Mechanical Engineering - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 10 of 16
  • Item
    Thumbnail Image
    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)
  • Item
    No Preview Available
    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)
  • Item
    No Preview Available
    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.
  • Item
    Thumbnail Image
    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.
  • Item
    Thumbnail Image
    Varying Joint Patterns and Compensatory Strategies Can Lead to the Same Functional Gait Outcomes: A Case Study
    Bacek, T ; SUN, M ; LIU, H ; Chen, Z ; Kulic, D ; Oetomo, D ; Tan, Y (IEEE, 2022)
    This paper analyses joint-space walking mechanisms and redundancies in delivering functional gait outcomes. Multiple biomechanical measures are analysed for two healthy male adults who participated in a multi-factorial study and walked during three sessions. Both participants employed varying intra- and inter-personal compensatory strategies (e.g., vaulting, hip hiking) across walking conditions and exhibited notable gait pattern alterations while keeping task-space (functional) gait parameters invariant. They also preferred various levels of asymmetric step length but kept their symmetric step time consistent and cadence-invariant during free walking. The results demonstrate the importance of an individualised approach and the need for a paradigm shift from functional (task-space) to joint-space gait analysis in attending to (a)typical gaits and delivering human-centred human-robot interaction.
  • Item
    Thumbnail Image
    On a Shubert Algorithm-Based Global Extremum Seeking Scheme
    Nesic, D ; Nguyen, T ; Tan, Y ; Manzie, C (IEEE, 2012)
    This paper adapts the so-called Shubert algorithm for Extremum Seeking Control (ESC) to seek the global extremum (in presence of local extrema) of general dynamic plants. Different from derivative based methods that are widely used in ESC, the Shubert algorithm is a good representative of sampling optimization methods. With knowledge of the Lipschitz constant of an unknown static mapping, this deterministic algorithm seeks the global extremum. By introducing “waiting time” the proposed Shubert algorithm-based global extremum seeking guarantees the semi-global practical convergence (in the initial states) to the global extremum if compact sets of inputs are considered. Several numerical examples demonstrate how proposed method may be successfully deployed.
  • Item
    Thumbnail Image
    Open Problems in Reset Control
    Zhao, G ; Nesic, D ; Tan, Y ; Wang, J (IEEE, 2013-01-01)
    It is well-known that there are fundamental performance limitations in the design of linear feedback control systems for single-input-single-output (SISO) linear-time-invariant (LTI) plants. These performance limitations sometimes include overshoot and rise time. This paper shows that for some examples of SISO LTI systems, it is possible to find suitable reset controllers that can overcome such performance limitations, though there are still some robust and implementable issues that need to be solved. This naturally leads to the formulation of several open research problems that we specify.
  • Item
    Thumbnail Image
    Unified frameworks for sampled-data extremum seeking control: Global optimisation and multi-unit systems
    Khong, SZ ; Nesic, D ; Tan, Y ; Manzie, C (PERGAMON-ELSEVIER SCIENCE LTD, 2013-09)
    Two frameworks are proposed for extremum seeking of general nonlinear plants based on a sampled-data control law, within which a broad class of nonlinear programming methods is accommodated. It is established that under some generic assumptions, semi-global practical convergence to a global extremum can be achieved. In the case where the extremum seeking algorithm satisfies a stronger asymptotic stability property, the converging sequence is also shown to be stable using a trajectory-based proof, as opposed to a Lyapunov-function- type approach. The former is more straightforward and insightful. This allows for more general optimisation algorithms than considered in existing literature, such as those which do not admit a state-update realisation and/or Lyapunov functions. Lying at the heart of the analysis throughout is robustness of the optimisation algorithms to additive perturbations of the objective function. Multi-unit extremum seeking is also investigated with the objective of accelerating the speed of convergence.
  • Item
    Thumbnail Image
    Multidimensional global extremum seeking via the DIRECT optimisation algorithm
    Khong, SZ ; Nesic, D ; Manzie, C ; Tan, Y (PERGAMON-ELSEVIER SCIENCE LTD, 2013-07-01)
    DIRECT is a sample-based global optimisation method for Lipschitz continuous functions defined over compact multidimensional domains. This paper adapts the DIRECT method with a modified termination criterion for global extremum seeking control of multivariable dynamical plants. Finite-time semi-global practical convergence is established based on a periodic sampled-data control law, whose sampling period is a parameter which determines the region and accuracy of convergence. A crucial part of the development is dedicated to a robustness analysis of the DIRECT method against bounded additive perturbations on the objective function. Extremum seeking involving multiple units is also considered within the same context as a means to increase the speed of convergence. Numerical examples of global extremum seeking based on DIRECT are presented at the end.
  • Item
    Thumbnail Image
    On non-local stability properties of extrernum seeking control
    Tan, Y ; Nesic, D ; Mareels, I (PERGAMON-ELSEVIER SCIENCE LTD, 2006-06-01)
    In this paper, we consider several extremum seeking schemes and show under appropriate conditions that these schemes achieve extremum seeking from an arbitrarily large domain of initial conditions if the parameters in the controller are appropriately adjusted. This non-local stability result is proved by showing semi-global practical stability of the closed-loop system with respect to the design parameters. We show that reducing the size of the parameters typically slows down the convergence rate of the extremum seeking controllers and enlarges the domain of the attraction. Our results provide guidelines on how to tune the controller parameters in order to achieve extremum seeking. Simulation examples illustrate our results.