Showing papers in "Automatica in 2006"

TL;DR: It is proved that, with the proposed control scheme, each agent can follow the leader if the (acceleration) input of the active leader is known, and the tracking error is estimated if the input ofThe leader is unknown.

TL;DR: This survey addresses the subject of bilateral teleoperation, a research stream with more than 50 years of history and one that continues to be a fertile ground for theoretical exploration and many applications.

TL;DR: The normalized and signed gradient dynamical systems associated with a differentiable function are characterized and their asymptotic convergence properties are identified and conditions that guarantee finite-time convergence are identified.

TL;DR: Sufficient conditions for exponential stability and weighted L"2-gain are developed for a class of switching signals with average dwell time and these conditions are given in the form of linear matrix inequalities (LMIs).

TL;DR: This work generates distributed optimal control problems for each subsystem and establishes that a distributed receding horizon control implementation is stabilizing to a neighborhood of the objective state.

TL;DR: It is shown that the class of admissible affine state feedback control policies with knowledge of prior states is equivalent to the classOf admissible feedback policies that are affine functions of the past disturbance sequence, which implies that a broad class of constrained finite horizon robust and optimal control problems can be solved in a computationally efficient fashion using convex optimization methods.

TL;DR: The objective here is to mean-square (m.s.) stabilize the system while minimizing a quadratic performance criterion when the information flow between the controller and the plant is disrupted due to link failures, or packet losses.

TL;DR: This paper shows semi-global practical stability of the closed-loop system with respect to the design parameters, and shows that reducing the size of the parameters typically slows down the convergence rate of the extremum seeking controllers and enlarges the domain of the attraction.

TL;DR: A stochastic sensor selection strategy that is easy to implement and is computationally tractable is described that is applied to the sensor coverage problem and the sensor selection problem, which has multiple sensors that cannot operate simultaneously.

TL;DR: This work proposes motion coordination algorithms that steer the mobile sensor network to an optimal deployment and that are amenable to a decentralized implementation and illustrates how the proposed algorithms lead to improved performance of an extended Kalman filter in a target-tracking scenario.

TL;DR: This paper provides a solution to the problem of robust output feedback model predictive control of constrained, linear, discrete-time systems in the presence of bounded state and output disturbances by combining a simple, stable Luenberger state estimator and a recently developed, robustly stabilizing, tube-based, model predictive controller.

TL;DR: It is proved that under certain conditions, the estimation error of the modified unscented Kalman filter remains bounded, and the Cramer-Rao lower bound (CRLB) is introduced as a performance measure.

TL;DR: The assumption that the state is available for feedback is removed and the output feedback problem is investigated, and a sufficient condition for the design of a dynamic output feedback controller which makes the closed loop system finite-time stable is provided.

TL;DR: In this article, an adaptive neural control of a completely non-affine pure-feedback system using RBF neural networks is presented by combining adaptive neural design with the backstepping method, input-to-state stability (ISS) analysis and the small-gain theorem.

TL;DR: Using the notion of a hybrid time domain and general results on set and graphical convergence, it is established under weak regularity and local boundedness assumptions that the set of solutions is sequentially compact and ''upper semicontinuous'' with respect to initial conditions and system perturbations.

TL;DR: This paper presents a new method (constrained ALS) to estimate the variances of the disturbances entering the process using routine operating data and guarantees positive semidefinite covariance estimates by adding constraints to the ALS problem.

TL;DR: A method for exponentially stabilizing a NCS is proposed by first identifying a pair of communication sequences that preserve reachability and observability and then designing an observer-based feedback controller based on those sequences.

TL;DR: In this paper, a new structure of slack variables is introduced to provide extra free dimensions in the solution space for the robust H"2 and H"~ optimization, which directly leads to performance improvement and reduction of conservativeness in the filtering solution.

TL;DR: A new stabilization conclusion is presented that is a generalization of some previous results in the literature that is suitable for a PDC law, which presents to be more relaxed than some existing results.

TL;DR: A navigation functions' based methodology, established in this work for centralized multiple robot navigation, is extended to address the problem of decentralized navigation, where each agent plans its actions without knowing the destinations of the other agents.

TL;DR: The purpose of this paper is to provide an accessible and self-contained review of stability analysis of switched systems, emphasizing the intuitive and geometric underlying ideas.

TL;DR: This paper explicitly construct a universal-type adaptive output feedback controller which globally regulates all the states of the uncertain systems without knowing the growth rate.

TL;DR: A stability criterion is derived by introducing some relaxation matrices that can be used to reduce the conservatism of the criteria, based on the Lyapunov-Krasovskii functional approach.

TL;DR: The uniform stability of discrete-time switched linear systems, possibly with a strongly connected switching path constraint, and the existence of finite-path-dependent dynamic output feedback controllers uniformly stabilizing such a system are both shown to be characterized by the existance of a finite-dimensional feasible system of linear matrix inequalities.

TL;DR: A delay-dependent condition for the existence of a state feedback controller, which ensures asymptotic stability and a prescribed H"~ performance level of the closed-loop system for all admissible uncertainties, is proposed in terms of a matrix inequality.

TL;DR: The concept of topological to the case of uncertain dynamical systems is extended to address problems of observability and optimal control via limited capacity digital communication channels and topological entropy is calculated.

TL;DR: This work shows that a ''secant'' criterion for local stability, derived earlier in the literature, is in fact a necessary and sufficient condition for diagonal stability of the corresponding class of matrices, and recovers the same stability condition using the authors' diagonal stability result as a tool for constructing a Lyapunov function.

TL;DR: An effective numerical algorithm for testing the BIBO stability of fractional delay systems described by fractional-order delay-differential equations based on using Cauchy's integral theorem and solving an initial-value problem is presented.

TL;DR: A method for designing a global robust adaptive controller that forces an underactuated ship to follow a reference path under both constant and time-varying disturbances induced by waves, wind and ocean-currents is proposed.

TL;DR: Methods for model validation of continuous-time nonlinear systems with uncertain parameters are presented, which employ functions of state-parameter-time whose existence proves that a model and a feasible parameter set are inconsistent with some time-domain experimental data.