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  • [ December 14, 2018]

    Data-Driven Control of a Production System by Using Marking-Dependent Threshold Policy

    | This study is motivated by the need of developing effective data-driven control methods for production systems. Our aim is answering the following research questions: How can we control production by using partial information (markings) obtained from a production system?; How can the control parameters be determined by using the real-time data? How well does the data-driven control policy perform?; and How can the markings be selected for a given system?
    In order to analyze the performance of a production system controlled with partial information, we introduce the Marked Markov Arrival Process (MMAP) framework to model a system that generates different signals, referred as markings, based on the system status. We then propose a marking-dependent threshold policy to control the system. An analytical method that is based on a matrix analytical approach is developed to analyze a production/inventory system with MMAP information and demand arrivals and a partially observable production time process modeled as a MMAP. A mathematical programming formulation is used to determine the optimal thresholds of the control policy based on the matrix geometric model of the system. We then present a joint simulation and optimization (JSO) approach to determine the parameters of the threshold policy by using the shop-floor data collected from the system.
    We test these methods on two production systems.
    We show that using a marking-dependent control policy together with a JSO approach that determines the policy parameters works effectively as a data-driven control method for manufacturing.
  • [ December 05, 2018]

    Emulsion and foam stability: one drop and bubble at a time

    | The stability of emulsions and foams are affected by a number of physical processes. As thin liquid films surrounding bubbles and drops drain, film rupture can occur, leading to coalescence and to coarsening. A common approach to appreciating stability in these systems is to create a bulk emulsion or foam and to follow the rate of creaming (for an emulsion) or collapse and drainage (for a foam). In this lecture, an alternative approach is described whereby individual bubbles and drops are monitored as they approach a fluid/fluid interface until coalescence ensues. These measurements utilize a newly developed instrument, the Dynamic Fluid Film Interferometer (DFI) where draining film thicknesses can be measured in space and time as well as the pressure drop (Laplace pressure) across the interface. Application of the DFI to study two problems is presented: (1) coalescence of oil/water emulsions in the presence of asphaltenes and (2) antifoaming of lubricating oils.
  • [ December 03, 2018]

    Screening and Tomographic Reconstruction of Defects by Structural Guided Ultrasonic Waves

    | Detecting and quantifying damages in large structures is of growing interest in various industries. Conventional ultrasonic methods are tedious and expensive, especially for inaccessible areas. Ultrasonic structural guided wave offers an attractive alternative for the rapid inspection of defects from a remote position in a large structure. In this talk, two interesting applications of ultrasonic guide waves will be discussed: defect screening in structural features such as weld, stiffeners and bends, as well as defect characterization using guided wave tomographic approach. A numerical forward model is used to predict the scattering of guided wave through defects, and an iterative inverse model is developed to reconstruct the defect profile. The imaging algorithm allows higher order diffraction and scattering to be considered in its numerical solver, thus can provide accurate inversion results. Despite two guided wave applications, recent progress in the research of acoustic metamaterial and laser ultrasound will also be shared in the talk.
  • [ December 03, 2018]

    Airway smooth muscle cells migration and orientation on 3D surfaces: taking side

    | Airway smooth muscle cells (ASMCs) are known to migrate and assemble into helical band structures around the tubular airway wall, with the helical angle variable in states from normal to disease such as asthma. However, the mechanism underlying such morphogenesis of the ASMCs remains largely unknown.
    Using concave/convex tubular/folding substrate, we found that on the surface of the micropatterned tubular substrate, the migration and orientation of the ASMCs were closely dependent not only on the tube’s radius, but also on which side of the tube either the concave or convex side. Furthermore, we demonstrate that the migration and orientation behaviors of the ASMCS were dependent on the contractile state of the cells, primarily on the actin-myosin interaction. These behaviours were not observed with other pulmonary cell types such as FBs and EPCs.
    Our findings indicate that under in vitro culture condition the ASMCs could quickly determine the microenvironment of the tubular/folding micropatterned curved surface, and change their behaviors accordingly, which ultimately led the cells to self assemble into a morphology most fit for their survival and function. This phenomenon may have important implications to better understand the mechanisms of tissue morphogenesis of tubular organs such as the pulmonary airways in both health and diseased.
  • [ November 28, 2018]

    Control of “Valley” Properties in 2D Materials by Magnetism

    | Exploiting the “valley” degree of freedom to store and manipulate information is an emerging direction of condensed matter physics, and provides a novel paradigm for future electronics. Valley is the local extremum in the electronic band structure. Transition metal dichalcogenides (TMDC), such as MoS2, WS2 and WSe2, are semiconductor analogy of graphite with atomic layers bonded together by Van der Waals interactions. A monolayer TMDC with broken inversion symmetry possesses two degenerate valleys that can be selectively excited by circularly polarized light. Breaking the valley degeneracy allows convenient control of valley degree of freedom. This can be done by applying an external magnetic field to Zeeman split the band edge states. We demonstrate that the valley properties can be controlled by magnetism. We show that valley splitting can be enhanced by more than an order of magnitude, utilizing the interfacial exchange field from a ferromagnetic substrate. We further show that transition metal doped TMDs demonstrate ferromagnetism with their magnetization tunable by light. These approaches open up new avenue for valley control forvalleytronics applications.
  • [ November 08, 2018]

