The Experts below are selected from a list of 252 Experts worldwide ranked by ideXlab platform

Tuhin Das - One of the best experts on this subject based on the ideXlab platform.

  • Robust Control of Solid Oxide Fuel Cell Ultracapacitor Hybrid System
    IEEE Transactions on Control Systems and Technology, 2011
    Co-Authors: T. Allag, Tuhin Das
    Abstract:

    Mitigating fuel starvation and improving load-following capability of solid oxide fuel cells (SOFC) are conflicting control objectives. In this paper, we address this issue using a hybrid SOFC ultracapacitor configuration. Fuel starvation is prevented by regulating the fuel cell current using a steady-State Invariant relationship involving fuel utilization, fuel flow, and current. Two comprehensive control strategies are developed. The first is a Lyapunov-based nonlinear control and the second is a standard H∞ robust control. Both strategies additionally control the State of charge of the ultracapacitor that provides transient power compensation. A hardware-in-the-loop test stand is developed where the proposed control strategies are verified.

  • Observer Based Transient Fuel Utilization Control for Solid Oxide Fuel Cells
    ASME 2010 Dynamic Systems and Control Conference Volume 1, 2010
    Co-Authors: Tuhin Das, Andrew Slippey
    Abstract:

    Transient control is important for prolonging the life of SOFCs and broadening their applications. This paper develops an observer based method for transient control. The essential idea is to regulate the fuel cell current using the estimated State, incorporated within a steady-State Invariant property of the SOFC. The objective is to directly address hydrogen starvation in SOFCs through control of transient fuel utilization. The method is demonstrated for two different SOFC systems. The applicability across configurations indicates the possible validity of this approach for SOFCs in general. The control design is supported by simulation results.Copyright © 2010 by ASME

Rene Vidal - One of the best experts on this subject based on the ideXlab platform.

  • initial State Invariant binet cauchy kernels for the comparison of linear dynamical systems
    Conference on Decision and Control, 2013
    Co-Authors: Rizwan Chaudhry, Rene Vidal
    Abstract:

    Linear Dynamical Systems (LDSs) have been extensively used for modeling and recognition of dynamic visual phenomena such as human activities, dynamic textures, facial deformations and lip articulations. In these applications, a huge number of LDSs identified from high-dimensional time-series need to be compared. Over the past decade, three computationally efficient distances have emerged: the Martin distance [1], distances obtained from the subspace angles between observability subspaces [2], and distances obtained from the family of Binet-Cauchy kernels [3]. The main contribution of this work is to show that the first two distances are particular cases of the latter family obtained by making the Binet-Cauchy kernels Invariant to the initial States of the LDSs. We also extend Binet-Cauchy kernels to take into account the mean of the dynamical process. We evaluate the performance of our metrics on several datasets and show similar or better human activity recognition results.

  • CDC - Initial-State Invariant Binet-Cauchy kernels for the comparison of Linear Dynamical Systems
    52nd IEEE Conference on Decision and Control, 2013
    Co-Authors: Rizwan Chaudhry, Rene Vidal
    Abstract:

    Linear Dynamical Systems (LDSs) have been extensively used for modeling and recognition of dynamic visual phenomena such as human activities, dynamic textures, facial deformations and lip articulations. In these applications, a huge number of LDSs identified from high-dimensional time-series need to be compared. Over the past decade, three computationally efficient distances have emerged: the Martin distance [1], distances obtained from the subspace angles between observability subspaces [2], and distances obtained from the family of Binet-Cauchy kernels [3]. The main contribution of this work is to show that the first two distances are particular cases of the latter family obtained by making the Binet-Cauchy kernels Invariant to the initial States of the LDSs. We also extend Binet-Cauchy kernels to take into account the mean of the dynamical process. We evaluate the performance of our metrics on several datasets and show similar or better human activity recognition results.

