By Topic

Automatic Control, IEEE Transactions on

Issue 6 • Date June 2012

Filter Results

Displaying Results 1 - 25 of 37
  • Table of contents

    Publication Year: 2012 , Page(s): C1 - C4
    Save to Project icon | Request Permissions | PDF file iconPDF (42 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Automatic Control publication information

    Publication Year: 2012 , Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (38 KB)  
    Freely Available from IEEE
  • Scanning the issue

    Publication Year: 2012 , Page(s): 1345 - 1346
    Save to Project icon | Request Permissions | PDF file iconPDF (39 KB)  
    Freely Available from IEEE
  • Identification of Fault Estimation Filter From I/O Data for Systems With Stable Inversion

    Publication Year: 2012 , Page(s): 1347 - 1361
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1022 KB) |  | HTML iconHTML  

    Classical methods for estimating additive faults are based on state-space models, e.g., moving horizon estimation (MHE) and unknown input observers (UIOs). This paper contributes new direct design methods from closed-loop I/O data for systems with stable inversion, which do not require building a state-space model by first principles, nor require identifying it. Inspired by subspace identification, we use the input and output (I/O) relationship of a plant in a Vector ARX (VARX) form to parameterize least-squares (LS) problems for estimating faults. We prove that with the order of the VARX descriptions tending to infinity, the fault estimates are unbiased. Under lower relative degrees, we prove that our new methods are equivalent to system-inversion-based estimation for both LTI and LTV systems. We will show more general unbiased estimation conditions for higher relative degrees. These require that the underlying inverted system from faults to outputs is stable. Algorithms of identifying unbiased fault estimation filters from data will be developed in this paper based on single LS. Moreover, covariance of the fault estimates can also be extracted from data. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Output-Based Event-Triggered Control With Guaranteed {cal L}_{\infty } -Gain and Improved and Decentralized Event-Triggering

    Publication Year: 2012 , Page(s): 1362 - 1376
    Cited by:  Papers (37)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (919 KB) |  | HTML iconHTML  

    Most event-triggered controllers available nowadays are based on static state-feedback controllers. As in many control applications full state measurements are not available for feedback, it is the objective of this paper to propose event-triggered dynamical output-based controllers. The fact that the controller is based on output feedback instead of state feedback does not allow for straightforward extensions of existing event-triggering mechanisms if a minimum time between two subsequent events has to be guaranteed. Furthermore, since sensor and actuator nodes can be physically distributed, centralized event-triggering mechanisms are often prohibitive and, therefore, we will propose a decentralized event-triggering mechanism. This event-triggering mechanism invokes transmission of the outputs in a node when the difference between the current values of the outputs in the node and their previously transmitted values becomes “large” compared to the current values and an additional threshold. For such event-triggering mechanisms, we will study closed-loop stability and L-performance and provide bounds on the minimum time between two subsequent events generated by each node, the so-called inter-event time of a node. This enables us to make tradeoffs between closed-loop performance on the one hand and communication load on the other hand, or even between the communication load of individual nodes. In addition, we will model the event-triggered control system using an impulsive model, which truly describes the behavior of the event-triggered control system. As a result, we will be able to guarantee stability and performance for event-triggered controllers with larger minimum inter-event times than the existing results in the literature. We illustrate the developed theory using three numerical examples. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Combining Convex–Concave Decompositions and Linearization Approaches for Solving BMIs, With Application to Static Output Feedback

    Publication Year: 2012 , Page(s): 1377 - 1390
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1028 KB) |  | HTML iconHTML  

    A novel optimization method is proposed to minimize a convex function subject to bilinear matrix inequality (BMI) constraints. The key idea is to decompose the bilinear mapping as a difference between two positive semidefinite convex mappings. At each iteration of the algorithm the concave part is linearized, leading to a convex subproblem. Applications to various output feedback controller synthesis problems are presented. In these applications, the subproblem in each iteration step can be turned into a convex optimization problem with linear matrix inequality (LMI) constraints. The performance of the algorithm has been benchmarked on the data from the COMPleib library. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Computational Complexity Certification for Real-Time MPC With Input Constraints Based on the Fast Gradient Method

