Showing papers in "Automatica in 2004"

TL;DR: A new approach to robust sampled- data control is introduced, modelled as a continuous-time one, where the control input has a piecewise-continuous delay, and sufficient linear matrix inequalities conditions for sampled-data state-feedback stabilization of such systems are derived via descriptor approach to time-delay systems.

TL;DR: Some new delay-dependent stability criteria are devised by taking the relationship between the terms in the Leibniz-Newton formula into account, which are less conservative than existing ones.

TL;DR: This paper presents the stabilization analysis for a class of nonlinear systems that are represented by a Takagi and Sugeno (TS) discrete fuzzy model using new control laws and new nonquadratic Lyapunov functions.

TL;DR: A general multi-sensor optimal information fusion decentralized Kalman filter with a two-layer fusion structure is given for discrete time linear stochastic control systems with multiple sensors and correlated noises.

TL;DR: The proposed algorithm for nonlinear receding horizon control is applied to a two-link arm whose dynamics is highly nonlinear and is shown to be bounded under some conditions.

TL;DR: A form of feedback model predictive control that overcomes disadvantages of conventional MPC but which has manageable computational complexity is presented.

TL;DR: A robust adaptive control scheme is developed without constructing the dead-zone inverse, which ensures global stability of the adaptive system and achieves desired tracking precision.

TL;DR: A novel dynamic model is proposed for the hysteresis in magnetostrictive actuators by coupling a Preisach operator to an ordinary differential equation, and a parameter identification method is described.

TL;DR: Decentralized overlapping feedback laws are designed for a formation of unmanned aerial vehicles based on the application of convex optimization tools involving linear matrix inequalities to robustly stabilize the perturbed nominal dynamics of the subsystem.

TL;DR: A delay-dependent bounded real lemma for systems with a state- Delay-dependent condition for the existence of robust H"~ control is presented in terms of nonlinear matrix inequalities, and an iterative algorithm involving convex optimization is proposed.

TL;DR: This paper provides algorithms based on mixed-integer linear or quadratic programming which are guaranteed to converge to a global optimum of hybrid dynamical systems, and suggests a way of trading off between optimality and complexity by using a change detection approach.

TL;DR: The proposed control schemes are based upon the use of a proportional-derivative feedback structure, for which an iterative term is added to cope with the unknown parameters and disturbances, for trajectory tracking of rigid robot manipulators, with unknown parameters, performing repetitive tasks.

TL;DR: An efficient and flexible parameter estimation scheme for grey-box models in the sense of discretely, partially observed Ito stochastic differential equations with measurement noise is presented along with a corresponding software implementation that provides more accurate and more consistent estimates of the parameters of the diffusion term.

TL;DR: Simple but powerful criteria of stability are presented for both continuous-time and discrete-time systems and using these criteria, stability can be checked in a closed loop Bode plot, making it easy to design the system for robustness.

TL;DR: In this paper, the robust H"2 and H"~ filtering problem for linear discrete-time systems with polytopic parameter uncertainty was studied and a matrix inequality condition was proposed to provide additional free parameters as compared to existing characterizations.

TL;DR: It is shown that if the controller is designed without taking into account the network so that it yields input-to-state stability (ISS) with respect to external disturbances, then the same controller will achieve semi-global practical ISS for the NCS when implemented via the network with a Lyapunov UGAS protocol.

TL;DR: A robust recursive design technique is developed for uncertain nonlinear plants in vectorial strict feedback form that bridges the geometric design with the speed assignment.

TL;DR: This paper considers more general reset structures than previously considered, allowing for higher-order controllers and partial-state resetting, and gives a testable necessary and sufficient condition for quadratic stability and links it to both uniform bounded-input bounded-state stability and steady-state performance.

TL;DR: It is shown that the parameter estimation error consistently converges to zero under generalized or weak persistent excitation conditions and unbounded noise variance, and that the output estimates uniformly converge to the true outputs.

TL;DR: This paper establishes a link between reachability, viability and invariance problems and viscosity solutions of a special form of the Hamilton-Jacobi equation to address optimal control problems where the cost function is the minimum of a function of the state over a specified horizon.

TL;DR: Interestingly, it is shown in this paper that the developed control strategy is easily extendible to situations of practical importance such as parking and point-to-point navigation.

TL;DR: This paper investigates the almost surely asymptotic stability for the nonlinear stochastic differential delay equations with Markovian switching and some sufficient criteria on the controllability and robust stability are established for linear stochastically differential delay equation with MarkOVian switching.

TL;DR: The main contributions of this work are to utilize HOS tools such as cumulants, bispectrum and bicoherence to develop two new indices: the non-Gaussianity index (NGI) and the nonlinearity index(NLI) for detecting and quantifying non- Gaussianity and non linearity that may be present in regulated systems.

TL;DR: An optimal interval estimate of the regression function is obtained, providing its uncertainty range for any assigned regressor values, and the set estimate allows to derive an optimal identification algorithm, giving estimates with minimal guaranteed L"p error on the assigned domain of the regressors.

TL;DR: Analytical optimal or suboptimal solutions of the basic problems involved in parameter or state estimation are presented and are counterparts in this context of uncertain models to classical approximations of the sum and intersection of ellipsoids.

TL;DR: This paper addresses the problem of estimating simultaneously the state and input of a class of nonlinear systems and concludes that upon satisfying some conditions, the observer design problem can be solved via a Riccati inequality or a LMI-based technique with asymptotic estimation guaranteed.

TL;DR: An algorithm for the construction of an explicit piecewise linear state feedback approximation to nonlinear constrained receding horizon control that allows such controllers to be implemented via an efficient binary tree search, avoiding real-time optimization.

TL;DR: An unremovable spectral theorem and a stochastic Popov-Belevith-Hautus Criterion for exact observability and a comparison theorem for stochastically algebraic Riccati equations and a result on Lyapunov-type equations are obtained.

TL;DR: This paper studies the switching control of linear parameter-varying (LPV) systems using multiple parameter-dependent Lyapunov functions to improve performance and enhance control design flexibility.

TL;DR: An overview of the existing work and the needed future developments is presented and the use of discrete maps in studying the stability of the closed orbits that represent the dynamics of a biped, which can be characterized as a hybrid system.