Joint Control Research Articles

Robust controller design for robot joint position servo systems

For the position servo control problem of a robot joint control system affected by the uncertainty of external disturbances, a model-based robust controller is designed in this paper. The designed controller is capable of suppressing the effect of external uncertain disturbances on the robot joint control system while improving the position servo accuracy and anti-interference capability of the system. The control scheme consists of two parts, the nominal part represents the model of the system dynamics, which is used to suppress any tendency to deviate from the constraints; the second part is the robust term, which is used to deal with the effects of the system due to uncertainties such as external disturbances. First, the boundedness and stability of the designed controller are proved by applying the Lyapunov function. Then, the effectiveness of the designed controller for trajectory tracking in position servoing is numerically simulated using MATLAB software. Finally, in this paper, the experimental equipment is used to build a test platform for joint control of a robot, and the proposed controller is verified experimentally, which confirms the efficiency and stability of the designed controller after the experimental comparison and analysis with some other control algorithms.

Noise generation and contribution of a single-gap bridge expansion joint: An experimental and numerical study

Noise generated from bridge expansion joints during vehicle passing has caused localized environmental problems around the world. The purpose of this paper is to investigate the vibration and noise radiation from the single-gap expansion joint induced by passing vehicles. First, a vibration and noise field test was performed for single-gap expansion joints in the highway ramps. Based on the tested results, two numerical models, involving a 3D tire-bridge expansion joint hybrid finite element model for the vibration analysis, as well as an acoustic boundary element model for the prediction of the noise radiation, were established and validated. The results of the numerical simulations and the field tests are well matched, which offers opportunities to predict the vibration and noise induced by vehicles passing through using the proposed methodology. Finally, the acoustic contribution and sound pressure distribution of different sound sources were discussed. The research showed that, for the single-gap expansion joint, the contribution of tire noise to the total noise level is dominant, and the contribution of structure-borne noise of the expansion joint and girder to the total noise level is insignificant. The findings emphasize the importance of tire noise and provide new ideas for noise control of single-gap expansion joints.

Innovative hip-knee health evaluation: Leveraging pose estimation for single-leg stance postural stability assessment

The analysis of the Hip and Knee (HK) joint angles during single-leg stance (SLS) activity contributes to a great understanding of the bio-mechanical mechanisms and balance maintenance across different age groups. Comprehending how these joints operate in the dynamic state is critical for identifying age-related changes in joint control and stability which can contribute to reducing the risk of falls and improving mobility among people. The possibility of revealing the health of HK joints without resorting to an MRI scan is the significance of this work. By obtaining the data on joint angles during the SLS test, we succeeded in identifying those with a higher risk of HK issues and thus the possibility of early intervention and treatment. Our proposed work is going to use a pose estimation technique that will track the trajectories of HK angles followed by association with instabilities or compromised balance in this way, we can detect the affected joint and evaluate the severity of the issue. The study found stable mean and standard deviation values for HK joints in a young participant, both hips (107.14 ± 5, 96.42 ± 7) and both knees (36.76 ± 7, 44.30 ± 4), these values align with the expected norm (110–120° for the hip and 45–65° for the knee) which indicates stable results. while elderly participants showed high variability and low mean values for both hips (65.42 ± 77, 85 ± 76.67) and both knees (4.15 ± 10.8, 7 ± 18) indicating concerns about joint health and stability. The evaluation of HK joint angles through SLS activity offers new insights.