    Publication Year: 2012 , Page(s): 1391 - 1403
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (885 KB) |  | HTML iconHTML  

    This paper proposes to use Nesterov's fast gradient method for the solution of linear quadratic model predictive control (MPC) problems with input constraints. The main focus is on the method's a priori computational complexity certification which consists of deriving lower iteration bounds such that a solution of pre-specified suboptimality is obtained for any possible state of the system. We investigate cold- and warm-starting strategies and provide an easily computable lower iteration bound for cold-starting and an asymptotic characterization of the bounds for warm-starting. Moreover, we characterize the set of MPC problems for which small iteration bounds and thus short solution times are expected. The theoretical findings and the practical relevance of the obtained lower iteration bounds are underpinned by various numerical examples and compared to certification results for a primal-dual interior point method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive Information Collection by Robotic Sensor Networks for Spatial Estimation

    Publication Year: 2012 , Page(s): 1404 - 1419
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1168 KB) |  | HTML iconHTML  

    This work deals with trajectory optimization for a robotic sensor network sampling a spatio-temporal random field. We examine the optimal sampling problem of minimizing the maximum predictive variance of the estimator over the space of network trajectories. This is a high-dimensional, multi-modal, nonsmooth optimization problem, known to be NP-hard even for static fields and discrete design spaces. Under an asymptotic regime of near-independence between distinct sample locations, we show that the solutions to a novel generalized disk-covering problem are solutions to the optimal sampling problem. This result effectively transforms the search for the optimal trajectories into a geometric optimization problem. Constrained versions of the latter are also of interest as they can accommodate trajectories that satisfy a maximum velocity restriction on the robots. We characterize the solution for the unconstrained and constrained versions of the geometric optimization problem as generalized multicircumcenter trajectories, and provide algorithms which enable the network to find them in a distributed fashion. Several simulations illustrate our results. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stability of a Class of Linear Switching Systems with Applications to Two Consensus Problems

    Publication Year: 2012 , Page(s): 1420 - 1430
    Cited by:  Papers (24)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (721 KB) |  | HTML iconHTML  

    In this paper, we first establish a stability result for a class of linear switched systems involving Kronecker product. The problem is interesting in that the system matrix does not have to be Hurwitz at any time instant. This class of linear switched systems arises in the control of multi-agent systems under switching network topology. As applications of this stability result, we give the solvability conditions for both the leaderless consensus problem and the leader-following consensus problem for general marginally stable linear multi-agent systems under switching network topology. In contrast with some existing results, our results only assume that the dynamic graph is uniformly connected. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Quantized H_{\infty } Control for Nonlinear Stochastic Time-Delay Systems With Missing Measurements

    Publication Year: 2012 , Page(s): 1431 - 1444
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (807 KB) |  | HTML iconHTML  

    In this paper, the quantized H control problem is investigated for a class of nonlinear stochastic time-delay network-based systems with probabilistic data missing. A nonlinear stochastic system with state delays is employed to model the networked control systems where the measured output and the input signals are quantized by two logarithmic quantizers, respectively. Moreover, the data missing phenomena are modeled by introducing a diagonal matrix composed of Bernoulli distributed stochastic variables taking values of 1 and 0, which describes that the data from different sensors may be lost with different missing probabilities. Subsequently, a sufficient condition is first derived in virtue of the method of sector-bounded uncertainties, which guarantees that the closed-loop system is stochastically stable and the controlled output satisfies H performance constraint for all nonzero exogenous disturbances under the zero-initial condition. Then, the sufficient condition is decoupled into some inequalities for the convenience of practical verification. Based on that, quantized H controllers are designed successfully for some special classes of nonlinear stochastic time-delay systems by using Matlab linear matrix inequality toolbox. Finally, a numerical simulation example is exploited to show the effectiveness and applicability of the results derived. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Verification of Bounded Discrete Horizon Hybrid Automata

