Minyue Fu

University of Newcastle, Newcastle, New South Wales, Australia

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Publications (300)346.46 Total impact

  • Huanshui Zhang · Juanjuan Xu · Minyue Fu ·
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    ABSTRACT: This paper is concerned with the long-standing problems of linear quadratic regulation (LQR) control and stabilization for a class of discrete-time stochastic systems involving multiplicative noises and input delay. These fundamental problems have attracted resurgent interests due to development of networked control systems. An explicit analytical expression is given for the optimal LQR controller. More specifically, the optimal LQR controller is shown to be a linear function of the conditional expectation of the state, with the feedback gain based on a Riccati-ZXL difference equation. It is also shown that the system is stabilizable in the mean-square sense if and only if an algebraic Riccati-ZXL equation has a particular solution. These results are based on a new technical tool, which establishes a non-homogeneous relationship between the state and the costate of this class of systems, and the introduction of a new Lyapunov function for the finite-horizon optimal control design.
    IEEE Transactions on Automatic Control 10/2015; 60(10):1-1. DOI:10.1109/TAC.2015.2411911 · 2.78 Impact Factor
  • Damian Marelli · Minyue Fu · Brett Ninness ·
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    ABSTRACT: Bayesian tracking is a general technique for state estimation of nonlinear dynamic systems, but it suffers from the drawback of computational complexity. This paper is concerned with a class of Wiener systems with multiple nonlinear sensors. Such a system consists of a linear dynamic system followed by a set of static nonlinear measurements. We study a maximum-likelihood Kalman filtering (MLKF) technique which involves maximum-likelihood estimation of the nonlinear measurements followed by classical Kalman filtering. This technique permits a distributed implementation of the Bayesian tracker and guarantees the boundedness of the estimation error. The focus of this paper is to study the extent to which the MLKF technique approximates the theoretically optimal Bayesian tracker. We provide conditions to guarantee that this approximation becomes asymptotically exact as the number of sensors becomes large. Two case studies are analyzed in detail.
    IEEE Transactions on Signal Processing 09/2015; 63(17):1-1. DOI:10.1109/TSP.2015.2440220 · 2.79 Impact Factor
  • Tianju Sui · Minyue Fu · Keyou You ·
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    ABSTRACT: This study studies a sensor scheduling problem for the state estimation of a stochastic discrete-time system where the measurements are to be sent from multiple sensors to a centralised estimator through a lossy channel. By adopting a carrier sense multiple access/collision avoidance (CSMA/CA) protocol, the packet loss rate of the channel increases with the number of competing sensors for data communication. To increase the channel utilisation, it requires to smartly select informative sensors to transmit their measurements. Depending on the availability of the acknowledgment (ACK) messages from the estimator, both online and offline algorithms for scheduling sensor communication are proposed to optimise the expected performance of minimum mean-square error state estimator. Particularly, the online scheduling uses the ACK to trigger the sensor communication while the offline version adopts a random transmission framework and only decides the probability of sending measurements for each sensor in an offline manner. The optimal online scheduler is given by the solution of an integer programming, which is approximated by a practically solvable optimisation. Simulations are included to demonstrate the effectiveness of the proposed algorithms.
    IET Control Theory and Applications 08/2015; 9(16). DOI:10.1049/iet-cta.2014.1038 · 2.05 Impact Factor
  • Source
    Tingrui Han · Zhiyun Lin · Minyue Fu ·
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    ABSTRACT: This paper concentrates on the formation merging control problem for a leader–follower network. The objective is to control a team of agents called followers such that they are merged with another team of agents called leaders to form a single globally rigid formation. A method based on graph Laplacian is introduced to address this problem. Each follower selects its interaction neighbors and interaction weights according to the given target configuration. The graph modeling the interaction topology of all the agents is directed and time-varying. First, by assuming that the synchronized velocity of the leaders is known to all the followers, a necessary and sufficient condition is derived to ensure uniform asymptotic formation merging. Second, we relax this assumption and consider that the velocity of the leaders is known to only a subset of followers, for which the same necessary and sufficient condition is obtained with the help of an internal model for velocity synchronization.
    Automatica 08/2015; 58:99-105. DOI:10.1016/j.automatica.2015.04.027 · 3.02 Impact Factor
  • Zhiyun Lin · Lili Wang · Zhimin Han · Minyue Fu ·

