Verification Of Stability Research Articles

A Model-Free Control Scheme for Rehabilitation Robots: Integrating Real-Time Observations with a Deep Neural Network for Enhanced Control and Reliability

Effective control of rehabilitation robots is of paramount importance and requires increased attention to achieve a fully reliable, automated system for practical applications. As the domain of robotic rehabilitation progresses rapidly, the imperative for precise and dependable control mechanisms grows. In this study, we present an innovative control scheme integrating state-of-the-art machine learning algorithms with traditional control techniques. Our approach offers enhanced adaptability to patient-specific needs while ensuring safety and effectiveness. We introduce a model-free feedback linearization control method underpinned by deep neural networks and online observation. While our controller is model-free, and system dynamics are learned during training phases, we employ an online observer to robustly estimate uncertainties that the systems may face in real-time, beyond their training. The proposed technique was tested through different simulations with varying initial conditions and step references, demonstrating the controller’s robustness and adaptability. These simulations, combined with Lyapunov’s stability verification, validate the efficacy of our proposed scheme in effectively controlling the system under diverse conditions.

Natural thermometers in concrete: Stability and reliability verification of inclusion decrepitation thermoacoustic thermometry

The fire-exposure temperature of concrete directly determines the degree of damage to its microstructure and the performance of concrete. Therefore, an accurate assessment of the fire-exposure temperature of concrete is crucial. But to date, there is not yet an accurate, practical, and effective method for measuring the internal temperature of concrete after fire. Based on the discovery that fluid inclusions in concrete act as natural thermometers, this paper investigates the scientific principles and experimental evidence of the decrepitation thermometry of inclusions. By extracting quartz sand samples from the interiors of concrete members after a fire and performing an inclusion decrepitation test on these samples, the maximum fire-exposure temperature of concrete can be determined with a high degree of accuracy. The test results reveal that the natural sand used in construction typically contains fluid inclusions, indicating that the necessary conditions for inclusion decrepitation thermometry are satisfied for concrete structures. In this study, standard quartz sand samples were configured, and inclusion decrepitation temperature measurements were conducted after subjecting the samples to different heating rates, cooling methods, thermostatic durations, and standing times after fire. The test results indicate that the impact of the aforementioned factors on the inclusion decrepitation temperature measurement is not evident. The maximum relative error between all temperature measurement results and the actual heating temperature is <10 %, and the average relative error is <2.5 %. The experimental results show that fluid inclusions are natural thermometers in concrete. After a fire, the maximum temperature experienced in the concrete can be quantitatively assessed using the initial decrepitation temperature of the inclusion. This method possesses the advantages of being a scientific test method and providing accurate temperature measurements without any indirect analysis or calculation using simple test equipment, sample preparation, and operation.

Similarity Distribution Density: An Optimized Approach to Outlier Detection

When dealing with uncertain data, traditional model construction methods often ignore or filter out noise data to improve model performance. However, this simple approach can lead to insufficient data utilization, model bias, reduced detection ability, and decreased robustness of detection models. Outliers can be considered as data that are inconsistent with other patterns at certain specific moments and are not always negative data, so their emergence is not always bad. In the process of data analysis, outliers play a crucial role in sample vector recognition, missing value processing, and model stability verification. In addition, unsupervised models have very high computation costs when recognizing outliers, especially non-parameterized unsupervised models. To solve the above problems, we used semi-supervised learning processes and used similarity as a negative selection criterion to propose a local density verification detection model (Vd-LOD). This model establishes similarity pseudo-labels for multi-label and multi-type samples, verifies the accuracy of outlier values based on local outlier factors, and increases the detector’s sensitivity to outliers. The experimental results show that under different parameter settings with varying outlier quantities, Vd-LOD outperforms other detection models in terms of the significant increase in average time consumption caused by verifying the presence of relationships, while also achieving an approximate 6% improvement in average detection accuracy.

