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Automatic Control, IEEE Transactions on

Issue 12 • Date Dec. 2010

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Displaying Results 1 - 25 of 34
  • Table of contents

    Page(s): C1 - C4
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    Freely Available from IEEE
  • IEEE Control Systems Society

    Page(s): C2
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    Freely Available from IEEE
  • Scanning the issue

    Page(s): 2677 - 2678
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  • Cooperative Minimum Time Surveillance With Multiple Ground Vehicles

    Page(s): 2679 - 2691
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1008 KB) |  | HTML iconHTML  

    In this paper, we formulate and solve two different minimum time problems related to unmanned ground vehicle (UGV) surveillance. The first problem is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from a point on a path and such that the time for executing the search in parallel is minimized. Here, the sensors' field of view are assumed to have a limited coverage range and be occluded by the obstacles. View full abstract»

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  • A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

    Page(s): 2692 - 2707
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (576 KB) |  | HTML iconHTML  

    In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems. View full abstract»

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  • Non-Asymptotic Confidence Sets for the Parameters of Linear Transfer Functions

    Page(s): 2708 - 2720
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (669 KB) |  | HTML iconHTML  

    We consider the problem of constructing confidence sets for the parameters of input-output transfer functions based on observed data. The assumptions on the noise affecting the system are reduced to a minimum; the noise can virtually be anything, but in return the user must be able to select the input signal. In this paper a procedure for solving this problem is developed in the general framework of leave-out sign-dominant confidence regions. The procedure returns confidence regions that are guaranteed to contain the true transfer function with a user-chosen probability for any finite data set. View full abstract»

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  • Engineering Stable Discrete-Time Quantum Dynamics via a Canonical QR Decomposition

    Page(s): 2721 - 2734
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (483 KB) |  | HTML iconHTML  

    We analyze the asymptotic behavior of discrete-time, Markovian quantum systems with respect to a subspace of interest. Global asymptotic stability of subspaces is relevant to quantum information processing, in particular for initializing the system in pure states or subspace codes. We provide a linear-algebraic characterization of the dynamical properties leading to invariance and attractivity of a given quantum subspace. We then construct a design algorithm for discrete-time feedback control that allows to stabilize a target subspace, proving that if the control problem is feasible, then the algorithm returns an effective control choice. In order to prove this result, a canonical QR matrix decomposition is derived, and also used to establish the control scheme potential for the simulation of open-system dynamics. View full abstract»

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  • Asynchronous Distributed Optimization With Event-Driven Communication

    Page(s): 2735 - 2750
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1127 KB) |  | HTML iconHTML  

    We consider problems where multiple agents cooperate to control their individual state so as to optimize a common objective while communicating with each other to exchange state information. Since communication costs can be significant, especially when the agents are wireless devices with limited energy, we seek conditions under which communication of state information among nodes can be restricted while still ensuring that the optimization process converges. We propose an asynchronous (event-driven) optimization scheme that limits communication to instants when some state estimation error function at a node exceeds a threshold and prove that, under certain conditions, such convergence is guaranteed when communication delays are negligible. We subsequently extend the analysis to include communication delays as long as they are bounded. We apply this approach to a sensor network coverage control problem where the objective is to maximize the probability of detecting events occurring in a given region and show that the proposed asynchronous approach may significantly reduce communication costs, hence also prolonging the system's lifetime, without any performance degradation. View full abstract»

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  • Finite Adaptability in Multistage Linear Optimization

    Page(s): 2751 - 2766
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (644 KB) |  | HTML iconHTML  

    In multistage problems, decisions are implemented sequentially, and thus may depend on past realizations of the uncertainty. Examples of such problems abound in applications of stochastic control and operations research; yet, where robust optimization has made great progress in providing a tractable formulation for a broad class of single-stage optimization problems with uncertainty, multistage problems present significant tractability challenges. In this paper we consider an adaptability model designed with discrete second stage variables in mind. We propose a hierarchy of increasing adaptability that bridges the gap between the static robust formulation, and the fully adaptable formulation. We study the geometry, complexity, formulations, algorithms, examples and computational results for finite adaptability. In contrast to the model of affine adaptability proposed in, our proposed framework can accommodate discrete variables. In terms of performance for continuous linear optimization, the two frameworks are complementary, in the sense that we provide examples that the proposed framework provides stronger solutions and vice versa. We prove a positive tractability result in the regime where we expect finite adaptability to perform well, and illustrate this claim with an application to Air Traffic Control. View full abstract»

