77 research outputs found

    Properties of recoverable region and semi-global stabilization in recoverable region for linear systems subject to constraints

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    This paper investigates time-invariant linear systems subject to input and state constraints. It is shown that the recoverable region (which is the largest domain of attraction that is theoretically achievable) can be semiglobally stabilized by continuous nonlinear feedbacks while satisfying the constraints. Moreover, a reduction technique is presented which shows, when trying to compute the recoverable region, that we only need to compute the recoverable region for a system of lower dimension which generally leads to a considerable simplification in the computational effort

    Internal stabilization and external LpL_p stabilization of linear systems subject to constraints

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    Having studied during the last decade several aspects of several control design problems for linear systems subject to magnitude and rate constraints on control variables, during the last two years the research has broadened to include magnitude constraints on control variables as well as state variables. Recent work by Han et al. (2000), Hou et al. (1998) and Saberi et al. (2002) considered linear systems in a general framework for constraints including both input magnitude constraints as well as state magnitude constraints. In particular, Saberi et al. consider internal stabilization while Han et al. consider output regulation in different frameworks, namely a global, semiglobal, and regional framework. These problems require very strong solvability conditions. Therefore, a main focus for future research should focus on finding a controller with a large domain of attraction and some good rejection properties for disturbances restricted to some bounded se

    Implementation of a Symbolic Circuit Simulator for Topological Network Analysis

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    Abstract- Many topological approaches to symbolic network analysis have been proposed in the literature, but none are implemented ultimately as a simulator for large network analysis due to their complexity and exponentially increasing number of terms. A novel methodology adopted in this paper uses a graph reduction approach based on a set of graph reduction rules developed recently. Furthermore, a Binary Decision Diagram is used in the implementation of a symbolic simulator that is capable of analyzing large analog circuit blocks. Implementation details and experimental results are reported. Keywords-admissible term, BDD, graph reduction, symbolic analysis I

    A Fast Symbolic Computation Approach to Statistical Analysis of Mesh Networks with Multiple Sources *

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    Abstract-Mesh circuits typically consist of many resistive links and many sources. Accurate analysis of massive mesh networks is demanding in the current integrated circuit design practice, yet their computation confronts numerous challenges. When variation is considered, mesh analysis becomes a much harder task. This paper proposes a symbolic computation technique that can be applied to the moment-based analysis of mesh networks with multiple sources. The variation issues are easily taken care of by a structured computation mechanism, which can naturally facilitate sensitivity based analysis. Applications are addressed by applying the computation technique to a set of mesh circuits with varying sizes

    Constrained output regulation of discrete-time linear plants

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    Atomistic simulations of thermodynamic properties of liquid gallium from first principles

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    In the research of condensed matter, atomistic dynamic simulations play a crucial role, particularly in revealing dynamic processes, phase transitions and thermodynamic statistics macroscopic physical properties in systems such as solids and liquids. For a long time, simulating complex and disordered liquids has been a challenge compared to ordered crystalline structures. The primary reasons for this challenge are the lack of precise force field functions and the neglect of nuclear quantum effects. To overcome these two limits in simulation of liquids, we use a deep potential (DP) with quantum thermal bath (QTB) approach. DP is a machine learning model are sampled from density functional theory and able to do large-scale atomic simulations with its precision. QTB is a method which incorporates nuclear quantum effects by quantum fluctuation dissipation. The application of this first principles approach enable us to successfully describe the phase transition processes in solid and liquid Gallium (Ga) as well as the associated dynamic phenomena. More importantly, we obtain the thermodynamic properties of liquid Ga, such as internal energy, specific heat, enthalpy change, entropy and Gibbs free energy, and these results align remarkably well with experiments. Our research has opened up a new paradigm for the study of dynamics and thermodynamics in liquids, amorphous materials, and other disordered systems, providing valuable insights and references for future investigations.Comment: 7 pages, 11 figures for maintext; 6pages, 8 figures for supplementary material

    A review of phase change heat transfer in shape-stabilized phase change materials (ss-PCMs) based on porous supports for thermal energy storage

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    Latent heat thermal energy storage (LHTES) uses phase change materials (PCMs) to store and release heat, and can effectively address the mismatch between energy supply and demand. However, it suffers from low thermal conductivity and the leakage problem. One of the solutions is integrating porous supports and PCMs to fabricate shape-stabilized phase change materials (ss-PCMs). The phase change heat transfer in porous ss-PCMs is of fundamental importance for determining thermal-fluidic behaviours and evaluating LHTES system performance. This paper reviews the recent experimental and numerical investigations on phase change heat transfer in porous ss-PCMs. Materials, methods, apparatuses and significant outcomes are included in the section of experimental studies and it is found that paraffin and metal foam are the most used PCM and porous support respectively in the current researches. Numerical advances are reviewed from the aspect of different simulation methods. Compared to representative elementary volume (REV)-scale simulation, the pore-scale simulation can provide extra flow and heat transfer characteristics in pores, exhibiting great potential for the simulation of mesoporous, microporous and hierarchical porous materials. Moreover, there exists a research gap between phase change heat transfer and material preparation. Finally, this review outlooks the future research topics of phase change heat transfer in porous ss-PCMs
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