Towards a stability verification of two‐span members based on experimental and numerical investigations

AbstractState‐of‐the‐art stability design methods of the current and future Eurocode 3 are based on idealized, simply supported members with fork restraints. However, in real‐world structural engineering applications, continuous members or frame structures are more common. The verification of these members often requires complex geometrically nonlinear computations. This paper addresses the extension of simplified methods to structural systems. The basis is laid with experimental, numerical and analytical studies on the stability behavior of two‐span members with doubly symmetric I‐sections in bending, axial compression and torsion. Five‐point bending tests were conducted to analyze the buckling behavior of two‐span members. The experimental results validate a numerical model subsequently used to extend the data basis. A comparison of the numerical load capacities with the results of the simplified method for the buckling resistance according to Annex C.2 of EN 1993‐1‐1:2022 reveals the method's applicability. The sensitivity analysis of the method to various parameters identifies potential for improvement concerning the capture of the influence of bending moments about the weak axis and warping moments, as well as the influence of lateral‐torsional buckling for stocky members.

QUANTITATIVE ASSESSMENT OF THE STABILITY OF PORTABLE RADIOGRAPHIC MONITORING TOOLS TO THE FACTORS OF A TRANSPORT ACCIDENT BY THE METHOD OF FINITE ELEMENT CALCULATIONS

A method of quantitative finite-element verification of stability of design and technological solutions of new generation portable radiographic equipment to the factors of transport accident at the stage of automated design of mathematical solid model of the shutter-type radiation head using software packages: "ZENIT-95" and "LS-DYNA" is proposed for consideration. The need for virtual quantitative assessment of stability of developed gamma detector components to emergency transport conditions at the design stage is largely due to the need to reduce costs for full-scale prototyping of technical solutions and test emergency tests. At the same time, production of prototypes equipped with radionuclide emitters without substantiating confirmation of the consistency of design solutions to extreme transportation conditions is certainly risky. Minimization of risk of making incorrect technical decisions at the stage of designing of radiographic control facilities of new generation with confirmation of consistency of design solutions to conditions of emergency transportation can be provided with the use of systems of automated design in 3D format and program-calculating modules "LS-DYNA" and "ZENIT-95" by finite-element calculations method. The object of the quantitative analysis of stability of the main functional unit of portable gamma detector to the transport accident factors by the finite element calculations method is a mathematical solid model of the radiation head conditionally containing radionuclide radiator and virtually exposed to transport accident factors: fall from height onto a target; thermal effects of fire. The 3D model of the WG as the main functional part of the gamma detector represents a logically connected system of elements, the state of which can be described by a set of differential equations, the solution of which using digital technology determines the stresses, strains and zones of thermal effect, allowing a quantitative assessment of mechanical strength and thermal stability of the structural solutions of the product. The results of finite element analysis in the software package "LS-DYNA" with a quantitative assessment of structural and strength stability of the radiation head of a gamma detector when falling from height, as well as the results of stability to thermal influence by the example of a finite element model of the radiation head in the software package "ZENIT-95" are presented.

Global Asymptotic Stability of Submodule Capacitor Voltage Self-converging Modular Multilevel Converters Based on Characteristic Root Method

This study presents global asymptotic stability verification of submodule capacitor voltage self-converging modular multilevel converters (SC-MMCs) according to the characteristic root method, which constructs a submodule switching state matrix for voltage balancing control. The mathematical model of MMC is established in form of the state-space equation. It is proved that SC-MMCs have the characteristic of global asymptotic stability at a certain time from the perspective of switching state matrix characteristic roots, according to the theories of Lyapunov stability and continuous-time piecewise linear system stability. Then, the submodule capacitor voltage self-convergence over a period of time is deduced based on the capacitor voltage deviation vector. Under the constraints of linearly independent switching state matrix row vectors, submodule capacitor voltage self-convergence without real-time voltage calculation and feedback can be achieved. The global asymptotic stability of SC-MMCs and the efficacy of submodule capacitor voltage self-convergence based on switching state matrix are testified by simulations.