Carbon starvation drives biosynthesis of high mannose-composition polysaccharides in Ganoderma lucidum

Polysaccharides with high mannose composition exhibit favorable antitumor activity, but there is currently a lack of well-defined and practical approaches to efficiently manufacture this type of polysaccharide. This study explores the impact of carbon utilization on exopolysaccharide (EPS) production and monosaccharide composition in Ganoderma lucidum, aiming to promote the biosynthesis of polysaccharides with high mannose composition. Sucrose supply significantly increased the mannose proportion to 35.52 % in EPS via carbon starvation. To enhance polysaccharide production with high mannose composition, a joint control by carbon starvation and glucose feeding strategy was developed, achieving 0.42 g/L EPS and 18.67 % mannose with 5 g/L glucose supplementation on day 6 in an initial 10 g/L glucose medium. Using this approach, G. lucidum mycelia exhibited normal growth patterns similar to those in sucrose culture. Essentially, carbon starvation upregulated key genes in the GDP-mannose synthesis pathway, including phosphomannose isomerase (PMI), phosphomannose mutase (PMM), and GDP-mannose pyrophosphorylase (GMP), by over 2-fold, facilitating high mannose-composition polysaccharide synthesis in both sucrose and carbon starvation conditions. This work provides insights into the biosynthesis of structurally specific polysaccharides in G. lucidum and offers a foundation for developing polysaccharides with diverse applications in food, medicine, and other fields.

Does the Air Pollution Joint Prevention and Control Policy Work: Evidence from China

Does the Air Pollution Joint Prevention and Control Policy Work: Evidence from China

Reinforcement Learning for Synchronization of Heterogeneous Multiagent Systems by Improved Q-Functions.

This article dedicates to investigating a methodology for enhancing adaptability to environmental changes of reinforcement learning (RL) techniques with data efficiency, by which a joint control protocol is learned using only data for multiagent systems (MASs). Thus, all followers are able to synchronize themselves with the leader and minimize their individual performance. To this end, an optimal synchronization problem of heterogeneous MASs is first formulated, and then an arbitration RL mechanism is developed for well addressing key challenges faced by the current RL techniques, that is, insufficient data and environmental changes. In the developed mechanism, an improved Q-function with an arbitration factor is designed for accommodating the fact that control protocols tend to be made by historic experiences and instinctive decision-making, such that the degree of control over agents' behaviors can be adaptively allocated by on-policy and off-policy RL techniques for the optimal multiagent synchronization problem. Finally, an arbitration RL algorithm with critic-only neural networks is proposed, and theoretical analysis and proofs of synchronization and performance optimality are provided. Simulation results verify the effectiveness of the proposed method.

Research on Remote and Near-Field Gas Collaborative Joint Control Technology in Coal and Gas Outburst Coal Seam

Research on Remote and Near-Field Gas Collaborative Joint Control Technology in Coal and Gas Outburst Coal Seam

Research on Rate Adaptation of Underwater Optical Communication with Joint Control of Photoelectric Domain

As the communication distance changes, the received signal strength of an underwater optical communication system will change, and the range of its variation may not only exceed the dynamic range of the photoelectric detection device but also cause the reliability of communication to change due to the change in the received signal-to-noise ratio. In order to maintain better communication over a longer distance, this paper proposes a rate-adaptive method for underwater optical communication with joint control in the photoelectric domain. In the optical domain, the incident light’s power is adaptively adjusted by controlling the transmittance of the liquid crystal light valve to reduce saturation distortion. In the electrical domain, the constellation distribution is optimized according to the desired probability mass function, and the modulation order is adjusted in real time by estimating the received signal-to-noise ratio of the link. The simulation results show that under the forward error correction (FEC) threshold, the proposed method increases the dynamic range of the photomultiplier tube (PMT) by about 10 dB and expands the dynamic range of the system’s communication distance.