    IEEE Transactions on Automatic Control 07/2015; DOI:10.1109/TAC.2015.2454711 · 2.78 Impact Factor
  • Source
    Zhiyun Lin · Minyue Fu · Yingfei Diao ·
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    ABSTRACT: This paper studies the 2D localization problem of a sensor network given anchor node positions in a common global coordinate frame and relative position measurements in local coordinate frames between node pairs. It is assumed that the local coordinate frames of different sensors have different orientations and the orientation difference with respect to the global coordinate frame are not known. In terms of graph connectivity, a necessary and sufficient condition is obtained for self-localizability that leads to a fully distributed localization algorithm. Moreover, a distributed verification algorithm is developed to check the graph connectivity condition, which can terminate successfully when the sensor network is self-localizable. Finally, a fully distributed, linear, and iterative algorithm based on the complex-valued Laplacian associated with the sensor network is proposed, which converges globally and gives the correct localization result.
    IEEE Transactions on Signal Processing 07/2015; 63(14):1-1. DOI:10.1109/TSP.2015.2432739 · 2.79 Impact Factor
  • Source
    Tianju Sui · Keyou You · Minyue Fu ·
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    ABSTRACT: This paper studies a networked state estimation problem for a spatially large linear system with a distributed array of sensors, each of which offers partial state measurements. A lossy communication network is used to transmit the sensor measurements to a central estimator where the minimum mean square error (MMSE) state estimate is computed. Under a Markovian packet loss model, we provide necessary and sufficient conditions for the stability of the estimator for any diagonalizable system in the sense that the mean of the state estimation error covariance matrix is uniformly bounded. In particular, the stability conditions for the second-order systems with an i.i.d. packet loss model are explicitly expressed as simple inequalities in terms of the largest open-loop pole and the packet loss rate.
    Automatica 03/2015; 53. DOI:10.1016/j.automatica.2014.12.022 · 3.02 Impact Factor
  • Source
    Ronghao Zheng · Zhiyun Lin · Minyue Fu · Dong Sun ·
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    ABSTRACT: The paper studies the general circumnavigation problem for a team of unicycle-type agents, with the goal of achieving specific circular formations and circling on different orbits centered at a target of interest. A novel distributed solution is proposed, in which the control laws are heterogeneous for the agents such that some agents are repellant from the target while attractive to its unique neighbor and some agents are attractive to the target while repellant from its neighbor. A systematic procedure is developed to design the control parameters according to the specific radii of the orbits and the formations that the agents are desired to converge to. Moreover, this control scheme uses a minimum number of information flow links between the agents and local measurements of relative position only. Based on the block diagonalization of circulant matrices by a Fourier transform, asymptotic convergence properties are analyzed rigorously. The validity of the proposed control algorithm is also demonstrated through numerical simulations.
    Automatica 03/2015; 53. DOI:10.1016/j.automatica.2014.11.012 · 3.02 Impact Factor
  • Source
    Yuting Mou · Hao Xing · Zhiyun Lin · Minyue Fu ·
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    ABSTRACT: Plug-in hybrid electric vehicles (PHEV) are expected to become widespread in the near future. However, high penetration of PHEVs can overload the distribution system. In smart grid, the charging of PHEVs can be controlled to reduce the peak load, known as demand-side management (DSM). In this paper, we focus on the DSM for PHEV charging at low-voltage transformers (LVTs). The objective is to flatten the load curve of LVTs, while satisfying each consumer’s requirement for their PHEV to be charged to the required level by the specified time. We first formulate this problem as a convex optimization problem and then propose a decentralized water-filling-based algorithm to solve it. A moving horizon approach is utilized to handle the random arrival of PHEVs and the inaccuracy of the forecast nonPHEV load. We focus on decentralized solutions so that computational load can be shared by individual PHEV chargers and the algorithm is scalable. Numerical simulations are given to demonstrate the effectiveness of our algorithm.
    IEEE Transactions on Smart Grid 03/2015; 6(2):726-736. DOI:10.1109/TSG.2014.2363096 · 4.25 Impact Factor
  • H. Xing · Y. Mou · M. Fu · Z. Lin ·
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    ABSTRACT: Economic dispatch problem (EDP) is an important optimization problem in power systems, aiming at minimizing the aggregate cost of a group of power generators, which cooperatively generate a given amount of power within their individual capacity constraints. In this paper, we present an average consensus based bisection approach for the EDP with quadratic cost functions, which is fully distributed and especially desirable in a smart grid scenario. Under the connected topology condition, we show that the proposed iterative solution converges to the globally optimal solution of EDP, without the need for a central decision maker or a leader node. Finally, numerical simulation based on the IEEE 14-bus system is given to show the performance of the approach.
    Proceedings of the IEEE Conference on Decision and Control 02/2015; 2015:3789-3794. DOI:10.1109/CDC.2014.7039979
  • Lili Wang · Zhiyun Lin · Minyue Fu ·
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    ABSTRACT: This paper proposes a simple, distributed control protocol for multi-agent systems with relative sensing capability over a directed network to achieve an affine formation. In contrast to the linear consensus protocol, the control protocol in this paper takes both positive and negative weights that partially encode the target formation shape and is thus able to achieve a formation pattern rather than just consensus. Having possibly negative weights in a graph, the associated Laplacian is called the generalized Laplacian. The connection between the generic rank property of the generalized Laplacian and the connectivity of a directed graph is established, based on which a necessary and sufficient graphical condition is developed to ensure the emergence of an affine formation by the proposed distributed control protocol.
    Proceedings of the IEEE Conference on Decision and Control 02/2015; 2015:3017-3022. DOI:10.1109/CDC.2014.7039853
  • Z. Han · Z. Lin · M. Fu ·
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    ABSTRACT: This paper studies the formation maneuvering control problem for a network of agents with the objective of achieving a desired group formation shape and a constant over-all group maneuvering velocity. A fully distributed approach is developed to solve the problem. That is, a control law is proposed for each agent in the network, with its parameters capable of being designed in a distributed manner, and is implementable locally via relative sensing and communication with neighbors. Necessary and sufficient conditions regarding a critical control parameter are obtained to guarantee the globally asymptotic convergence of the overall system for both the single-integrator kinematics case and the double-integrator dynamics case.
    Proceedings of the IEEE Conference on Decision and Control 02/2015; 2015:6185-6190. DOI:10.1109/CDC.2014.7040358