An adaptive impedance control for dual-arm manipulators incorporated with the virtual decomposition control

The interaction force control problem for the object manipulated by the dual-arm manipulator with the unknown environment is addressed in this paper. An adaptive dual-loop impedance control scheme is designed to meet the three control targets, including the trajectory tracking control of the object, the internal force control of the object with the two arms, and the interaction force control of the object with the unknown environment. Firstly, an adaptive variable impedance control method is proposed in the outer loop to copy with the unknown stiffness and position of the environment. Secondly, an impedance control scheme based on the internal force is designed in the inner loop to plan the internal force and the modified position supplied with the outer-loop control. Thirdly, to realize the reference trajectory supplied with the inner-loop control, the virtual decomposition control (VDC) method is incorporated, which is a recursive adaptive control progress, so that the unknown dynamics of the manipulators is acceptable and the computation complexity is also very low to satisfy the real-time control requirement. The stability verifications of the inner-loop impedance control and the VDC method are given based on the Lyapunov method, and the stability analysis of the outer-loop impedance control is obtained using the Routh criterion. Finally, a plane dual-arm robotic manipulator with three degrees of freedom is used to verify the effectiveness of the proposed control scheme.

Robust Control Method Design for Underactuated Double-Pendulum Overhead Cranes

Overhead travelling cranes are infrastructure for building construction and their main purpose is to ensure accurate and rapid transport of goods to a given location in the shortest possible time without any residual oscillation. The overhead crane is also a typical underdrive method, which has fewer inputs than the amount being controlled. In some practical applications, uneven weight and f-loads on the hook can lead to load and hook oscillations and the bridge crane can develop the so-called double-pendulum properties. This leads to a high degree of coupling and a high degree of non-linearity between the various state variables of the crane system. The study that follows suggests a new energy-coupled control strategy for an underactuated double-pendulum overhead crane with initial control force constraints. Strong robustness and superior control performance to parameter changes and external disturbances are the proposed controller’s noticeable characteristics. To ensure the smooth start of the trolley, a robust control adds the hyperbolic tangent function to the control procedure. In addition, the stability analysis and stability verification of the control system is given by using the LaSalle’s invariance principle and Lyapunov techniques. The simulation results show that the new energy coupling control method has stability and strong robustness under various conditions such as different rope lengths, load quality, target position and external disturbance when the initial control force decreases.

A consistent approach for global buckling of steel structures

AbstractThe ”General Method“ according to chapter 6.3.4 of EN1993‐1‐1 or 8.3.4 of prEN1993‐1‐1 deals with the verification of stability problems of frame and beam structures with loadings in‐plane. The ”General method“ according to Eurocode is intended for the general case of a combined moment and normal force. For the choice of the reduction factor χop, there are two options for applying the reduction curve, either the minimum of lateral torsional buckling (LTB) and flexural buckling (FB) or a weighted combination of both. With the use of analytical derivations, it can be shown that this approach leads to inconsistencies which can possibly lead to incorrect results. In this paper an alternative approach is presented which leads to unification and fully mechanical justification in verification. The approach allows e.g. the verification of stability of an entire frame system directly and without interaction factors (as in the equivalent member method). In addition, the issue of a consistent equivalent imperfection is addressed. With the use of this method, geometrical non‐linear analyses of structures showing out‐of‐plane instability can be omitted; only an in‐plane calculation and a determination of a linear buckling analysis is necessary. Finally, examples are presented in this paper that demonstrate the application of the approach shown.

Optimal interval controller design for uncertain systems

AbstractThe interval controller design is a hot issue for uncertain systems, whereas how to design an optimal interval controller under the premise of ensuring system stability is a difficult problem that needs further study. This paper mainly aims at the single input single output uncertain system to propose an optimal interval controller based on the Kharitonov theorem and an interval optimization algorithm, which can guarantee the stability and optimization of a closed‐loop interval system. According to the Kharitonov theorem, the optimal interval controller design can be transformed into an optimal controller synthesis issue of multiple vertex objects. An interval particle swarm optimization (IPSO) algorithm is then used to optimize the quadratic performance index with interval variables for each vertex object to obtain the solution domains of the controller parameters, and the vertex method is utilized to prevent interval width expansion or divergence in the iteration. Finally, the intersections of the solution domains for all vertex objects are obtained as the optimal interval solution of interval controller parameters. In addition, the stability verification approach of the closed‐loop system and the empirical rule to select the interval particle width are given. Simulation results for typical examples demonstrate that the designed interval controller not only performs optimally but also can robustly stabilize the interval system.

