9,831 research outputs found

    Decentralized control with input saturation: a first step toward design

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    This article summarizes important observations about control of decentralized systems with input saturation and provides a few examples that give insight into the structure of such systems

    Quantum Internal Model Principle: Decoherence Control

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    In this article, we study the problem of designing a Decoherence Control for quantum systems with the help of a scalable ancillary quantum control and techniques from geometric control theory, in order to successfully and completely decouple an open quantum system from its environment. We re-formulate the problem of decoherence control as a disturbance rejection scheme which also leads us to the idea of Internal Model Principle for quantum control systems which is first of its kind in the literature. It is shown that decoupling a quantum disturbance from an open quantum system, is possible only with the help of a quantum controller which takes into account the model of the environmental interaction. This is demonstrated for a simple 2-qubit system wherein the effects of decoherence are completely eliminated. The theory provides conditions to be imposed on the controller to ensure perfect decoupling. Hence the problem of decoherence control naturally gives rise to the quantum internal model principle which relates the disturbance rejecting control to the model of the environmental interaction. Classical internal model principle and disturbance decoupling focus on different aspects viz. perfect output tracking and complete decoupling of output from external disturbances respectively. However for quantum systems, the two problems come together and merge in order to produce an effective platform for decoherence control. In this article we introduce a seminal connection between disturbance decoupling and the corresponding analog for internal model principle for quantum systems.Comment: Submitted to IEEE Transactions on Automatic Control, Mar 15 2010. A basic introduction appeared in 46th IEEE CDC 2007. Acknowledgements: The authors would like to thank the Center for Quantum Information Science and Technology at Tsinghua University, R.-B. Wu, J. Zhang, J.-W. Wu, M. Jiang, C.-W. Li and G.-L. Long for their valuable comments and suggestion

    Parameter Varying Mode Decoupling for LPV systems

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    The paper presents the design of parameter varying input and output transformations for Linear Parameter Varying systems, which make possible the control of a selected subsystem. In order to achieve the desired decoupling the inputs and outputs of the plant are blended together, and so the MIMO control problem is reduced to a SISO one. The new input of the blended system will only interact with the selected subsystem, while the response of the undesired dynamical part is suppressed in the single output. Decoupling is achieved over the whole parameter range, and no further dynamics are introduced. Linear Matrix Inequality methods form the basis of the proposed approach, where the minimum sensitivity (denoted by the H − index) is maximized for the subsystem to be controlled, while the H∞ norm of the subsystem to be decoupled is minimized. The method is evaluated on a flexible wing aircraft model

    Trade-off between complexity and BER performance of a polynomial SVD-based broadband MIMO transceiver

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    In this paper we investigate non-linear precoding solutions for the problem of broadband multiple-input multiple output(MIMO) systems. Based on a polynomial singular value decomposition (PSVD) we can decouple a broadband MIMO channel into independent dispersive spectrally majorised single-input single-output (SISO) subchannels. In this contribution, the focus of our work is to explore the influence of approximations on the PSVD, and the performance degradation that can be expected as a result

    The decoupling problem : invariants, parameter variations, composite systems and time-varying linear systems

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    On computing minimal realizations of periodic descriptor systems

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    Abstract: We propose computationally efficient and numerically reliable algorithms to compute minimal realizations of periodic descriptor systems. The main computational tool employed for the structural analysis of periodic descriptor systems (i.e., reachability and observability) is the orthogonal reduction of periodic matrix pairs to Kronecker-like forms. Specializations of a general reduction algortithm are employed for particular type of systems. One of the proposed minimal realization transformations for which the backward numerical stability can be proved
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