T. Allag - One of the best experts on this subject based on the ideXlab platform.

  • Robust Control of Solid Oxide Fuel Cell Ultracapacitor Hybrid System
    IEEE Transactions on Control Systems and Technology, 2011
    Co-Authors: T. Allag, Tuhin Das
    Abstract:

    Mitigating fuel starvation and improving load-following capability of solid oxide fuel cells (SOFC) are conflicting control objectives. In this paper, we address this issue using a hybrid SOFC ultracapacitor configuration. Fuel starvation is prevented by regulating the fuel cell current using a steady-State Invariant relationship involving fuel utilization, fuel flow, and current. Two comprehensive control strategies are developed. The first is a Lyapunov-based nonlinear control and the second is a standard H∞ robust control. Both strategies additionally control the State of charge of the ultracapacitor that provides transient power compensation. A hardware-in-the-loop test stand is developed where the proposed control strategies are verified.

Rizwan Chaudhry - One of the best experts on this subject based on the ideXlab platform.

  • initial State Invariant binet cauchy kernels for the comparison of linear dynamical systems
    Conference on Decision and Control, 2013
    Co-Authors: Rizwan Chaudhry, Rene Vidal
    Abstract:

    Linear Dynamical Systems (LDSs) have been extensively used for modeling and recognition of dynamic visual phenomena such as human activities, dynamic textures, facial deformations and lip articulations. In these applications, a huge number of LDSs identified from high-dimensional time-series need to be compared. Over the past decade, three computationally efficient distances have emerged: the Martin distance [1], distances obtained from the subspace angles between observability subspaces [2], and distances obtained from the family of Binet-Cauchy kernels [3]. The main contribution of this work is to show that the first two distances are particular cases of the latter family obtained by making the Binet-Cauchy kernels Invariant to the initial States of the LDSs. We also extend Binet-Cauchy kernels to take into account the mean of the dynamical process. We evaluate the performance of our metrics on several datasets and show similar or better human activity recognition results.

  • CDC - Initial-State Invariant Binet-Cauchy kernels for the comparison of Linear Dynamical Systems
    52nd IEEE Conference on Decision and Control, 2013
    Co-Authors: Rizwan Chaudhry, Rene Vidal
    Abstract:

    Linear Dynamical Systems (LDSs) have been extensively used for modeling and recognition of dynamic visual phenomena such as human activities, dynamic textures, facial deformations and lip articulations. In these applications, a huge number of LDSs identified from high-dimensional time-series need to be compared. Over the past decade, three computationally efficient distances have emerged: the Martin distance [1], distances obtained from the subspace angles between observability subspaces [2], and distances obtained from the family of Binet-Cauchy kernels [3]. The main contribution of this work is to show that the first two distances are particular cases of the latter family obtained by making the Binet-Cauchy kernels Invariant to the initial States of the LDSs. We also extend Binet-Cauchy kernels to take into account the mean of the dynamical process. We evaluate the performance of our metrics on several datasets and show similar or better human activity recognition results.

J Matas - One of the best experts on this subject based on the ideXlab platform.

  • Steady-State Invariant frequency and amplitude droop control using adaptive output impedance for parallel-connected UPS inverters
    Twentieth Annual IEEE Applied Power Electronics Conference and Exposition 2005. APEC 2005., 2005
    Co-Authors: J.m. Guerrero, J Matas, L.g. De Vicuna, J. Miret, J. Cruz
    Abstract:

    In this paper, a novel wireless load-sharing controller for parallel connected UPS inverters is proposed. As opposed to the conventional droop method, the proposed method achieves stable steady-State frequency and amplitude. The paper explorers the output impedance of the UPS inverters, and adaptive virtual output impedance is proposed in order to reduce its line impedance impact. Experimental results are presented from two 6 kVA UPS inverters controlled by TMS320LF2407A DSP boards, showing the feasibility of the proposed approach

  • steady State Invariant frequency control of parallel redundant uninterruptible power supplies
    Conference of the Industrial Electronics Society, 2002
    Co-Authors: Garcia L De Vicuna, J Matas, Jaume Miret
    Abstract:

    In this paper, a new approach for the wireless control of parallel-connected uninterruptible power supplies is proposed. This method can perform the output-voltage frequency accuracy of the paralleled system, by using a transient droop characteristic. In this manner, the controller endows to the system absence of frequency-deviation in steady State conditions. This fact contrasts with conventional P-/spl omega/ droop schemes, in which the trade-off between active power sharing and frequency variation limits strongly the performances. The proposed control is particularly suitable since both steady-State Invariant frequency and good current balance are achieved. In addition, the transient response can be easily modified by means of controller parameters. Simulation results are reported to prove the feasibility of the approach for this kind of systems.