Robustly Cooperative Control of Transient Stability for Power System Considering Wind Power and Load Uncertainty by Distribution Preserving Graph Representation Learning (DPG)

Aiming at the influence of wind power and load uncertainty on the transient stability of a power system under low carbon mode, this paper first proposes a collaborative preventive and emergency control model of transient stability by distribution preserving graph representation learning (DPG). Second, the uncertainty set of wind power output and load demand is studied, and the mathematical form of the two-stage robust transient stability collaborative control model is proposed. Then, the latest artificial intelligence technology is embedded into the global optimization algorithm of the model so as to further improve the solving efficiency of the algorithm. Finally, based on the developed improved two-stage robust optimization framework, an effective collaborative control method for transient stability is developed. The transient stability prediction and control system developed in this project is not only conducive to large-scale wind power grid connection but also expected to make academic contributions to development of power system transient stability and practical simulation verification.

Structural health dynamic monitoring for gear transmission based on guided waves

The rotating machinery has a wide range of applications in many fields. The gear transmission system is one of the key structures of rotating machinery. Once the failure occurs to the gear system, it will destroy the equipment itself and lead the whole industrial production to break. Thus, it is necessary to directly monitor the health condition of the gear system under static and running working conditions. Guided waves method is a technology which has been widely used in the field of structural health monitoring. In this paper, guided waves technology is innovatively applied to the condition monitoring of gear system, which realizes the gear structure direct monitoring for low speed rotating machinery. The piezoelectric transducers integrated with the SMART Layer were placed near the gear mesh region for the direct health monitoring. The feasibility was verified by the guided waves monitoring experiments in a fixed-axis spur gear transmission system. The tooth wear and gear crack were monitored by guided waves under a single working condition. In addition, the stability verification experiment of guided waves was also performed under various low-speed working conditions. To characterize the propagation of gear faults, considering the characteristics of guided waves, a modified health indicator extraction methodology is proposed based on permutation entropy. The results indicated that the guided waves technology has fantastic potential applications in gear transmission system dynamic direct health monitoring.

Identification of extremely GC-rich micro RNAs for RT-qPCR data normalization in human plasma.

We aimed at extending the repertoire of high-quality miRNA normalizers for reverse transcription-quantitative PCR (RT-qPCR) of human plasma with special emphasis on the extremely guanine-cytosine-rich portion of the miRNome. For high-throughput selection of stable candidates, microarray technology was preferred over small-RNA sequencing (sRNA-seq) since the latter underrepresented miRNAs with a guanine-cytosine (GC) content of at least 75% (p = 0.0002, n = 2). miRNA abundances measured on the microarray were ranked for consistency and uniformity using nine normalization approaches. The eleven most stable sequences included miRNAs of moderate, but also extreme GC content (45%-65%: miR-320d, miR-425-5p, miR-185-5p, miR-486-5p; 80%-95%: miR-1915-3p, miR-3656-5p, miR-3665-5p, miR-3960-5p, miR-4488-5p, miR-4497 and miR-4787-5p). In contrast, the seven extremely GC-rich miRNAs were not found in the two plasma miRNomes screened by sRNA-seq. Stem-loop RT-qPCR was employed for stability verification in 32 plasma samples of healthy male Caucasians (age range: 18-55years). In general, inter-individual variance of miRNA abundance was low or very low as indicated by coefficient of variation (CV) values of 0.6%-8.2%. miR-3665 and miR-1915-3p outperformed in this analysis (CVs: 0.6 and 2.4%, respectively). The eight most stable sequences included four extremely GC-rich miRNAs (miR-1915-3p, miR-3665, miR-4787-5p and miR-4497). The best-performing duo normalization factor (NF) for the condition of human plasma, miR-320d and miR-4787-5p, also included a GC-extreme miRNA. In summary, the identification of extremely guanine-cytosine-rich plasma normalizers will help to increase accuracy of PCR-based miRNA quantification, thus raise the potential that miRNAs become markers for psychological stress reactions or early and precise diagnosis of clinical phenotypes. The novel miRNAs might also be useful for orthologous contexts considering their conservation in related animal genomes.