    Publication Year: 2012 , Page(s): 1445 - 1455
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (278 KB) |  | HTML iconHTML  

    We consider the class of o-minimally definable hybrid automata with a bounded discrete-transition horizon. We show that for every hybrid automata in this class, there exists a bisimulation of finite index, and that the bisimulation quotient can be effectively constructed when the underlying o-minimal theory is decidable. More importantly, we give natural specifications for hybrid automata which ensure the boundedness of discrete-transition horizons. In addition, we show that these specifications are reasonably tight with respect to the decidability of the models and that they can model modern day real-time and embedded systems. As a result, the analysis of several problems for these systems admit effective algorithms. We provide a representative example of a hybrid automaton in this class. Unlike previously examined subclasses of o-minimally defined hybrid automata with decidable verification properties and extended o-minimal hybrid automata, we do not impose re-initialization of the continuous variables in a memoryless fashion when a discrete transition is taken. Our class of hybrid systems has both rich continuous dynamics and strong discrete-continuous coupling, showing that it is not necessary to either simplify the continuous dynamics or restrict the discrete dynamics to achieve decidability. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Inner Approximations for Polynomial Matrix Inequalities and Robust Stability Regions

    Publication Year: 2012 , Page(s): 1456 - 1467
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1722 KB) |  | HTML iconHTML  

    Following a polynomial approach, many robust fixed-order controller design problems can be formulated as optimization problems whose set of feasible solutions is modeled by parametrized polynomial matrix inequalities (PMIs). These feasibility sets are typically nonconvex. Given a parametrized PMI set, we provide a hierarchy of linear matrix inequality (LMI) problems whose optimal solutions generate inner approximations modeled by a single polynomial superlevel set. Those inner approximations converge in a well-defined analytic sense to the nonconvex original feasible set, with asymptotically vanishing conservatism. One may also impose the hierarchy of inner approximations to be nested or convex. In the latter case, they do not converge any more to the feasible set, but they can be used in a convex optimization framework at the price of some conservatism. Finally, we show that the specific geometry of nonconvex polynomial stability regions can be exploited to improve convergence of the hierarchy of inner approximations. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stabilizing Model Predictive Control of Stochastic Constrained Linear Systems

    Publication Year: 2012 , Page(s): 1468 - 1480
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (823 KB) |  | HTML iconHTML  

    This paper investigates stochastic stabilization procedures based on quadratic and piecewise linear Lyapunov functions for discrete-time linear systems affected by multiplicative disturbances and subject to linear constraints on inputs and states. A stochastic model predictive control (SMPC) design approach is proposed to optimize closed-loop performance while enforcing constraints. Conditions for stochastic convergence and robust constraints fulfillment of the closed-loop system are enforced by solving linear matrix inequality problems off line. Performance is optimized on line using multistage stochastic optimization based on enumeration of scenarios, that amounts to solving a quadratic program subject to either quadratic or linear constraints. In the latter case, an explicit form is computable to ease the implementation of the proposed SMPC law. The approach can deal with a very general class of stochastic disturbance processes with discrete probability distribution. The effectiveness of the proposed SMPC formulation is shown on a numerical example and compared to traditional MPC schemes. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Recursive Update Filtering for Nonlinear Estimation

    Publication Year: 2012 , Page(s): 1481 - 1490
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (585 KB) |  | HTML iconHTML  

    Nonlinear filters are often very computationally expensive and usually not suitable for real-time applications. Real-time navigation algorithms are typically based on linear estimators, such as the extended Kalman filter (EKF) and, to a much lesser extent, the unscented Kalman filter. This work proposes a novel nonlinear estimator whose additional computational cost is comparable to (N-1) EKF updates, where N is the number of recursions, a tuning parameter. The higher N the less the filter relies on the linearization assumption. A second algorithm is proposed with a differential update, which is equivalent to the recursive update as N tends to infinity. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Temporal Logic Control of Discrete-Time Piecewise Affine Systems

    Publication Year: 2012 , Page(s): 1491 - 1504
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1041 KB) |  | HTML iconHTML  