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  • Optimal Scheduling of a Single-Supplier Single-Manufacturer Supply Chain With Common due Windows

    Page(s): 2767 - 2777
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (406 KB) |  | HTML iconHTML  

    We study a supply chain scheduling control problem involving a single supplier, a single manufacturer and multiple retailers, where the manufacturer with limited production capacity can only take some of the orders of the retailers. The manufacturer aims to maximize its profit, which is a function of the storage time, storage quantity, order sequence dependent weighted storage costs, and idle time of the orders to be accepted. We formulate the problem as a two-machine common due windows proportionate flow shop scheduling problem. We show that the problem is NP-hard. We provide the first pseudo-polynomial algorithm to optimally solve the problem. We show that for an accepted set of orders the shortest processing time earliest permutation schedule yields an optimal schedule. We prove that we can reduce the latest due dates of the due windows, which are given parameters, for minimizing the computational effort. We establish a tight upper bound on the enumeration process to manage the order idle time. We eliminate the need for generating all the optimal partial schedules to obtain an optimal solution, thus reducing the running time of our algorithm for solving the problem. We computationally tested the algorithm and the results show that the algorithm can solve large-sized problems very efficiently. View full abstract»

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  • Optimization Based Production Planning With Hybrid Dynamics and Constraints

    Page(s): 2778 - 2792
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (816 KB) |  | HTML iconHTML  

    Optimizing production planning has tremendous economic impact for many industrial production systems. In this paper, the planning problem of a class of production systems with hybrid dynamics and constraints is considered with practical background of power generation planning and other applications. The problem is solved within the Lagrangian relaxation framework, with the system wide demand and resource limit constraints relaxed by Lagrange multipliers. A new method is developed in this paper to obtain the exact optimal solutions to the subproblems with hybrid dynamics and constraints efficiently without discretizing the continuous production levels or introducing intermediate levels of relaxation. A novel definition of the discrete state associated with a consecutive time span is introduced so that solving each subproblem is converted into solving a number of continuous optimization problems and a discrete optimization problem separately. An efficient double dynamic programming (DP) method is developed to solve these subproblems and the principle of optimality is guaranteed for both the continuous and discrete problem. The production levels in a consecutive running span with non-convex piecewise linear cost functions are determined in a DP forward sweep without discretization. The DP method is then applied to determine the optimal discrete operating states across time efficiently. Numerical testing results demonstrate that the new method is efficient and effective for optimization based production planning with the complex hybrid dynamics and constraints. View full abstract»

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  • The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space

    Page(s): 2793 - 2798
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (296 KB) |  | HTML iconHTML  

    We consider autonomous partially observable Markov decision processes where the control action influences the observation process only. Considering entropy as the cost incurred by the Markov information state process, the optimal observability problem is posed as a Markov decision scheduling problem that minimizes the infinite horizon cost. This scheduling problem is shown to be equivalent to minimization of an entropy measure, called estimation entropy which is related to the invariant measure of the information state. View full abstract»

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  • The NCE (Mean Field) Principle With Locality Dependent Cost Interactions

    Page(s): 2799 - 2805
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (412 KB) |  | HTML iconHTML  

    We study large population stochastic dynamic games where each agent assigns individually determined coupling strengths (with possible spatial interpretation) to the states of other agents in its performance function. The mean field methodology yields a set of decentralized controls which generates an -Nash equilibrium for the population of size . A key feature of the mean field approximation (here with localized interactions) is that the resulting th individual agent's control law depends on that agent's state and the precomputable weighted average trajectory of the collection of all agents each applying a decentralized control law. View full abstract»

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  • Three-Dimensional Motion Coordination in a Spatiotemporal Flowfield

    Page(s): 2805 - 2810
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (482 KB) |  | HTML iconHTML  

