Mechanical Engineering - Research Publications

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    A Geometry-Based Distributed Connectivity Maintenance Algorithm for Discrete-time Multi-Agent Systems with Visual Sensing Constraints
    Li, X ; Fu, J ; Liu, M ; Xu, Y ; Tan, Y ; Xin, Y ; Pu, Y ; Oetomo, D (WORLD SCIENTIFIC PUBL CO PTE LTD, 2024-03-01)
    This paper presents a novel approach to address the challenge of maintaining connectivity within a multi-agent system (MAS) when utilizing directional visual sensors. These sensors have become essential tools for enhancing communication and connectivity in MAS, but their geometric constraints pose unique challenges when designing controllers. Our approach, grounded in geometric principles, leverages a mathematical model of directional visual sensors and employs a gradient-descent optimization method to determine the position and orientation constraints for each sensor based on its geometric configuration. This methodology ensures network connectivity, provided that initial geometric constraints are met. Experimental results validate the efficacy of our approach, highlighting its practical applicability for a range of tasks within MAS.
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    Robust Admittance Control With Complementary Passivity
    Xu, J ; Chen, X ; Tan, Y ; Zou, W (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)
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    Tri-Space Operational Control of Redundant Multilink and Hybrid Cable-Driven Parallel Robots Using an Iterative-Learning-Based Reactive Approach
    Bhattacharya, D ; Chan, YP ; Shang, S ; Chan, YS ; Tan, Y ; Lau, D (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023-11)
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    On Active Disturbance Rejection Control for Unmanned Tracked Ground Vehicles with Nonsmooth Disturbances
    Liu, M ; Xu, Y ; Lin, X ; Tan, Y ; Pu, Y ; Li, W ; Oetomo, D (WORLD SCIENTIFIC PUBL CO PTE LTD, 2023-01-01)
    This paper proposes robust controllers for a class of unmanned tracked ground vehicles (UTGVs), which are built to autonomously clean carryback or spillage from the conveyor belts used in the mining industry. The UTGV, a nonholonomic system in its nature, needs to follow a given path in a harsh environment with large uncertainties due to the time-varying mass and inertia when the UTGV loads and unloads as well as unknown frictions and flatness of the ground. Moreover, the input constraints coming from motors do exist. It is usually hard to design robust controllers for such complex systems. By utilizing the available autonomous driving system, which is designed to be compatible with the existing remote motion controller in unmanned systems to generate autonomous ability, this paper uses the off-the-shelf motion planner to calculate desired linear and angular velocities based on the given path and sensor perceptions. Consequently, the control design can be simplified as two decoupled linear time-invariant scalar dynamic systems with uncertainties, making the active disturbance rejection controller (ADRC) applicable. By carefully designing the parameters of ADRC with the help of an extended state observer (ESO), it is shown that the proposed ADRC and ESO can achieve good tracking performance in the presence of input saturation and can handle nonsmooth disturbances. The proposed simulation results and experimental results support the theoretical findings.
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    Input-mapping based data-driven model predictive control for unknown linear systems via online learning
    Yang, L ; Li, D ; Ma, A ; Xi, Y ; Pu, Y ; Tan, Y (WILEY, 2022-01-01)
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    Frequency set selection for multi-frequency steady-state visual evoked potential-based brain-computer interfaces
    Mu, J ; Grayden, DBB ; Tan, Y ; Oetomo, D (FRONTIERS MEDIA SA, 2022-12-21)
    OBJECTIVE: Multi-frequency steady-state visual evoked potential (SSVEP) stimulation and decoding methods enable the representation of a large number of visual targets in brain-computer interfaces (BCIs). However, unlike traditional single-frequency SSVEP, multi-frequency SSVEP is not yet widely used. One of the key reasons is that the redundancy in the input options requires an additional selection process to define an effective set of frequencies for the interface. This study investigates systematic frequency set selection methods. METHODS: An optimization strategy based on the analysis of the frequency components in the resulting multi-frequency SSVEP is proposed, investigated and compared to existing methods, which are constructed based on the analysis of the stimulation (input) signals. We hypothesized that minimizing the occurrence of common sums in the multi-frequency SSVEP improves the performance of the interface, and that selection by pairs further increases the accuracy compared to selection by frequencies. An experiment with 12 participants was conducted to validate the hypotheses. RESULTS: Our results demonstrated a statistically significant improvement in decoding accuracy with the proposed optimization strategy based on multi-frequency SSVEP features compared to conventional techniques. Both hypotheses were validated by the experiments. CONCLUSION: Performing selection by pairs and minimizing the number of common sums in selection by pairs are effective ways to select suitable frequency sets that improve multi-frequency SSVEP-based BCI accuracies. SIGNIFICANCE: This study provides guidance on frequency set selection in multi-frequency SSVEP. The proposed method in this study shows significant improvement in BCI performance (decoding accuracy) compared to existing methods in the literature.