    Reconfigurable Systems for Manufacturing and Automotive Applications

    | We live in an engineered world, where mechatronics is enabling the design of smart systems in which knowledge about the system can be embedded in the system itself. The design of such smart systems requires new engineering design methods, such as reconfiguration, co-design and component swapping modularity, which are introduced here in the context of applications in manufacturing and automotive systems. Reconfigurable manufacturing systems (RMS) provide exactly the manufacturing functionality and capacity needed, exactly when needed. Examples are presented to highlight the role that dynamics and control plays in designing systems to be more reconfigurable. These examples include optimal capacity management in an RMS, dynamics of a reconfigurable machine tool, and a reconfigurable stamping control system. Methods for combined design, or co-design, of an artifact and its controller and for component swapping modularity in controller design, are also presented with applications to active suspension design, and controller design for a plug-in hybrid electric vehicle, respectively.
  • [ November 06, 2018]

    Computational Intelligence in Smart Power Grid Management and Energy Feasibility Studies

    | Today, big data is a significant matter! This seminar will discuss research in predictive modelling with artificial intelligence. It will describe briefly big data principles, with less technical detail but a greater focus on applications and result. In application space it will provide case studies in recent papers demonstrating the merits of advanced data analytic models in real-life, particularly in energy management systems. Models considered will include, but not limited to, deep learning, extreme learning machines(极限学习机器), artificial neural network(人工神经网络), support vector machines(支持向量机器), multivariate adaptive regression spline (多元自适应回归样条)and M5 Tree, whereas model optimisation tools will include the results obtained by applying meta-heuristic feature selection (元启发式特征选择)(or ‘search’) algorithms, feature weight optimisation (or ‘add-in’) algorithms and multi-resolution tools such as empirical mode decomposition applied to model data to improve the prediction. In particular, feature selections are required to screen optimal inputs, improve the accuracy and reduce the computational burden, whereas add-in algorithms can help extract most, if not all of the predictive features from a large pool of carefully screened input variables. Empirical mode decompositions, can assist in identifying the frequency components in model inputs and addressing issues of non-stationarity, trends, jumps and periodicities present in model design data. This seminar will reveal the importance of ancillary tools in predictive modelling with applications of artificial intelligence models in energy demand management and solar energy simulations. The seminar will discuss and expect to exchange ideas and future challenges that we as, researchers, face in predictive modelling that must be considered in practical energy management models that are used in real-life simulations to design decision systems for energy management with big data analytics.
  • [ October 24, 2018]

    Defects on carbon for electrocatalysis

    | Electrocatalysis is the key for energy conversion and storage devices such as fuel cells, metal-air batteries and water splitting. The development of highly efficient and non-precious metal catalyst is extremely important. Recently, we presented a new concept of defect electrocatalysis, in which the topological defects on carbons or in oxides/compounds are the active sites for electrochemical reactions. A series of non-metal catalysts have been developed based on this new theory. Besides, the defects are such characterized points with higher energy, thus provides ideal sites to interact with non-/metal species in various sizes. The strong interactions may provide both high reactivity and stability. When the size of metal species reduces to atomic level, the general configurations are metal atoms trapped into defects according to the minimum energy theory. The coordination of the defect and atomic species plays the central role for electrocatalysis as the local electronic structures defined by this coordination determines the interaction of reactant and active sites.
  • [ October 17, 2018]

    Fluid mechanics for functional materials

    | Additive manufacturing, commonly known as 3D printing, has accelerated the development of complex, multi-scale materials. These materials can be designed to exhibit special functional properties, such as sensing, support of living cells, sound or shock absorption, or controlled expansion/shrinkage. Therefore, they are highly relevant both from a scientific and a societal point of view.

    In this talk I will discuss novel, droplet-based additive manufacturing strategies for metals, biological (living) materials, and cellular materials, in which micro-droplets or bubbles are used as modular building blocks that constitute the functional material properties. High-speed imaging proves a crucial step in the development of these processes, as it enables studying the dynamics of droplet ejection, deposition, and manipulation. Understanding these aspects is required to tune the shape, size, and constitution of the building blocks, which determine the functional properties of the deposited materials.
  • [ September 27, 2018]

    Continuous Finite- and Fixed-Time High-Order Regulators

    | It is well known that a state of a controllable linear system of an arbitrary dimension can be asymptotically driven as close to zero as necessary by means of a linear scalar feedback control. Using a continuous nonlinear scalar control law, a chain of integrators of an arbitrary dimension can be driven to the origin in finite time. Given that an arbitrary minimum phase linear system can be transformed into a chain of integrators form by using an appropriate change of variables, finite-time high-order regulators are applicable to an arbitrary minimum phase multi-dimensional linear system. A relevant problem consists in estimating the convergence (settling) time for the finite-time convergent control laws Another challenging problem is to design a fixed-time continuous control law such that a system state converges to the origin for a pre-established or fixed settling time, independently of a magnitude of initial conditions.

    The contribution of this study is twofold. First, an upper estimate of the convergence (settling) time is calculated for the finite-time convergent control algorithm that drives the state of a series of integrators to the origin. To the best of the authors’ knowledge, such an estimate is obtained for the first time. Second, a novel fixed-time continuous control law is proposed for a chain of integrators of an arbitrary dimension. Its fixed-time convergence is established and the uniform upper bound of the settling time is computed. The theoretical developments are applied to a case study of controlling a DC motor.

    Finally, an extension of the developed approach to design fixed-time observers for integrator chain systems (differentiators) is discussed and compared to a built-in Simulink differentiation technique.
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