Mechanical Engineering - Research Publications

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    Multi-agent gradient climbing via extremum seeking control
    Kong, SZ ; Manzie, CG ; Tan, Y ; Nesic, D (IFAC - International Federation of Automatic Control, 2014)
    A unified framework based on discrete-time gradient-based extremum seeking control is proposed to localise an extremum of an unknown scalar field distribution using a group of equipped with sensors. The controller utilises estimates of gradients of the field from local dithering sensor measurements collected by the mobile agents. It is assumed that distributed coordination which ensures uniform asymptotic stability with respect to a prescribed formation of the agents is employed. The framework is useful in that a broad range of nonlinear programming algorithms can be combined with a wide class of cooperative control laws to perform extreme source seeking. Semi-global practical asymptotically stable convergence to local extrema is established in the presence of bounded field sampling noise.
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    PDE Battery Model Simplification for Charging Strategy Evaluation
    Zou, C ; MANZIE, C ; Nesic, D ; Che Soh, A ; Selamat, H ; Rahman, RZA ; Ishak, AJ ; Ahmad, SA ; Ramli, HRH ; Faudzi, A (IEEE Press, 2015)
    A safe, fast charging strategy is desired in the utilisation of rechargeable Lithium-ion batteries. Traditionally, experimental methods are used in exploring and evaluating new strategies, but these require extensive time and cost. This paper aims to establish a model-based system for quick and accurate evaluation of charging strategies. Starting from a nonlinear coupled partial differential equation (PDE) battery model that accurately captures system dynamics, simplification techniques are conducted based on the identification of separable time scales within the states. By pertinent use of a singular perturbation approach, a PDE model simplification framework containing families of simplified battery models is established. All assumptions are explicitly stated and shown to enable families of simplified models to be rigorously justified. An evaluation procedure synthesised from the simplified models and averaging theory is proposed. This procedure is implemented on several typical battery charging strategies. The benefits relative to simulation on other higher order models are assessed in terms of computational efficiency and accuracy and demonstrate significant computational savings are possible with the proposed approach.
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    PDE Battery Model Simplification for SOC and SOH Estimator Design
    Zou, C ; Kallapur, AG ; MANZIE, C ; Nesic, D (IEEE, 2015)
    Accurate knowledge of the battery state-of-charge (SOC) and state-of-health (SOH) is critical for optimal and safe utilisation of the battery. Although the battery system dynamics contain electrochemical, thermal, electrical, and ageing phenomena, most state estimators resort to equivalent circuit models (ECM). These models are often not accurate and are problematic for SOC estimation during an extended range of operations and do not address SOH dynamics. In this paper, starting from an initial high-fidelity Lithium-ion (Li-ion) battery model consisting of a set of partial differential equations (PDE), a recently proposed framework for PDE battery model simplification is employed and one of these obtained models is used for battery state estimation. Model order reduction techniques are then constructively applied to the simplified PDE battery model and resulted in a computationally efficient ordinary differential equation (ODE) model. Based on this obtained ODE model, an extended Kalman filter (EKF) is designed for the estimation of both SOC and SOH. Simulations over 20 cycles show the designed estimator is capable of simultaneously estimating the battery's SOC in each electrode and SOH.
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    Hybrid Extremum Seeking for Black-Box Optimization in Hybrid Plants: An Analytical Framework
    Poveda, JI ; Kutadinata, R ; Manzie, C ; Nesic, D ; Teel, AR ; Liao, C-K (IEEE, 2018-01-01)
    This paper presents an analytical framework to design and analyze hybrid extremum seeking controllers for plants with hybrid dynamics. The extremum seeking controllers are characterized by a hybrid dither generator, a hybrid Jacobian estimator, and a hybrid dynamic optimizer. This structure allows us to consider a family of novel extremum seeking controllers that have not been studied in the literature before. Moreover, the hybrid extremum seeking controllers can be applied to plants with hybrid dynamics generating well-defined response maps. A convergence result is established for the closed -loop system by using singular perturbation theory for hybrid dynamical systems with hybrid boundary layers.