoiding unwinding phenomenon and the robustness to measurement noise. A benchmark case for the attitude tracking control of a miniature quadrotor prototype verifies the designed random reset rule.

Small-satellite attitude consensus using limited-stroke oscillating-mass actuators with continuous sinusoidal controls

This paper addresses attitude consensus for a formation of small satellites where each satellite relies on internal oscillating-mass actuators. Unlike traditional flywheel systems, the actuators considered in this work cannot perform unrestricted rotations. The rotational stroke of each actuator on the ith satellite is limited to [−αi,αi] rad, where αi>0. We develop and analyze two feedback control methods for attitude consensus using limited-stroke oscillating-mass actuators. The first algorithm achieves local attitude consensus for the case where each satellite uses relative-attitude feedback of its neighbor satellites. The second algorithm achieves almost global attitude consensus for the case where each satellite uses absolute-attitude feedback of its neighbor satellites. Both methods use control signals that are continuous and piecewise sinusoidal but whose derivatives can contain discontinuities. The main results show that each method achieves consensus and that the strict actuator stroke constraint is satisfied. Each method is demonstrated by a numerical simulation of a small-satellite formation in deep space.

Global Attitude Synchronization for Networked Rigid Bodies Under Directed Topologies

This paper is devoted to dealing with global attitude synchronization problems for networked rigid bodies subjected to directed topologies and arbitrary initial orientations. To avoid the asynchronous pitfall where only vector parts of rigid bodies reach agreement on some identical value but scalar parts do not, multiplicative quaternion errors are incorporated to develop attitude synchronization protocols for rigid bodies with absolute attitude measurements. It is shown that global synchronization of networked rigid bodies is achieved if and only if the directed topology is quasi-strongly connected. Simultaneously, a novel double-energy-function analysis method, equipped with an ordering permutation technique for the scalar parts and a coordinate transformation mechanism, is constructed for the quaternion behavior analysis of networked rigid bodies. In particular, global synchronization works well with our analysis method, regardless of the highly nonlinear and strongly coupling problems resulting from multiplicative quaternion errors, which seriously hinder the traditional analysis of global synchronization for networked rigid bodies. Simulations for networked spacecraft are presented to validate global synchronization performances under different directed topologies.

Hybrid triggering design for global attitude synchronization of networked rigid bodies

This paper is devoted to dealing with the problem of global attitude synchronization for quaternion-based multiple rigid bodies, regardless of the general directed topologies of networks and arbitrary initial orientations of rigid bodies. A novel canonical quaternion is constructed to represent all physical attitudes of rigid bodies such that the pseudo-synchronization of their quaternion representations (namely, the quaternions’ vector parts of all rigid bodies reach agreement on some identical value, whereas their scalar parts do not) can be precluded. Moreover, to reduce unnecessary communication requirements of rigid bodies, a hybrid triggering mechanism involving both the time regulation and neighbors’ non-real-time information is proposed, with which a distributed protocol is developed by leveraging the constructed canonical quaternion. It is shown that the presented protocol for rigid bodies over directed networks can simultaneously realize the global attitude synchronization and naturally exclude the Zeno behavior. In addition, these observations are also validated via the application of our hybrid triggering protocol to networked spacecraft.

Optimized Design of Flexible Quick-Change System Based on Genetic Algorithm and Monte Carlo Method

In order to realize the high efficiency and precision clamping of large workpieces with several processes and multiple species processing, the distribution number and position of the zero point clamping unit in the flexible quick-change process system for big thin-walled cylindrical structural parts are presented. The error model of the flexible quick-change process system is established by the Monte Carlo method, which is used to optimize the system structure design. The error variation of the flexible quick-change process system under the action of transposition and extreme working conditions such as cutting force is revealed, and further analysis on the sensitivity of the workpiece’s global displacement error and global attitude error to each error source is carried out. After the optimization, a high-quality, cost-effective, flexible quick-change clamping system is created. The three-coordinate measurement experiment is used to test the functionality and accuracy of the flexible quick-change process system. A significantly improved level of the system’s repetitive positioning accuracy (less than 0.01 mm) is detected. Importantly, the flexible quick-change system obtained by the combinatorial optimal design method has been successfully applied to the production of aerospace components with improved quality and efficiency.

Synergistic potential functions from single modified trace function on SO(3)

This paper is about the construction of a family of centrally synergistic potential functions from a single modified trace function on SO(3). First, we demonstrate that it is possible to complete the construction through angular warping with multiple directions, particularly effective in the unresolved cases in the literature. Second, it can be shown that for each potential function in the family, there exists a subset of the family such that the synergistic gap is positive at the unwanted critical points. This allows the switching condition to be checked within the selected subsets while implementing synergistic hybrid control. Furthermore, the positive lower bound of synergistic gap is explicitly expressed by selecting a traditional warping angle function. Finally, we apply the proposed synergistic potential functions to obtain robust global attitude tracking.

Omicron virus emotions understanding system based on deep learning architecture.

Emotions understanding has acquired a significant interest in the last few years because it has introduced remarkable services in many aspects regarding public opinion mining and recognition in the field of marketing, seeking product reviews, reviews of movies, and healthcare issues based on sentiment understanding. This conducted research has utilized the issue of Omicron virus as a case study to implement a emotions analysis framework to explore the global attitude and sentiment toward Omicron variantas anexpression of Positive feeling, Neutral, and Negative feeling. Because since December 2021. Omicron variant has gained obvious attention and wide discussions on social media platforms that revealed lots of fears and anxiety feeling, due to its rapid spreading and infection ability between humans that could exceed the Delta variant infection. Therefore, this paper proposes to develop a framework utilizes techniques of natural languages processing (NLP) in deep learning methods usingneural network model of Bidirectional-Long-Short-Term-Memory (Bi-LSTM) and deep neural network (DNN) to achieve accurate results. This study utilizes textual data collected and pulled from the Twitter platform (users' tweets) for the time interval from 11-Dec.-2021 to 18-Dec.-2021. Consequently, the overall achieved accuracy for the developed model is 0.946%. The produced results from carrying out the proposed framework for sentiment understanding have recorded Negative sentiment at 42.3%, Positive sentiment at 35.8%, and Neutral sentiment at 21.9% of overall extracted tweets. The acquired accuracyusing data of validation for the deployed model is 0.946%.