Dynamic modelling and equilibrium manifold of multi‐converter systems: A study on grid‐forming and grid‐following converters in renewable energy power plants

AbstractThis study explores the optimal balance between grid‐forming (GFM) and grid‐following (GFL) converter capacities within power stations to ensure stable operations. The investigation introduces a novel, generic modelling approach for analysing multiple converter systems in the wind and photovoltaic power plants. The method aims to elucidate the dynamic characteristics of the converters in power plants, particularly focusing on the continuity and existence of the equilibrium manifolds and their impact on system stability. Findings reveal a pronounced difference in the recovery capabilities of GFM and GFL following synchronization losses, highlighting an asymmetry in their abilities. Specifically, GFL converters exhibit more effectiveness in reinstating synchrony after synchronization losses caused by GFM. Conversely, GFM demonstrates a lesser capacity to recover from synchronization losses induced by GFL. Furthermore, analysis indicates that when the capacity ratio of GFL to the system's short‐circuit capacity significantly exceeds that of GFM (exceeding a 1:5 ratio), the system experiences an absence of a stable equilibrium point, thereby affecting the synchronization stability of GFM. These conclusions have been validated through joint controller hardware‐in‐the‐loop testing.

A solution for the automatic detection of expansion joints in dam stilling pools using underwater robots

This research addresses the critical challenges of detecting and measuring underwater concrete structure expansion joints (CSEJ), with a particular focus on dam stilling basin environments. A full set of algorithms for detecting expansion joints with underwater robots is presented by the research, enabling real-time and offline analysis along with visualization. These algorithms introduce the use of Convolutional Neural Networks (CNNs) for image feature extraction and segmentation in CSEJ detection, significantly improving accuracy and adaptability over traditional methods. An automated approach known as the Underwater Dam Crack Detection Network (UDCD Network) was introduced by this research. And advanced attention gates and hybrid dilated convolutions to enhance its detection capabilities are incorporated in this system. Additionally, a three-phase deep transfer learning strategy during training was utilized in this research, which significantly improves the model's performance. The research suggests an underwater image restoration algorithm that uses a dark channel prior and dynamic white balance correction to improve image clarity. Furthermore, unique underwater environmental challenges were tackled by this research, such as non-contact measurement of expansion joint widths using a view-geometry-based algorithm and comprehensive detection of dam wall surfaces. Experimental validation demonstrates that the advanced imaging technologies of the proposed underwater robots hold significant potential for autonomous detection of expansion joints in dam stilling basins.

Plantar massage or ankle mobilization do not alter gait biomechanics in those with chronic ankle instability: a randomized controlled trial

ABSTRACT Objectives Chronic ankle instability (CAI) is characterized by persistent neuromechanical impairments following an initial lateral ankle sprain. Ankle joint mobilization and plantar massage have improved the range of motion and static postural control in those with CAI. This study aimed to determine the impact of two-week joint mobilization and plantar massage interventions on gait kinematics and kinetics in individuals with CAI. Methods A single-blind randomized trial was conducted with 60 participants with CAI, randomized into three groups: joint mobilization (n = 20), plantar massage (n = 20), and control (n = 20). The two treatment groups received six 5-min sessions manual therapy over a 2-week, while the control group received no intervention. Gait biomechanics were assessed on an instrumented treadmill before and after the intervention using 3D kinematics and kinetics analysis. Analyses compared biomechanical outcomes from each treatment group to the control group individually using a 1-dimensional statistical parametric mapping. The alpha level was set at p < 0.05. Results Eighteen participants per group were part of the final analysis. No significant main or interactions effects were found for ankle sagittal or frontal plane positions following either intervention (p > 0.05 for all comparisons). COP location relative to the lateral border of the foot also did not change (p > 0.05). Conclusion The findings suggest that two-week joint mobilization and plantar massage interventions do not significantly alter gait biomechanics in individuals with CAI. These results support the need for gait-specific interventions to modify biomechanics in this population.

Efficacy of radial incision combined with tunnel floating line drainage in the treatment of high posterior horseshoe anal fistula and perianal flora: Randomized control trial.