  • IEEE/ASME Transactions on Mechatronics 01/2015; DOI:10.1109/TMECH.2015.2496343 · 3.43 Impact Factor
  • Yingfei Diao · Minyue Fu · Zhiyun Lin · Huanshui Zhang ·

    IEEE Transactions on Control of Network Systems 01/2015; DOI:10.1109/TCNS.2015.2426772
  • Yuanhua Yang · Minyue Fu · Huanshui Zhang ·
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    ABSTRACT: This paper studies an optimal state estimation (Kalman filtering) problem under the assumption that output measurements are subject to random time delays caused by network transmissions without time stamping. We first propose a random time delay model which mimics many practical digital network systems. We then study the so-called unbiased, uniformly bounded linear state estimators and show that the estimator structure is given based on the average of all received measurements at each time for different maximum time delays. The estimator gains can be derived by solving a set of recursive discrete-time Riccati equations. The estimator is guaranteed to be optimal in the sense that it is unbiased with uniformly bounded estimation error covariance. A simulation example shows the effectiveness of the proposed algorithm.Copyright © 2013 John Wiley & Sons, Ltd.
    International Journal of Robust and Nonlinear Control 11/2014; 24(17). DOI:10.1002/rnc.3016 · 3.18 Impact Factor
  • Source
    Tianju Sui · Keyou You · Minyue Fu · Damian Marelli ·
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    ABSTRACT: This paper studies the state estimation problem for a stochastic discrete-time system over a lossy channel where the packet loss is modeled as an independent and identically distributed binary process. To counter the effect of random packet loss, we propose a linear coding method to preprocess the measured output, and prove that the coded output is information preserving when packet loss is void and is information enhancing when packet loss is present. An optimal state estimator under the minimum mean square error (MMSE) criterion is derived for the coded output when subject to packet loss. The maximum packet loss rate for ensuring a stable estimator is then derived and shown to be very close to a well-known lower bound. Also considered is a compressed linear coding method where the measured output is first compressed onto a lower dimensional space before encoding, and it is shown that the similar packet rate condition for stability holds.
    Automatica 11/2014; 51. DOI:10.1016/j.automatica.2014.10.086 · 3.02 Impact Factor
  • Source
    Damián Edgardo Marelli · Minyue Fu ·
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    ABSTRACT: In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.
    Automatica 11/2014; 51. DOI:10.1016/j.automatica.2014.10.077 · 3.02 Impact Factor
  • E.R. Rohr · Damian Marelli · Minyue Fu ·
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    ABSTRACT: This paper addresses the stability of a Kalman filter when measurements are intermittently available due to constraints in the communication channel between the sensor and the estimator. We give a necessary condition and a sufficient condition, with a trivial gap between them, for the boundedness of the expected value of the estimation error covariance. These conditions are more general than the existing ones in the sense that they only require the state matrix of the system to be diagonalizable and the sequence of packet losses to be a stationary finite order Markov process. Hence, we extend the class of systems for which these conditions are known in two directions, namely, by including degenerate systems, and by considering network models more general than i.i.d. and Gilbert-Elliott. We show that these conditions recover known results from the literature when evaluated for non-degenerate systems under the assumption of i.i.d. or Gilbert-Elliott packet loss models.
