Showing papers in "Automatica in 1998"

TL;DR: In this paper, an order of the maximal differentiation error to the square root of the maximum deviation of the measured input signal from the base signal from Lipschitz's constant of the derivative was proposed.

TL;DR: These results may be viewed as generalizing the classical Krasovskii theorem, and, more loosely, linear eigenvalue analysis, and the approach is illustrated by controller and observer designs for simple physical examples.

TL;DR: It is proved that feasibility of the open-loop optimal control problem at time t = 0 implies asymptotic stability of the closed-loop system.

TL;DR: In this article, a new scheme based on stochastic control theory and a separation property is shown to hold for the optimal controller for real-time systems subject to random time delays in the communication network is presented.

TL;DR: A modified adaptive backstepping design procedure is proposed for a class of nonlinear systems with three types of uncertainty: (i)unknown parameters; (ii)uncertain nonlinearities and (iii)unmodeled dynamics.

TL;DR: Estimators are obtained which, using only a measured output, can asymptotically estimate to any desired accuracy the system state and the input.

TL;DR: The static output feedback stabilization problem is addressed using the linear matrix inequality technique and an iterative LMI (ILMI) algorithm is proposed to compute the feedback gain.

TL;DR: In this article, an optimal two-stage identification algorithm is presented for Hammerstein-Wiener systems, where two static nonlinear elements surround a linear block, and the algorithm is shown to be convergent in the absence of noise and convergent with probability one in the presence of white noise.

TL;DR: The design is based on optimization of load disturbance rejection with constraints on sensitivity and weighting of set point response, leading to a non-convex optimization problem.

TL;DR: The proposed scheme simplifies significantly the controller designs given in Venkataraman and Gulati (1989) and Man et al. (1994) by reducing tracking error in the steady state and reduced control efforts in the transient state.

TL;DR: The results indicate that the proposed scheme is indeed very effective in achieving the closed-loop system integrity in the presence of actuator failures.

TL;DR: A means of extending the results to state-space models and showing that improved numerical conditioning can be obtained for many stable-predictive control strategies is developed.

TL;DR: Both the key principles and real application examples of a unified theory which allows us to perform the on-board incipient fault detection and isolation tasks involved in monitoring for condition-based maintenance are described.

TL;DR: The original dynamic compensator can be modified, while retaining those dynamic features that produce a desirable closed-loop steady-state response, to ensure that the requisite invariant subspace exists and it is reasonably tuned for input saturation.

TL;DR: The proposed controller is applied to a precise-positioning problem in the presence of nonlinearly parametrized friction dynamics and leads to position errors and friction compensation that are orders of magnitude better than those based on estimation of linear parametrizations.

TL;DR: A systematic and simple approach to the design of schemes for input reconstruction is developed based on a matrix pencil decomposition form which is obtainable using numerically stable orthogonal transformations.

TL;DR: It is proved that the proposed observer based on a slight modification of the extended Kalman filter is an exponential observer and is applied to the highly nonlinear flux and angular velocity estimation problem for induction machines.

TL;DR: This paper traces the development of many ideas from these formulae, covering linear H"2 and H"~ control, identification, adaptive control and nonlinear systems.

TL;DR: An optimal strategy for the so-called model-based approach is proposed, based on an H"~ optimisation framework, which has been found to give good results on numerical examples taken from the literature.

TL;DR: The tracking error bound is proven to be a class-K function of the bounds of reinitialization errors, uncer- tainties and disturbances to the systems, and the time delays in the system states do not play a significant role in the ILC convergence property.

TL;DR: Simulation results on a microbial growth process are provided, which illustrate the relevance of the proposed FDI method.

TL;DR: A scheduled low-and-high-gain design technique is developed to solve several central control problems for linear systems with saturating actuators where the actuator limitations have to be incorporated a priori into control design.

TL;DR: In this paper, the authors propose a global theoretical framework for the analysis of bioreactor dynamics, which uses technical tools issued from the nonlinear systems theory, which allow the design of observer-based estimators.

TL;DR: An improved adaptation law on the upper bound of uncertainties is proposed to guarantee the boundednenss of both states of the plant and the estimated control gains when the boundary layer technique is employed.

TL;DR: A new stabilizing receding horizon control, based on a finite input and state horizon cost with a finite terminal weighting matrix, is proposed for time-varying discrete linear systems with constraints.

TL;DR: To make a nonlinear system with factorisable high-frequency gain matrix exponentially passive via either state or output feedback, exponential minimum phaseness and invertibility conditions are necessary and sufficient and these conditions also guarantee exponential output feedback stabilisability.

TL;DR: The main result is a recursive scheme for constructing an ellipsoidal state estimation set of all states consistent with the measured output and the given noise and uncertainty description.

TL;DR: The consistency of a large class of methods for estimating the extended observability matrix is analyzed and persistence of excitation conditions on the input signal are given which guarantee consistent estimates for systems with only measurement noise.

TL;DR: It is shown that the system outputs, states and control inputs can be guaranteed to converge to desired trajectories in the absence of state, output disturbances and repeatability uncertainty.

TL;DR: A method based on conceptual tools of predictive control is described for tackling tracking problems of uncertain linear systems wherein pointwise-in-time input and/or state inequality constraints are present.