Due to the high prevalence of posterior horseshoe anal fistula and causing numerous complications, this study aimed to investigate the clinical effect of radial incision combined with tunnel floating line drainage (RCTD) and arc incision internal drainage in the treatment of the disease and the influence on perianal flora. Ninety-six subjects treated with high posterior horseshoe anal fistula were stochastically assigned to a joint group (RCTD), and control group (arc incision internal drainage). The operation-related conditions, complication rate, anal function, and recurrence rate of 6 months after operation were compared, and perianal secretions were collected before operation and 1 day after operation to detect the changes of microbial flora. After operation, it was corroborated notable difference between joint group and control group in operation time, intraoperative blood loss, wound healing time, visual analogue scale score 6 hours after operation and phase I cure rate. Chi square test analysis showed notable difference between control group (27.08%) and joint group (10.40%) in incidence of complications, in terms of number of pathogens detected around anus, significantly smaller of the incremental change for the joint subgroup versus the control subgroup 1 day after operation. RCTD can be the best choice for patients with high posterior horseshoe anal fistula. This operation method has the advantages of short operation time, less trauma, fewer complications, fast recovery of anal function, and can also reduce perianal pathogenic bacteria infection.

Energy-Aware Hierarchical Control of Joint Velocities

Nowadays, robots are applied in dynamic environments. For a robust operation, the motion planning module must consider other tasks besides reaching a specified pose: (self) collision avoidance, joint limit avoidance, keeping an advantageous configuration, etc. Each task demands different joint control commands, which may counteract each other. We present a hierarchical control that, depending on the robot and environment state, determines online a suitable priority among those tasks. Thereby, the control command of a lower-prioritized task never hinders the control command of a higher-prioritized task. We ensure smooth control signals also during priority rearrangement. Our hierarchical control computes reference joint velocities. However, the underlying concepts of hierarchical control differ when using joint accelerations or joint torques as control signals instead. So, as a further contribution, we provide a comprehensive discussion on how joint velocity control, joint acceleration control, and joint torque control differ in hierarchical task control. We validate our formulation in an experiment on hardware.

Приближенный метод синтеза непрерывных систем совместного оценивания и управления на основе SDRE технологи

&lt;p&gt;The problem of approximate synthesis of a closed loop nonlinear continuous system of joint estimation and control is considered. An approach is used based on the application of the idea of the separation theorem for linear dynamical systems. Using the factorization operation, a nonlinear system is transformed into a structure similar to a linear system, and algorithms for synthesizing an optimal linear controller and state observer are applied to the transformed system, a feature of which is the dependence of the matrices included in the corresponding Riccati equations on the state vector. An example of the synthesis of a state observer and a controller is given, demonstrating the application of the proposed algorithm.&lt;/p&gt;

The haze reduction effect in china under the digital economy

Haze pollution is becoming increasingly serious as it endangers human health and pressurizes economic development. This study incorporates the digital economy and haze pollution management into a unified research framework, and uses the panel data of 285 cities in China from 2011 to 2020 to precisely identify the haze reduction effect of the digital economy, governance mechanisms, and the non-linear and spatial spillover characteristics of the haze reduction effect in China. The findings demonstrate that: First, the digital economy can significantly reduce haze pollution, and this conclusion still holds after considering endogeneity and other robustness tests. Second, the digital economy can inhibit haze pollution by promoting industrial upgrading and improving total factor energy efficiency, and there is a chain mechanism of “industrial green transformation → total factor energy efficiency” and “factor market distortion → total factor energy efficiency.” However, the haze reduction mechanism of digital economy is heterogeneous to cities with different levels of economic development. Independent transmission mechanism plays a complete intermediary role in cities with low level of economic development, while it plays a partial intermediary role in cities with high level of economic development. Chain transmission mechanism only has an impact on cities with high level of economic development. Third, there is an evident threshold effect on the digital economy, and its haze reduction effect has N-type non-linear characteristics. Meanwhile, Digital economy has threshold effect on the mechanism of restraining haze pollution through total factor energy efficiency, industrial green transformation and factor market distortion. With the development of total factor energy efficiency, industrial green transformation and the reduction of factor market distortion, the haze reduction effect of digital economy can produce a qualitative leap. Fourth, Haze pollution in the spatial, temporal, and spatial dimensions has spillover and warning effects, and the haze reduction effect of digital economy shows strong positive externalities. Therefore, the digital economy should be actively developed, and industrial green transformation and factor market reform should be promoted to curb haze pollution by promoting industrial upgrading, improving energy efficiency and strengthening regional joint prevention and control mechanisms.

