Electrical and Electronic Engineering - Research Publications
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ItemNo Preview AvailableTRACKING AND REGRET BOUNDS FOR ONLINE ZEROTH-ORDER EUCLIDEAN AND RIEMANNIAN OPTIMIZATION(SIAM PUBLICATIONS, 2022)
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ItemOnline optimization of spark advance in alternative fueled engines using extremum seeking control(Elsevier, 2014-08-01)Alternative fueled engines offer greater challenges for engine control courtesy of uncertain fuel composition. This makes optimal tuning of input parameters like spark advance extremely difficult in most existing ECU architectures. This paper proposes the use of grey-box extremum seeking techniques to provide real-time optimization of the spark advance in alternative fueled engines. Since practical implementation of grey-box extremum seeking methods is typically done using digital technology, this paper takes advantage of emulation design methods to port the existing continuous-time grey-box extremum seeking methods to discrete-time frameworks. The ability and flexibility of the proposed discrete-time framework is demonstrated through simulations and in practical situation using a natural gas fueled engine.
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ItemMulti-agent source seeking via discrete-time extremum seeking control(PERGAMON-ELSEVIER SCIENCE LTD, 2014-09)Recent developments in extremum seeking theory have established a general framework for the methodology, although the specific implementations, particularly in the context of multi-agent systems, have not been demonstrated. In this work, a group of sensor-enabled vehicles is used in the context of the extremum seeking problem using both local and global optimisation algorithms to locate the extremum of an unknown scalar field distribution. For the former, the extremum seeker exploits estimates of gradients of the field from local dithering sensor measurements collected by the mobile agents. It is assumed that a distributed coordination which ensures uniform asymptotic stability with respect to a prescribed formation of the agents is employed. An inherent advantage of the frameworks is 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 field sampling noise. Subsequently, global extremum seeking with multiple agents is investigated and shown to give rise to robust practical convergence whose speed can be improved via computational parallelism. Nonconvex field distributions with local extrema can be accommodated within this global framework.
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ItemExtremum seeking of dynamical systems via gradient descent and stochastic approximation methods(Elsevier, 2015-06)Abstract This paper examines the use of gradient based methods for extremum seeking control of possibly infinite-dimensional dynamic nonlinear systems with general attractors within a periodic sampled-data framework. First, discrete-time gradient descent method is considered and semi-global practical asymptotic stability with respect to an ultimate bound is shown. Next, under the more complicated setting where the sampled measurements of the plant’s output are corrupted by an additive noise, three basic stochastic approximation methods are analysed; namely finite-difference, random directions, and simultaneous perturbation. Semi-global convergence to an optimum with probability one is established. A tuning parameter within the sampled-data framework is the period of the synchronised sampler and hold device, which is also the waiting time during which the system dynamics settle to within a controllable neighbourhood of the steady-state input–output behaviour.
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ItemMulti-time-scale observer design for state-of-charge and state-of-health of a lithium-ion battery(ELSEVIER SCIENCE BV, 2016-12-15)The accurate online state estimation for some types of nonlinear singularly perturbed systems is challenging due to extensive computational requirements, ill-conditioned gains and/or convergence issues. This paper proposes a multi-time-scale estimation algorithm for a class of nonlinear systems with coupled fast and slow dynamics. Based on a boundary-layer model and a reduced model, a multi-time-scale estimator is proposed in which the design parameter sets can be tuned in different time-scales. Stability property of the estimation errors is analytically characterized by adopting a deterministic version of extended Kalman filter (EKF). This proposed algorithm is applied to estimator design for the state-of-charge (SOC) and state-of-health (SOH) in a lithium-ion battery using the developed reduced order battery models. Simulation results on a high fidelity lithium-ion battery model demonstrate that the observer is effective in estimating SOC and SOH despite a range of common errors due to model order reductions, linearisation, initialisation and noisy measurement.