Stability Verification for Heterogeneous Complex Networks via Iterative SOS Programming

This letter is to investigate the stability verification for heterogeneous polynomial complex networks through iterative sum-of-squares programming approach. With polynomial Lyapunov functions, a global asymptotic stability criterion is established for the heterogeneous complex networks under the directed topology. Based on the proposed criterion, the stability verification problem is then reduced to a sum-of-squares optimization problem for solving polynomial matrix inequalities. To process non-convex terms of the polynomial matrix inequalities, we present an iterative sum-of-squares programming approach to turn them into the convex polynomial matrix inequalities, yielding polynomial Lyapunov functions effectively to realize the stability verification. Finally, a numerical example is given to show the fully automatic verification of global asymptotic stability for the heterogeneous polynomial complex networks, which demonstrates the theoretical and algorithmic advantages of the proposed method.

Construction of a novel fluorescent DNA aptasensor for the fast-response and sensitive detection of copper ions in industrial sewage.

Heavy metal pollution poses a great threat to the ecological environment and human health. In particular, copper ions (Cu2+) play a vital role in regulating fundamental life behavior, and the homeostasis of Cu2+ is closely related to many physiological processes. The excessive accumulation of Cu2+ in the human body through food and drinking water will cause severe diseases. However, current conventional Cu2+ detection methods for evaluating the content of Cu2+ are unable to meet the complete requirements of practical Cu2+ analysis in the practical aquatic environment. In this work, we successfully constructed a novel fluorescent DNA aptasensor, which originated from the binding reaction between the improved DNA fluorescent light-up aptamer termed S2T3AT-GC and a small fluorescent molecule termed DFHBI-1T (S2T3AT-GC/DFHBI-1T) to realize fast and anti-interference response for Cu2+via the competitive interaction between Cu2+ and S2T3AT-GC (Cu2+/S2T3AT-GC) destroying the contained G-quadruplex structure of S2T3AT-GC. Moreover, it enables the sensitive detection of Cu2+ with a detection limit of 0.3 μM and a wide detection linear range from 0.3 to 300 μM. Moreover, with the verification of high stability in real industrial sewage samples, this aptasensor exhibits excellent detection performance for Cu2+ analysis in real water samples. Therefore, the proposed aptasensor exhibits great potential in exploring Cu2+-related environmental and ecological research.

Methodology for Designing an Optimal Test Stand for Camera Thermal Drift Measurements and Its Stability Verification

The effects of temperature changes on cameras are realized by observing the drifts of characteristic points in the image plane. Compensation for these effects is crucial to maintain the precision of cameras applied in machine vision systems and those expected to work in environments with varying factors, including temperature changes. Generally, mathematical compensation models are built by measuring the changes in the intrinsic and extrinsic parameters under the temperature effect; however, due to the assumptions of certain factors based on the conditions of the test stand used for the measurements, errors can become apparent. In this paper, test stands for thermal image drift measurements used in other works are assessed, and a methodology to design a test stand, which can measure thermal image drifts while eliminating other external influences on the camera, is proposed. A test stand was built accordingly, and thermal image drift measurements were performed along with a measurement to verify that the test stand did eliminate external influences on the camera. The experiment was performed for various temperatures from 5 °C to 45 5 °C, and as a result, the thermal image drift measured with the designed test stand showed its maximum error of 16% during its most rapid temperature change from 25 °C to 5 °C.

Multivehicle 3D Cooperative Positioning Algorithm Based on Information Geometric Probability Fusion of GNSS/Wireless Station Navigation

With the rapid development of large urban agglomerations and the increasing complexity of urban roads, the high-precision positioning of vehicles has become the cornerstone for the application of vehicle core technologies such as automatic driving. The real-time positioning accuracy of satellite navigation is easily affected by urban canyons, and its stability is poor; thus, how to use the information of the internet of vehicles to achieve satellite navigation fusion has become a difficult problem of multivehicle cooperative positioning. Aiming at this problem, this paper proposes a multivehicle 3D cooperative positioning algorithm based on information geometric probability fusion of GNSS/wireless station navigation (MVCP-GW), which creatively converts various navigation source information into an information geometric probability model, unifies navigation information time–frequency parameters, and reduces the impact of sudden error. Combined with the Kullback–Leibler algorithm (KLA) fusion method, it breaks off the shackles of the probabilistic two-dimensional model and achieves multivehicle three-dimensional cooperative positioning. Compared with the existing cooperative positioning algorithms in the performance of accuracy stability, applicability, obstruction scenarios, and physical verification, the simulation results and physical verification show that the MVCP-GW algorithm can effectively improve real-time vehicle positioning and the stability of vehicle positioning, as well as resist the impact of obstructed environments.