High-precision silver electrode based on PEN substrate with robust mechanical performance

Wearable electronics are becoming more and more popular, and in order to ensure the safety and accuracy of wearable electronics, the requirements for the refinement and stability of flexible electrodes are getting higher and higher. The reduction of the amount of ink jet and the reduction of surface charge density and electrostatic stress near the nozzle hole can significantly improve the jetting state of the ink. And nozzle voltage is a key factor that affects them. The spreading of ink droplets on the substrate and the formation of a specific pattern is a dynamic process, which is closely related to the properties of the substrate and the state of the ink droplets. In this paper, PEN is used as the substrate to print silver electrode, with its good thermal stability and good mechanical properties. In order to solve these problems and improve the accuracy of the electrode pattern on PEN substrate, a joint control method of ink drop spacing and nozzle voltage is proposed. It is found that the accuracy of the pattern increases with the increase of the drop spacing. At 45 μm, 90.91 % of the pattern accuracy with the ideal pattern can be achieved. As the nozzle voltage decreases, so does the satellite spot. And at 25 V, it can achieve satellite-free spot printing. Because this method avoids the adjustment of ink properties and the regulation of voltage waveform, this advancement provides a simpler solution for patterned high-precision printed silver electrodes based on flexible substrates. In addition, a silver electrode with a resistivity of 3.43 μΩ·cm was obtained at an annealing temperature of 160 °C. The resistivity change of the electrode only 7.58 % under 5000 times of bending. This is very rare in flexible electrodes.The silver film on the PEN substrate exhibited excellent adhesion under the tape test. XPS depth profiling was used to characterize the elemental states of the films at different depths. The results indicated that the coordination bond between the PEN substrate and the Ag film resulted in good bending resistance, which gives a persuasive explanation for the first time. This result is also due to the precise handling of the film, which also results in a homogeneous distribution of the film. It solves the problem of poor adhesion of silver electrodes based on other substrates or other preparation methods. Therefore, silver electrodes based on PEN substrates have a broad application prospect in the field of flexible wearable electronics.

Measurements of noise emissions for classification of highway expansion joints

In this paper, we classify expansion joints on Slovenian highways by their potential as noise sources. To measure this potential, we utilized a close proximity measurement chain with additional vibration measurements on the car's undercarriage. By combining these measurements, we were able to amass a large amount of noise relatable data specific to expansion joints. By correlating this data to expansion joint types present on a number of bridges and viaducts, we were able to statistically analyse and rank various joint types regarding their noise emission. Our previous research activities focused on noise complaints associated with specific cases that showed that the problem can be very annoying, even though it was quite localized. Our study opens up a new way to assess expansion joints during regular close proximity measurements on the road network, and simultaneously presents a quantifiable measurement data basis to exhibit the expansion joint noise emission problems near highways.

A human visual attention analysis model for remote interaction interface of unmanned agricultural vehicles

When unmanned agricultural vehicles (UAVs) encounter unexpected failures or incidents during autonomous operations, a highly efficient remote human–machine interaction (HMI) interface is needed to assist in the manual joint control process. The highly complex cognitive mechanisms and visual characteristics of humans make it difficult to design efficient human–machine interfaces. Therefore, a human visual attention analysis model was proposed based on fully convolutional networks for the remote interaction interface of unmanned agricultural vehicles. First, visual attention experimental software combined with gaze-contingent real-time simulation methods was developed to build the dataset. Subsequently, the human visual attention analysis model (HVAAM) is constructed, and the corresponding training strategy is proposed, which is trained on the ILSVRC2012 standard and self-constructed datasets. The accuracy of the HVAAM analysis on the test dataset was validated. Ultimately, a human–machine interaction test of random failure warning for remote monitoring interface of unmanned plowing operation is performed with a self-developed unmanned electric tractor as the carrier. In the test dataset, the average analysis accuracy of HVAAM was 79.2 %, and the proposed training strategy led to a 20.7 % improvement in the model accuracy. In the unmanned electric tractor human–machine interaction test, HVAAM achieved 77.9 % accuracy in the visual attention analysis of the monitoring interface. This study can effectively facilitate the analysis, design, and optimization of remote monitoring interfaces for unmanned agricultural vehicles.

