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This paper aims to design an event-triggered adaptive prescribed performance controller for flexible manipulators, with the primary objectives of achieving output performance constraints and addressing communication resource limitations.

The authors propose a novel prescribed performance barrier Lyapunov function (PP-BLF) that considers both output and tracking performance constraints. The PP-BLF ensures that the system's output, transient behavior and steady-state performance, adhere to prescribed constraints. The boundary of the PP-BLF is established by an exponential function that decays over time. Notably, the PP-BLF can be applied seamlessly in unconstrained cases without necessitating controller redesign. Moreover, the controller design incorporates an event-triggered mechanism, effectively reducing the frequency of controller updates and optimizing the utilization of communication resources. Additionally, the authors employ adaptive techniques to estimate the system's unknown parameters and approximate unknown nonlinear functions using radial basis function neural networks (RBFNN). To address the challenge of “complexity explosion”, dynamic surface technology is employed.

Numerical simulations are conducted under five different cases to verify the effectiveness of the proposed controller. The results demonstrate that the controller successfully constrains the output tracking error within the prescribed performance boundary. Moreover, compared with the traditional time-triggered mechanism, the event-triggered mechanism significantly reduces the controller's update frequency, resolving the problem of limited communication resources.

The paper reduces the update frequency of control signals and improves resource utilization through an event-triggered mechanism in the form of relative thresholds. The authors recognize that the event-triggered mechanism may impact the output performance of the system. To address this challenge, the authors propose a prescribed performance Barrier Lyapunov Function (PP-BLF). The PP-BLF is designed to effectively constrain the output performance of the system, ensuring satisfactory control even when the control signal updates are reduced.

The study aims to equip robots with the ability to precisely maintain interaction forces, which is crucial for tasks such as polishing in highly dynamic environments with unknown and varying stiffness and geometry, including those found in airplane wings or thin, soft materials. The purpose of this study is to develop a novel adaptive force-tracking admittance control scheme aimed at achieving a faster response rate with higher tracking accuracy for robot force control.

In the proposed method, the traditional admittance model is improved by introducing a pre-proportional-derivative controller to accelerate parameter convergence. Subsequently, the authors design an adaptive law based on fuzzy logic systems (FLS) to compensate for uncertainties in the unknown environment. Stability conditions are established for the proposed method through Lyapunov analysis, which ensures the force tracking accuracy and the stability of the coupled system consisting of the robot and the interaction environment. Furthermore, the effectiveness and robustness of the proposed control algorithm are demonstrated by simulation and experiment.

A variety of unstructured simulations and experimental scenarios are designed to validate the effectiveness of the proposed algorithm in force control. The outcomes demonstrate that this control strategy excels in providing fast response, precise tracking accuracy and robust performance.

In real-world applications spanning industrial, service and medical fields where accurate force control by robots is essential, the proposed method stands out as both practical and straightforward, delivering consistently satisfactory performance across various scenarios.

This research introduces a novel adaptive force-tracking admittance controller based on FLS and validated through both simulations and experiments. The proposed controller demonstrates exceptional performance in force control within environments characterized by unknown and varying.

This paper aims to explore the possibility of converting the nitrile butadiene rubber (NBR) water-lubricated bearing material into a self-lubricating bearing material by the action of polytetrafluoroethylene (PTFE) particles and water lubrication.

A group of experimental studies was carried out on a ring-on-block friction test. The physical properties, tribological properties and interface structure of PTFE-NBR self-lubricating composites filled with different percentages of PTFE particles were investigated.

The experimental results indicated that the reduction in friction and wear is a result of the formation of the lubricating film on the surface of the composites. The lubricating film was formed of a large amount of PTFE particles continuously supplied under water lubrication conditions and the PTFE particles here can greatly enhance the load capacity and lubrication performance.

In this study, the tribological properties of PTFE particles added to the NBR water-lubricated bearing materials under water lubrication were investigated experimentally, and the research was carried out by a ring-on-block friction test. It is believed that this study can provide some guidance for the application of PTFE-NBR self-lubricating.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2020-0187/

The purpose of this study is to describe and observe the effect of surface topography associated with arbitrary directions of rolling and sliding velocities on the performance of lubricating films in elliptical contacts.

The most recently published mixed elastohydrodynamic (EHL) model by Pu and Zhu is used. Three different machined rough surfaces are discussed and the correlated inclined angle of surface velocity varies from 0° to 90° in the analyzed cases. These cases are carried out in a wide range of speeds (five orders of magnitude) while the simulated lubrication condition covers full-film and mixed EHL down to the boundary lubrication.

The results indicate that the variation of the average film thickness corresponding to different entrainment angles is distinct from those without considering surface roughness. In addition, the surface topography appears to have an immense effect on the lubrication film thickness in the exceptive situation.

This paper has not been published previously. Surface roughness has attracted much attention for many years owing to the significant influence on lubricating property. However, previous studies mainly focus on the counterformal contact with the same direction between surface velocity and principal axis of the contact zone. Little attention has been paid to the specific condition with the arbitrary direction of rolling and sliding velocities found in hypoid gears and worm, and some other components. The purpose of this study is to describe and observe the effect of surface topography associated with arbitrary directions of rolling and sliding velocities on the performance of lubricating films in elliptical contacts based on the most recently published mixed EHL model by Pu and Zhu.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.