Quality of eucalyptus seedlings of different clones produced at different times

Fast-growing economic forests are important, especially for the cultivation of eucalyptus, as they represent multiple uses associated with the preservation of native forests, generation of jobs, and income. In recent years, there has been significant growth in the number of nurseries that produce clonal eucalyptus seedlings throughout Brazil, and in Espírito Santo soil, most are concentrated in Sooretama, producing seedlings throughout Brazil and for export. However, information on the quality of these seedlings when produced throughout the different seasons is not available. This information can be important, from a practical point of view, for planting and management, and from an experimental point of view, to direct research involving newly produced seedlings. Thus, this work aims to qualify, through the characteristic of DQI, clonal eucalyptus seedlings of different clones and in different seasons, to study the presence of interaction between the clones, and the environments formed by the different seasons of the year. Statistical analyzes were performed from 6,400 eucalyptus seedlings of four clones produced at different times in Sooretama and Jaguaré in the state of Espirito Santo, applying joint evaluation methods to study the interaction between genotypes by environments and verification of adaptability and stability. In the analysis by Annicchiarico and Lin Binns, the G3 genotype showed general adaptability and also showed adaptability in unfavorable environments, and the G2 and G4 genotypes showed adaptability to favorable environments. Despite the specificities of adaptability, all four genotypes can be indicated for planting at any time of the year, as they have an DQI greater than 0.2.

Flight testing verification of lateral-directional dynamic stability of gliding birds due to wing dihedral

PurposeUnlike conventional aircraft, birds can glide without a vertical tail. The purpose of this paper is to analyse the influence of dihedral angle spanwise distribution on lateral-directional dynamic stability by the simulation, calculation in the development of the bird-inspired aircraft and the flight testing.Design/methodology/approachThe gliding magnificent frigatebird (Fregata magnificens) was selected as the study object. The geometric and mass model of the study object were developed. Stability derivatives and moments of inertia were obtained. The lateral-directional stability was assessed under different spanwise distributions of dihedral angle. A bird-inspired aircraft was developed, and a flight test was carried out to verify the analysed results.FindingsThe results show that spanwise distribution changing of dihedral angle has influence on the lateral-directional mode stability. All of the analysed configurations have convergent Dutch roll mode and rolling mode. The key role of dihedral angle changing is to achieve a convergent spiral mode. Flight test results show that the bird-inspired aircraft has a well-convergent Dutch roll mode.Practical implicationsThe theory that birds can achieve its lateral-directional stability by changing its dihedral angle spanwise distribution may explain the stability mechanism of gliding birds.Originality/valueThis paper helps to improve the understanding of bird gliding stability mechanism and provides bio-inspired solutions in aircraft designing.

L-Mix: A Latent-Level Instance Mixup Regularization for Robust Self-Supervised Speaker Representation Learning

Over the recent years, various self-supervised embedding learning methods for deep speaker verification were proposed. The performance of the self-supervised learning framework highly depends on the data augmentation technique, but due to the sensitive nature of speaker information within the speech signal, most speaker embedding training relies on simple augmentations such as additive noise or simulated reverberation. Thus while the conventional self-supervised speaker embedding systems can yield minimum within-utterance variability, their capability to generalize to out-of-set utterance is limited. In order to alleviate this problem, we investigate the utilization of the instance mix (i-mix) regularization for training a self-supervised speaker embedding system. Moreover, we propose a new mixup strategy that applies i-mix on the latent space, instead of the raw acoustic feature domain. In this paper, the i-mix and the proposed l-mix strategy were incorporated into the self-supervised angular prototypical and softmax-based objective functions and were evaluated on the VoxCeleb dataset. From the experimental results, we observe that the self-supervised embedding network can benefit greatly from the i-mix and l-mix strategies in terms of training stability and speaker verification performance.