Global robust attitude tracking with torque disturbance rejection via dynamic hybrid feedback

In this paper an approach to the design of robust global attitude tracking controllers for fully actuated rigid bodies is proposed. The challenge of simultaneously dealing with topological obstructions to global attitude tracking and with disturbances affecting the attitude dynamics is tackled by means of a hybrid hierarchical design that exploits the cascade structure of the underlying mathematical model. The proposed hierarchical strategy is based on an inner–outer loop paradigm comprising a dynamic control law for angular velocity tracking (inner loop) and a hybrid control law for attitude tracking (outer loop). By leveraging recent tools for the stability analysis of hybrid systems, we prove a robust global tracking property by assuming mild properties on the dynamics of the velocity feedback. We also discuss a few relevant examples satisfying these properties, encompassing harmonic disturbance compensators and conditional integrators, capable of rejecting unknown constant disturbances with an intrinsic anti-windup action.

AN ANALYTICAL STUDY ON PUNITIVE AND RESTORATIVE JUSTICE UNDER CRIMINAL LAW IN INDIA

We are living in a perilous time in world history, beset by terrible threats that will soon materialise. We now feel more strongly than ever that we are living a dishonest and unappreciated existence. Is this due to a flawed legal system, a corrupt police force, an unequal application of the law, a lack of strong economic or political viewpoints, or pervasive judicial corruption that has swallowed everything valuable from the victim perspective and propelled the administration of criminal justice? Because it is commonly known that criminal justice systems all over the globe completely favour the accused, pre- and post-trial rights have been established for them. India is not an exception to this global attitude mentioned above. India's status quo in relation to other countries in the world, however, has been distinctive. The adversarial system of criminal justice that India has chosen has further fostered this. The pre- and post-trial rights of the defendant have been acknowledged in our nation both legally and legally procedurally. The victim, who is a key component of the criminal justice system, has no place in the Indian system other than as a witness when necessary. As a result, this study provides a critical analysis of the factors and information pertaining to India's strong tendency for punitive and restorative justice.

Processing of Gypsum Construction and Demolition Waste and Properties of Secondary Gypsum Binder

The waste amount coming from construction and demolition (CDW) has significant volume and potential to provide the backbone of a secondary material bank. Up to now, little attention is paid to waste gypsum recycling from CDW while a shift in global attitude toward waste management brings motivation to use CDW gypsum as secondary raw material. The present research investigates the properties of gypsum binder obtained from secondary raw materials originating from CDW. Three types of drywall boards and cast monolithic gypsum from interior walls, treated in the laboratory, and a gypsum binder was obtained. Comparison has been studied and the most effective solutions regarding CDW treatment are represented. Separation, crushing, and milling were done. DTA/TG, XRD, SEM, and particle size distribution were characterized by CDW gypsum. The heat treatment temperature was selected at 130 °C for 4 or 24 h and 180 °C for 4 h. Consistency, set time, and mechanical properties were characterized. Results indicate that a gypsum binder with a strength up to 3.7 MPa can be obtained. Low strength is associated with fineness of CDW gypsum and a high water/gypsum ratio (from 0.6 to 1.396). Gypsum content in CDW (38 to 92 wt.%) should be considered as an important factor during gypsum CDW recycling.

Further development of the Teacher Attitudes to Inclusion Scale: principal components and Rasch analysis

ABSTRACT Providing an effective and high-quality education for all children and young people remains a significant challenge throughout the world. Disputes and contradictions contribute to the prevailing debate as to the justification and merits of inclusive education. One of the reoccurring themes within the literature on inclusive education is the relationship between the successful application of teachers’ knowledge, skills, and abilities utilised to include inclusive strategies in their classrooms, and their attitude towards inclusion. A teacher with more positive attitudes will be more accepting of students, build more successful relationships with them, aid in a child’s sense of belonging, student academic success and social integration. To address this issue, the Teacher Attitudes to Inclusion Scale (TAIS) was developed by the first author to measure the attitudes of qualified (in-service) teachers towards inclusive education. Using an Exploratory Principal Components Analysis and Reliability, a revised version of the TAIS, the TAIS-R provides a psychometrically validated measure of two constructs – a global attitude and a personal attitude towards inclusive education that provides an accurate evaluation tool for research and practice.

Quaternion-Based Attitude Synchronization With an Event-Based Communication Strategy

This paper designs an event-triggering based communication strategy for the global attitude synchronization of a network of rigid bodies. To overcome the topological constraint on the manifold <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$SO(3)$ </tex-math></inline-formula> , the quaternion-based hybrid control strategy is designed using a binary logic variable, relying on the relative measurements of adjacent rigid bodies, to determine the torque orientation. The Zeno-free distributed event-triggering strategies (ETSs) are designed combining with the reset of the binary logic variable to generate discrete communication instants, where only the corresponding parts of the control inputs are updated at those discrete instants. By assuming perfect knowledge of the rigid bodies’ dynamics and considering uncertainties and/or exogenous disturbances simultaneously, nominal and robust cases are analyzed to ensure the global attitude synchronization, respectively. The effectiveness of the main results is demonstrated by considering the attitude synchronization of six miniature quadrotor prototypes.