Wenkang Xu

Bio: Wenkang Xu is an academic researcher from Nanjing University of Science and Technology. The author has contributed to research in topics: Iterative learning control & Impedance control. The author has an hindex of 5, co-authored 9 publications receiving 80 citations.

Neural-network-based robot time-varying force control with uncertain manipulator–environment system

Abstract: This paper considers the problem of time-varying force control for robot manipulators in the presence of uncertainties from both the robotic model and working environment. The position-based impeda...

Time-varying force tracking in impedance control

Abstract: Compared with the general compliance control problem where the manipulator-environment interaction force is often assumed to be a fixed value, the time-varying interaction force within position-based impedance control is studied on a 2-joint robot manipulator. Exploration of theoretical analysis and tentative improvements on time-varying force control are proposed with the improvements of traditional target impedance model. An adaptive control algorithm is additionally introduced to identify the uncertain location and stiffness of the environment, and the Lyapunov-based stability analysis is also given. Finally, Simulations are performed to verify the efficacy of the newly proposed methods in both trajectory tracking and force control.

Robotic Time-varying Force Tracking in Position-based Impedance Control

Abstract: This paper presents a unified control framework for both set-point and time-varying force control of robot manipulator by introducing an improved position-based impedance control (IPBIC). In order to essentially achieve accurate force control, especially time-varying force tracking, a new target impedance function compensated by a force controller is presented. The essence of the improved method in realizing time-varying force tracking, as well as the coupled stability of the manipulator–environment system is investigated. To further improve the force control performance, the Newton-type iterative learning control (ILC) is introduced upon the closed-loop system. A case study on a two-link robot model demonstrates the effectiveness of this method.

Cascade based iterative learning control of robotic-assisted upper extremity stroke rehabilitation

Abstract: This paper develops a combined cascade and iterative learning control based scheme for regulating the assistive stimulation applied to the human muscle in robotic-assisted upper-limb stroke rehabilitation. Guided by a robot the patient makes repeated attempts at a finite duration task with assistive stimulation applied to the relevant muscles. Once each attempt is complete, the arm is reset to the starting location and an iterative learning control algorithm is used to compute the stimulation to be applied on the next attempt, where if the patient is improving with each attempt the level of assistive stimulation required should decrease and the voluntary effort increase. This property has been observed in clinical trials where a critical problem is the response of the muscles to electrical stimulation and, in particular, fatigue. The new results in this paper relate to the addition of a cascade controller in an inner feedback loop around the muscle model to counter the onset of fatigue. Results from a simulation based assessment of the final design using patient data are given, where such a study is a prerequisite for obtaining ethical approval to conduct a clinical trial.

Active Impedance Control of Bioinspired Motion Robotic Manipulators: An Overview

Abstract: There are two main categories of force control schemes: hybrid position-force control and impedance control. However, the former does not take into account the dynamic interaction between the robot's end effector and the environment. In contrast, impedance control includes regulation and stabilization of robot motion by creating a mathematical relationship between the interaction forces and the reference trajectories. It involves an energetic pair of a flow and an effort, instead of controlling a single position or a force. A mass-spring-damper impedance filter is generally used for safe interaction purposes. Tuning the parameters of the impedance filter is important and, if an unsuitable strategy is used, this can lead to unstable contact. Humans, however, have exceptionally effective control systems with advanced biological actuators. An individual can manipulate muscle stiffness to comply with the interaction forces. Accordingly, the parameters of the impedance filter should be time varying rather than value constant in order to match human behavior during interaction tasks. Therefore, this paper presents an overview of impedance control strategies including standard and extended control schemes. Standard controllers cover impedance and admittance architectures. Extended control schemes include admittance control with force tracking, variable impedance control, and impedance control of flexible joints. The categories of impedance control and their features and limitations are well introduced. Attention is paid to variable impedance control while considering the possible control schemes, the performance, stability, and the integration of constant compliant elements with the host robot.

HyPlag: A Hybrid Approach to Academic Plagiarism Detection

Abstract: Current plagiarism detection systems reliably find instances of copied and moderately altered text, but often fail to detect strong paraphrases, translations, and the reuse of non-textual content and ideas. To improve upon the detection capabilities for such concealed content reuse in academic publications, we make four contributions: i) We present the first plagiarism detection approach that combines the analysis of mathematical expressions, images, citations and text. ii) We describe the implementation of this hybrid detection approach in the research prototype HyPlag. iii) We present novel visualization and interaction concepts to aid users in reviewing content similarities identified by the hybrid detection approach. iv) We demonstrate the usefulness of the hybrid detection and result visualization approaches by using HyPlag to analyze a confirmed case of content reuse present in a retracted research publication.