Axial compression stress-strain relationship of lithium slag rubber concrete

Replacing cement with lithium slag and fine aggregate with rubber in concrete solves waste disposal, reduces material consumption, boosts sustainability, and enhances concrete performance. A set of prismatic concrete specimens with varying proportions were designed and experimentally tested in order to study the compressive stress-strain behavior of lithium slag rubber concrete (LSRC). The main factors affecting the specimens were lithium slag substitution ratio (SL=0%, 10%, 20%, 30%) and rubber substitution ratio (SR=0%, 5%, 10%, 15%). The results demonstrated that the LSRC exhibited good integrity during the damage. Furthermore, the incorporation of lithium slag (LS) was found to effectively compensate for the reduction in compressive strength due to the incorporation of rubber. When 10% of the fine aggregate was replaced with rubber and 20% of the cement was substituted with lithium slag, the axial compressive strength, elastic modulus, and peak strain of the tested specimens increased by 21.57%, 6.92%, and 17.26%, respectively. Compared with ordinary concrete, LSRC has good toughness, impact resistance and durability with minimal loss of strength, and has broad application prospects in engineering fields (such as airports, highways, housing expansion joints, concrete floors and railway concrete sleepers, etc.). Based on the experimental data, simplified modified equations to predict the compressive strength, elastic modulus, peak strain and axial stress-strain constitutive model of LSRC were proposed, so as to promote the development of LSRC.

Observation-based quantification of aerosol transport using optical flow: A satellite perspective to characterize interregional transport of atmospheric pollution

Interregional transport plays a significant role in haze formation with varying and disputable contribution extent. Current research on quantitatively analyzing interregional atmospheric pollution transport has mainly relied on meteorological and chemical models. However, these models are typically affected by uncertainties due to the assumptions and simplifications inherent in the numerical simulations and source emission estimations. In this study, a comprehensive optical flow framework is developed to offer a new perspective on quantitative characterization of interregional transport of atmospheric pollution based on synergistic observations from geostationary and sun-synchronous satellites. In this framework, the high-frequency continuous aerosol observing images are regarded as video in computer vision, and an aerosol dynamic optical flow algorithm is proposed by incorporating aerosol-specific assumptions and constraints, overcoming the limitation that traditional optical flow methods are typically confined to rigid bodies. Results demonstrate that the developed optical flow framework could distinguish the aerosol transport process from other dynamic processes of aerosol development and accurately capture the fast-changing details of transport processes. Moreover, the satellite-based optical flow framework achieves aerosol transport results comparable to those of widely accepted model-based methods, demonstrating the physical interpretation of pixel-based optical flow results and highlighting its effectiveness in quantitative characterization of the atmospheric pollution transport process via the Aerosol Transport Index (ATI). Furthermore, a case analysis of long-term assessments of interregional transport of atmospheric pollution indicates that Beijing acts as a “sink” of atmospheric pollution, and a downward trend could be found from the annually averaged transported aerosol net loadings due to the emission reduction policy. Compared with model-based methods, the satellite-based optical flow framework is directly grounded in observations and does not rely on emission inventories that take years to update. Therefore, it not only helps improve understanding the patterns of atmospheric pollution interregional transport, but also provides a more efficient and economical way to assess the effectiveness of regional joint control policy.