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    Task-Driven Formation of Nonholonomic Vehicles With Communication Constraints
    Li, X ; Tan, Y ; Tang, J ; Chen, X (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023-01)
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    A Multi-Processor Implementation for Networked Control Systems
    Maass, AI ; Wang, W ; Nesic, D ; Tan, Y ; Postoyan, R (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)
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    On state estimation for nonlinear systems under random access wireless protocols
    Maass, AI ; Nesic, D ; Postoyan, R ; Tan, Y (SPRINGER LONDON LTD, 2023-03-01)
    This article is dedicated to Eduardo D. Sontag on the occasion of his 70th birthday. We build upon fundamental stability concepts developed by Sontag, such as input-to-state stability and its related properties, to study a relevant application in industrial internet of things, namely estimation for wireless networked control systems. Particularly, we study emulation-based state estimation for nonlinear plants that communicate with a remote observer over a shared wireless network subject to packet losses. To reduce bandwidth usage, a stochastic communication protocol is employed to determine which node should be given access to the network. Each node has a different successful transmission probability. We describe the overall closed-loop system as a stochastic hybrid model, which allows us to capture the behaviour both between and at transmission instants, whilst covering network features such as random transmission instants, packet losses and stochastic scheduling. We then provide sufficient conditions on the transmission rate that guarantee an input-to-state stability property (in expectation) for the corresponding estimation error system. We illustrate our results in the design of circle criterion observers.
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    Technology-assisted assessment of spasticity: a systematic review
    Guo, X ; Wallace, R ; Tan, Y ; Oetomo, D ; Klaic, M ; Crocher, V (BMC, 2022-12-09)
    BACKGROUND: Spasticity is defined as "a motor disorder characterised by a velocity dependent increase in tonic stretch reflexes (muscle tone) with exaggerated tendon jerks". It is a highly prevalent condition following stroke and other neurological conditions. Clinical assessment of spasticity relies predominantly on manual, non-instrumented, clinical scales. Technology based solutions have been developed in the last decades to offer more specific, sensitive and accurate alternatives but no consensus exists on these different approaches. METHOD: A systematic review of literature of technology-based methods aiming at the assessment of spasticity was performed. The approaches taken in the studies were classified based on the method used as well as their outcome measures. The psychometric properties and usability of the methods and outcome measures reported were evaluated. RESULTS: 124 studies were included in the analysis. 78 different outcome measures were identified, among which seven were used in more than 10 different studies each. The different methods rely on a wide range of different equipment (from robotic systems to simple goniometers) affecting their cost and usability. Studies equivalently applied to the lower and upper limbs (48% and 52%, respectively). A majority of studies applied to a stroke population (N = 79). More than half the papers did not report thoroughly the psychometric properties of the measures. Analysis identified that only 54 studies used measures specific to spasticity. Repeatability and discriminant validity were found to be of good quality in respectively 25 and 42 studies but were most often not evaluated (N = 95 and N = 78). Clinical validity was commonly assessed only against clinical scales (N = 33). Sensitivity of the measure was assessed in only three studies. CONCLUSION: The development of a large diversity of assessment approaches appears to be done at the expense of their careful evaluation. Still, among the well validated approaches, the ones based on manual stretching and measuring a muscle activity reaction and the ones leveraging controlled stretches while isolating the stretch-reflex torque component appear as the two promising practical alternatives to clinical scales. These methods should be further evaluated, including on their sensitivity, to fully inform on their potential.