    IEEE Transactions on Automatic Control 10/2014; 59(10). DOI:10.1109/TAC.2014.2328183 · 2.78 Impact Factor
  • Source
    Keyou You · Tianju Sui · Minyue Fu ·
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    ABSTRACT: In this paper, we study the mean square stability of Kalman filtering of a discrete-time stochastic system under two periodically switching sensors. The sensor measurements are sent to a remote estimator over a lossy channel whose packet loss process is independent and identically distributed. We prove that the problem can be converted into the stability analysis of Kalman filtering using two sensors at each time, and the measurements of each sensor are transmitted to the estimator via an independent lossy channel of the same packet loss rate. Some necessary and/or sufficient conditions for stability of the estimation error covariance matrices are derived. Moreover, the effect of the sensor switching on the filter stability is revealed. Their implications and relationships with related results in the literature are discussed.
    Asian Journal of Control 09/2014; 17(1). DOI:10.1002/asjc.975 · 1.56 Impact Factor
  • Yingfei Diao · Zhiyun Lin · Minyue Fu ·
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    ABSTRACT: This paper studies the problem of determining the sensor locations in a large sensor network using only relative distance (range) measurements. Based on a generalized barycentric coordinate representation, our work generalizes the DILOC algorithm to the localization problem under arbitrary deployments of sensor nodes and anchor nodes. First, a criterion and algorithm are developed to determine a generalized barycentric coordinate of a node with respect to its neighboring nodes, which do not require the node to be inside the convex hull of its neighbors. Next, for the localization problem based on the generalized barycentric coordinate representation, a necessary and sufficient condition for the localizability of a sensor network with a generic configuration is obtained. Finally, a new linear iterative algorithm is proposed to ensure distributed implementation as well as global convergence to the true coordinates.
    IEEE Transactions on Signal Processing 09/2014; 62(18):4760-4771. DOI:10.1109/TSP.2014.2339797 · 2.79 Impact Factor

Publication Stats

4k Citations
346.46 Total Impact Points


  • 1994-2015
    • University of Newcastle
      • • School of Electrical Engineering and Computer Science
      • • Centre for Complex Dynamic Systems and Control
      • • Department of Electrical Engineering
      Newcastle, New South Wales, Australia
  • 2010-2013
    • Zhejiang University
      • Department of Control Science and Engineering
      Hang-hsien, Zhejiang Sheng, China
    • Shandong University
      Chi-nan-shih, Shandong Sheng, China
  • 2012
    • Beijing Institute Of Technology
      • School of Automation
      Peping, Beijing, China
  • 2004
    • National ICT Australia Ltd
      Sydney, New South Wales, Australia
  • 2003
    • Federal University of Santa Catarina
      Nossa Senhora do Destêrro, Santa Catarina, Brazil
  • 1994-2000
    • University of Iowa
      • Department of Electrical and Computer Engineering
      Iowa City, IA, United States
  • 1999
    • Newcastle University
      Newcastle-on-Tyne, England, United Kingdom
  • 1996
    • Illinois Institute of Technology
      • Department of Electrical & Computer Engineering
      Chicago, IL, United States
  • 1995
    • Tel Aviv University
      • Department of Electrical Engineering - Systems
      Tell Afif, Tel Aviv, Israel