    We present a computational framework for automatic synthesis of a feedback control strategy for a discrete-time piecewise affine (PWA) system from a specification given as a linear temporal logic (LTL) formula over an arbitrary set of linear predicates in the system's state variables. Our approach consists of two main steps. First, by defining appropriate partitions for its state and input spaces, we construct a finite abstraction of the PWA system in the form of a control transition system. Second, by leveraging ideas and techniques from LTL model checking and Rabin games, we develop an algorithm to generate a control strategy for the finite abstraction. While provably correct and robust to state measurements and small perturbations in the applied inputs, the overall procedure is conservative and expensive. The proposed algorithms have been implemented as a software package and made available for download. Illustrative examples are included. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • System Theoretic Aspects of Influenced Consensus: Single Input Case

    Publication Year: 2012 , Page(s): 1505 - 1511
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (261 KB) |  | HTML iconHTML  

    This technical note examines the dynamics of networked multi-agent systems operating with a consensus-type algorithm, under the influence of an attached node or external agent. Depending on the specific scenario, the attached node can be viewed as a network intruder or an administrator. We introduce an influence scheme, naive of the network topology, involving predictable excitation of the network with the objective of manipulating, disrupting, or steering its evolution. The spectrum of the corresponding Dirichlet matrix provides bounds on the system-theoretic properties of the resulting influenced network, quantifying its security-or viewed differently-its manageability. Finally, the controllability gramian for influenced consensus is examined, providing insights into its H2-norm and controllability properties. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fourier-Hermite Kalman Filter

    Publication Year: 2012 , Page(s): 1511 - 1515
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    In this note, we shall present a new class of Gaussian filters called Fourier-Hermite Kalman filters. Fourier-Hermite Kalman filters are based on expansion of nonlinear functions with the Fourier-Hermite series in same way as the traditional extended Kalman filter is based on the Taylor series. The first order truncation of the Fourier-Hermite series gives the previously known statistically linearized filter. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Decomposition Technique for Nonlinear Dynamical System Analysis

    Publication Year: 2012 , Page(s): 1516 - 1521
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (328 KB) |  | HTML iconHTML  

    A method for analyzing large-scale nonlinear dynamical systems by decomposing them into coupled lower order subsystems that are sufficiently simple for computational analysis is presented. It is shown that the decomposition approach can be used to scale the Sum of Squares programming framework for nonlinear systems analysis. The method constructs subsystem Lyapunov functions which are used to form a composite Lyapunov function for the whole system. Further computational savings are achieved if a method based on sparsity maximization is used to obtain the subsystem Lyapunov functions. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Robustness and Safe Sampling of Distributed-Delay Control Laws for Unstable Delayed Systems

    Publication Year: 2012 , Page(s): 1521 - 1526
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (263 KB) |  | HTML iconHTML  

    In the control of delayed systems by a finite spectrum assignment (FSA) , in the control law, the integral over the time delay of a function of past control appears. This assignment is in fact available for continuous delayed process independently of the stability of the latter, which is very interesting since Smith predictor is usually only used with stable processes. Nevertheless, in case of FSA control implementation, this integral control should be sampled so that spectrum assignment is not necessarily preserved and an unstable discrete closed loop can be obtained , . In this technical note, FSA integral control robustness with respect to prediction time uncertainty is analyzed for an unstable continuous linear system. A transformation approach is also proposed to understand the effects of different ways of sampling control laws. In a last part, a case study shows how Simpson approximation of integral control law leads to an unstable digital closed loop. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Supervised Switching Control Policy for LPV Systems With Inaccurate Parameter Knowledge

    Publication Year: 2012 , Page(s): 1527 - 1532
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (261 KB) |  | HTML iconHTML  

