Electrical and Electronic Engineering - Research Publications
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ItemNo Preview AvailableSub-Optimal Moving Horizon Estimation in Feedback Control of Linear Constrained Systems(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)
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ItemNo Preview AvailableReachability of Linear Time-Invariant Systems via Ellipsoidal Approximations(Elsevier BV, 2023-01-01)
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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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ItemNo Preview AvailableSub-Optimal MPC With Dynamic Constraint Tightening(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)
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ItemNo Preview AvailableAn algorithm for the selection of linearisation points in non-linear systems: a diesel air-path case study(TAYLOR & FRANCIS LTD, 2023-12-02)
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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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ItemZeroth-Order Optimization on Subsets of Symmetric Matrices With Application to MPC Tuning(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2021-11-08)This article provides a zeroth-order optimization framework for nonsmooth and possibly nonconvex cost functions with matrix parameters that are real and symmetric. We provide complexity bounds on the number of iterations required to ensure a given accuracy level for both the convex and nonconvex cases. The derived complexity bounds for the convex case are less conservative than available bounds in the literature since we exploit the symmetric structure of the underlying matrix space. Moreover, the nonconvex complexity bounds are novel for the class of optimization problems that we consider. The utility of the framework is evident in the suite of applications that use symmetric matrices as tuning parameters. Of primary interest here is the challenge of tuning the gain matrices in model predictive controllers, as this is a challenge known to be inhibiting the industrial implementation of these architectures. To demonstrate the framework, we consider the problem of MIMO diesel air-path control and implement the framework iteratively ``in-the-loop'' to reduce tracking error on the output channels. Both simulations and experimental results are included to illustrate the effectiveness of the proposed framework over different engine drive cycles.
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ItemNo Preview Available