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ItemModel Predictive Control for Lithium-Ion Battery Optimal Charging(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018-04)Charging time and lifetime are important performances for lithium-ion (Li-ion) batteries, but are often competing objectives for charging operations. Model-based charging controls are challenging due to the complicated battery system structure that is composed of nonlinear partial differential equations and exhibits multiple time-scales. This paper proposes a new methodology for battery charging control enabling an optimal tradeoff between the charging time and battery state-of-health (SOH). Using recently developed model reduction approaches, a physics-based low-order battery model is first proposed and used to formulate a model-based charging strategy. The optimal fast charging problem is formulated in the framework of tracking model predictive control (MPC). This directly considers the tracking performance for provided state-of-charge and SOH references, and explicitly addresses constraints imposed on input current and battery internal state. The capability of this proposed charging strategy is demonstrated via simulations to be effective in tracking the desirable SOH trajectories. By comparing with the constant-current constant-voltage charging protocol, the MPC-based charging appears promising in terms of both the charging time and SOH. In addition, this obtained charging strategy is practical for real-time implementation.
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ItemAdaptive Scan for Atomic Force Microscopy Based on Online Optimization: Theory and Experiment(Institute of Electrical and Electronics Engineers, 2020-05-01)A major challenge in atomic force microscopy is to reduce the scan duration while retaining the image quality. Conventionally, the scan rate is restricted to a sufficiently small value in order to ensure a desirable image quality as well as a safe tip-sample contact force. This usually results in a conservative scan rate for samples that have a large variation in aspect ratio and/or for scan patterns that have a varying linear velocity. In this paper, an adaptive scan scheme is proposed to alleviate this problem. A scan line-based performance metric balancing both imaging speed and accuracy is proposed, and the scan rate is adapted such that the metric is optimized online in the presence of aspect ratio and/or linear velocity variations. The online optimization is achieved using an extremum-seeking approach, and a semiglobal practical asymptotic stability result is shown for the overall system. Finally, the proposed scheme is demonstrated via both simulation and experiment.
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ItemPractical exponential stability and closeness of solutions for singularly perturbed systems via averaging(PERGAMON-ELSEVIER SCIENCE LTD, 2021-04)This paper studies the behavior of singularly perturbed nonlinear differential equations with boundary-layer solutions that do not necessarily converge to an equilibrium. Using the average for the derivative of the slow state variables and assuming the boundary-layer solutions converge exponentially fast to a bounded set, which is possibly parameterized by the slow variable, results on the closeness of solutions of the singularly perturbed system to the solutions of the reduced average and boundary-layer systems over a finite time interval are presented. The closeness of solution error is shown to be of order O(ε) where ε is the perturbation parameter. Moreover, under the additional assumption of exponential stability of the reduced average system, practical exponential stability of the solutions of the singularly perturbed system is provided.
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ItemScan Rate Adaptation for AFM Imaging Based on Performance Metric Optimization(Institute of Electrical and Electronics Engineers (IEEE), 2020-02)Constant-force contact-mode atomic force microscopy (AFM) relies on a feedback control system to regulate the tip–sample interaction during imaging. Due to limitations in actuators and control, the bandwidth of the regulation system is typically small. Therefore, the scan rate is usually limited in order to guarantee a desirable image quality for a constant-rate scan. By adapting the scan rate online, further performance improvement is possible, and the conditions to this improvement have been explored qualitatively in a previous study for a wide class of possible scan patterns. In this article, a quantitative assessment of the previously proposed adaptive scan scheme is investigated through experiments that explore the impact of various degrees of freedom in the algorithm. Further modifications to the existing scheme are proposed and shown to improve the closed-loop performance. The flexibility of the proposed approach is further demonstrated by applying the algorithm to tapping-mode AFM.
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ItemA Framework for Simplification of PDE-Based Lithium-Ion Battery Models(Institute of Electrical and Electronics Engineers (IEEE), 2016)Simplified models are commonly used in battery management and control, despite their (often implicit) limitations in capturing the dynamic behavior of the battery across a wide range of operating conditions. This paper seeks to develop a framework for battery model simplification starting from an initial high-order physics-based model that will explicitly detail the assumptions underpinning the development of simplified battery models. Starting from the basis of a model capturing the electrochemical, thermal, electrical, and aging dynamics in a set of partial differential equations, a systematic approach based on singular perturbations and averaging is used to simplify the dynamics through identification of disparate timescales inherent in the problem. As a result, libraries of simplified models with interconnections based on the specified assumptions are obtained. A quantitative comparison of the simplified models relative to the original model is used to justify the model reductions. To demonstrate the utility of the framework, a set of battery charging strategies is evaluated at reduced computational effort on simplified models.