    This technical note deals with the switched supervised control of linear parameter varying systems whose parameters values are online acquirable only with an arbitrarily large degree of uncertainty. The purpose is to define a switching policy inside a family of predesigned controllers so that the switched closed-loop system result to be exponentially stable. The proposed switching logic is based on a performance-evaluation criterion which uses a measurable Lyapunov-like functional of the output. The exponential stability condition is derived imposing a sufficient long time interval over which the functional is decreasing. An interesting feature of the technical note is that no particular structure on the kind of uncertainty affecting the parameter values is assumed. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • LMI Relaxations for Reduced-Order Robust {cal H}_{\infty } Control of Continuous-Time Uncertain Linear Systems

    Publication Year: 2012 , Page(s): 1532 - 1537
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (250 KB) |  | HTML iconHTML  

    This technical note is concerned with the problem of reduced order robust H dynamic output feedback control design for uncertain continuous-time linear systems. The uncertain time-invariant parameters belong to a polytopic domain and affect all the system matrices. The search for a reduced-order controller is converted in a problem of static output feedback control design for an augmented system. To solve the problem, a two-stage linear matrix inequality (LMI) procedure is proposed. At the first step, a stabilizing state feedback scheduled controller with polynomial or rational dependence on the parameters is determined. This parameter-dependent state feedback controller is used at the second stage, which synthesizes the robust (parameter-independent) output feedback H dynamic controller. A homogeneous polynomially parameter-dependent Lyapunov function of arbitrary degree is used to assess closed-loop stability with a prescribed H attenuation level. As illustrated by numerical examples, the proposed method provides better results than other LMI based conditions from the literature. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stochastic Barbalat's Lemma and Its Applications

    Publication Year: 2012 , Page(s): 1537 - 1543
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB) |  | HTML iconHTML  

    In the deterministic case, a significant improvement on stability analysis of nonlinear systems is caused by introducing Barbalat's lemma into control area after Lyapunov's second method and LaSalle's theorem were established. This note considers the extension of Barbalat's lemma to the stochastic case. To this end, the uniform continuity and the absolute integrability are firstly described in stochastic forms. It is nevertheless a small generalization upon the existing references since our result can be used to adapted processes which are not necessarily Itô diffusions. When it is applied to Itô diffusion processes, many classical results on stochastic stability are covered as special cases. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Discrete-Time Observer Error Linearizability via Restricted Dynamic Systems

    Publication Year: 2012 , Page(s): 1543 - 1547
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB) |  | HTML iconHTML  

    In this technical note, we define the observer error linearization problem of a discrete-time autonomous nonlinear system via a restricted dynamic system. This is the dual to restricted dynamic feedback linearization in a loose sense. Necessary and sufficient conditions for this problem are obtained in terms of the index. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Robust Finite-Horizon Kalman Filtering for Uncertain Discrete-Time Systems

    Publication Year: 2012 , Page(s): 1548 - 1552
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (171 KB) |  | HTML iconHTML  

    In this note, we propose a design for a robust finite-horizon Kalman filtering for discrete-time systems suffering from uncertainties in the modeling parameters and uncertainties in the observations process (missing measurements). The system parameter uncertainties are expected in the state, output and white noise covariance matrices. We find the upper-bound on the estimation error covariance and we minimize the proposed upper-bound. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Distributed Containment Control with Multiple Dynamic Leaders for Double-Integrator Dynamics Using Only Position Measurements

    Publication Year: 2012 , Page(s): 1553 - 1559
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (317 KB) |  | HTML iconHTML  

    This note studies the distributed containment control problem for a group of autonomous vehicles modeled by double-integrator dynamics with multiple dynamic leaders. The objective is to drive the followers into the convex hull spanned by the dynamic leaders under the constraints that the velocities and the accelerations of both the leaders and the followers are not available, the leaders are neighbors of only a subset of the followers, and the followers have only local interaction. Two containment control algorithms via only position measurements of the agents are proposed. Theoretical analysis shows that the followers will move into the convex hull spanned by the dynamic leaders if the network topology among the followers is undirected, for each follower there exists at least one leader that has a directed path to the follower, and the parameters in the algorithm are properly chosen. Numerical results are provided to illustrate the theoretical results. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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

Full Aims & Scope

Meet Our Editors

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