    Decentralized algorithms to stabilize 3-D formations of unmanned vehicles in a flowfield that varies in space and time have applications in environmental monitoring in the atmosphere and ocean. In this note, we provide a Lyapunov-based control design to steer a system of self-propelled particles traveling in three dimensions at a constant speed relative to a spatiotemporal flowfield. We assume that the flow is known locally to each particle and that it does not exceed the particle speed. Multiple particles can be steered to form 3-D parallel or helical formations in a flowfield. Also presented are motion coordination results for a special case of the 3-D model in which the particles travel in a circular formation on the surface of a rotating sphere. View full abstract»

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  • On the Equivalent Relationship Between Generalized Performance, Robust Stability, and Quadratic Stability

    Page(s): 2811 - 2816
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (699 KB) |  | HTML iconHTML  

    This technical note addresses the equivalent relationship between notions of generalized performance, robust stability, and quadratic stability for the feedback connection , where is the transfer matrix of a nominal system and describes the set of uncertainty. By defining the three notions in a more general setting, the conventional equivalent relationship between robust stability and quadratic stability with respect to the norm-bound uncertainty (respectively, the positive real uncertainty) and the corresponding performance (respectively, the extended strict positive realness) has been proved only special case of the results derived in the technical note. A version of the Kalman-Yakubovich-Popov lemma, which plays a crucial role in establishing the equivalence between the generalized performance and the quadratic stability, is also presented. View full abstract»

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  • NGMV Control of Delayed Piecewise Affine Systems

    Page(s): 2817 - 2821
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (347 KB) |  | HTML iconHTML  

    A Nonlinear Generalized Minimum Variance (NGMV) control algorithm is introduced for the control of piecewise affine (PWA) systems. Under some conditions, discrete-time PWA systems can be transferred into an equivalent state-dependent nonlinear system form. The equivalent state-dependent systems maintain the hybrid nature of the original PWA systems and include both the discrete and continuous signals in one general description. In a more general way, the process is assumed to include common delays in input or output channels of magnitude . Then the NGMV control strategy can be applied. The NGMV controller is related to a well-known and accepted solution for time delay systems (Smith Predictor) but has the advantage that it may stabilize open-loop unstable processes. View full abstract»

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  • Global Regulation of a Class of Uncertain Nonlinear Systems by Switching Adaptive Controller

    Page(s): 2822 - 2827
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (276 KB) |  | HTML iconHTML  

    There are several results on the stabilization or regulation of nonlinear systems with either triangular or feedforward nonlinearity. However, the existing results are applicable to their considered systems when the nonlinearity structure is known a priori. In this technical note, we propose a switching adaptive controller which tunes the dynamic gain depending on the nonlinearity structure. Thus, as a benefit over the existing results, the structural information on the nonlinearity is not needed. Although the linear growth condition is assumed, the rate of growth is unknown and arbitrary large with our control scheme. View full abstract»

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  • A Class of Bounded Distributed Control Strategies for Connectivity Preservation in Multi-Agent Systems

    Page(s): 2828 - 2833
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (358 KB) |  | HTML iconHTML  

    This technical note proposes a general class of distributed potential-based control laws with the connectivity preserving property for single-integrator agents. The potential functions are designed in such a way that when an edge in the information flow graph is about to lose connectivity, the gradient of the potential function lies in the direction of that edge, aiming to shrink it. The results are developed for a static information flow graph first, and then are extended to the case of dynamic edge addition. Connectivity preservation for problems involving static leaders is covered as well. The potential functions are chosen to be smooth, resulting in bounded control inputs. Other constraints may also be imposed on the potential functions to satisfy various design criteria such as consensus, containment, and formation convergence. The effectiveness of the proposed control strategy is illustrated by simulation for examples of consensus and containment. View full abstract»

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  • Formal Analysis of Discrete-Time Piecewise Affine Systems

    Page(s): 2834 - 2840
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (506 KB) |  | HTML iconHTML  

    In this technical note, we study temporal logic properties of trajectories of discrete-time piecewise affine (PWA) systems. Specifically, given a PWA system and a linear temporal logic formula over regions in its state space, we attempt to find the largest region of initial states from which all trajectories of the system satisfy the formula. Our method is based on the iterative computation and model checking of finite quotients. We illustrate our method by analyzing PWA models of two synthetic gene networks. View full abstract»

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  • Further Results on the Use of Nussbaum Gains in Adaptive Neural Network Control

    Page(s): 2841 - 2846
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (349 KB) |  | HTML iconHTML  

    In this note, the use of Nussbaum gains for adaptive neural network (NN) control is examined. Extending previous approaches that have been successfully applied to prove the forward completeness property (boundedness up to finite time), we address the boundedness for all time (up to infinity) problem. An example is constructed showing that this is not possible in general with the existing theoretical tools. To achieve boundedness for all time, a novel hysteresis-based deadzone scheme with resetting is introduced for the associated update laws. In this way, a unique, piecewise continuously differentiable solution is obtained while the error converges in finite time within some arbitrarily small region of the origin. Using the proposed modification, an adaptive NN tracking controller is designed for a class of multiple-input multiple-output nonlinear systems. View full abstract»

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  • Stochastic Stabilization of Noisy Linear Systems With Fixed-Rate Limited Feedback

    Page(s): 2847 - 2853
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (340 KB) |  | HTML iconHTML  

    Fixed-rate quantizers whose bin levels are adaptive have been used in the networked control literature as efficient schemes for stabilizing open-loop unstable noise-free linear systems with arbitrary initial conditions connected over noiseless channels. In this note, stochastic stability results for such simple adaptive quantizers when the system noise has unbounded support for its probability measure are presented. It is shown that, there exists a unique invariant distribution for the state and the quantizer parameters under mild conditions. The second moment under the invariant distribution is finite, if the system noise is Gaussian. View full abstract»

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  • On Uncontrollable Discrete-Time Bilinear Systems Which are “Nearly” Controllable

    Page(s): 2853 - 2858
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (211 KB) |  | HTML iconHTML  

    In this note, for a class of uncontrollable discrete-time bilinear systems, it is shown that the controllable region “nearly” covers the whole space while the uncontrollable region is only a hypersurface. As a result, for almost any initial state and any terminal state of the system, the former can be transferred to the latter. In addition, the two-dimensional controllability counterexamples in are generalized to arbitrary finite-dimensional cases. View full abstract»

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  • Stochastic Optimization on Continuous Domains With Finite-Time Guarantees by Markov Chain Monte Carlo Methods

    Page(s): 2858 - 2863
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (381 KB) |  | HTML iconHTML  

    We introduce bounds on the finite-time performance of Markov chain Monte Carlo (MCMC) algorithms in solving global stochastic optimization problems defined over continuous domains. It is shown that MCMC algorithms with finite-time guarantees can be developed with a proper choice of the target distribution and by studying their convergence in total variation norm. This work is inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory. View full abstract»

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  • A Unified Lyapunov Approach to Analysis of Oscillations and Stability for Systems With Piecewise Linear Elements

    Page(s): 2864 - 2869
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (456 KB) |  | HTML iconHTML  

    This technical note develops a unified Lyapunov approach to analysis of self-induced oscillations and stability for systems with piecewise linear elements. For self-induced oscillation within a global or regional attractor, invariant level sets of a piecewise quadratic Lyapunov function are obtained to bound the attractor via linear matrix inequality based optimization. The analysis results for self-induced oscillations are easily adapted to global or regional stability analysis. View full abstract»

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  • The Design of Multi-Lead-Compensators for Stabilization and Pole Placement in Double-Integrator Networks

    Page(s): 2870 - 2875
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (181 KB) |  | HTML iconHTML  

    We study decentralized controller design for stabilization and pole-placement, in a network of autonomous agents with double-integrator internal dynamics and arbitrary observation topology. We show that a simple multi-lead-compensator architecture, in particular one in which each agent uses a derivative-approximation compensator with three memory elements, can achieve both stabilization and effective pole placement while subdividing complexity/actuation among the agents. Through a scaling argument, we also demonstrate that the multi-lead-compensator can stabilize the double-integrator network under actuator saturation constraints. View full abstract»

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Aims & Scope

In the IEEE Transactions on Automatic Control, the IEEE Control Systems Society publishes high-quality papers on the theory, design, and applications of control engineering.  Two types of contributions are regularly considered

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Meet Our Editors

Editor-in-Chief
P. J. Antsaklis
Dept. Electrical Engineering
University of Notre Dame