Robust control for nonlinear uncertain systems has been solved for matched uncertainty but has not been completely solved yet for unmatched uncertainty. This paper developed a new method in which an adaptive radial basis function neural network is used to compensate for the effects of unmatched uncertainty in the framework of integral sliding mode control. The stability of the whole system is g...

Output feedback sliding mode control has received great research interests, due to it does not require full accessibility of states and increases the ability of practical implementation of sliding mode control. In this paper, a new approach of chattering-free OFSMC design is proposed by incorporating integral sign function control for general multi-input multi-output linear uncertain systems. C...

In this paper, we develop two new model reference adaptive control (MRAC) schemes for a class of nonlinear dynamic systems that is robust with respect to an uncertain state (output) dependent nonlinear perturbations and/or external disturbances with unknown bounds. The design is based on a controller parametrization with an adaptive integral action. Two types of adaptive controllers are conside...

I n severe and fatal asthma dramatic changes in airway structure have been described, collectively referred to as remodelling [1, 2]. Current dogma dictates that remodelling reflects aberrant repair in response to ongoing inflammation and injury. However, the interplay between inflammation and remodelling, and, more importantly, between airway structure and function remains elusive, such that w...

This article deals with a method to describe and manage spatial knowledge. Each georeferenced data is considered as an information source, whose location and value are independently described. The method proposed in this paper uses the information sources to infer the value of any request zone . This method is able to treat imprecise or uncertain, qualitative and quantitative data. It can be ap...

In this paper the robust stability of an autonomous mobile robot based on a parametric approach is presented. The closed-loop control consists of Multi-Input / MultiOutput (MIMO) uncertain plant (mobile robot) and a MIMO Proportional Integral (PI) controller. Using Kharitonov’s Theorem and Zero Exclusion Condition the closed-loop system is proved to be robustly stable in the presence of paramet...

Copositive linear Lyapunov functions are used along with dissipativity theory for stability analysis and control of uncertain linear positive systems. Unlike usual results on linear systems, linear supply-rates are employed here for robustness and performance analysis using L1and L∞-gains. Robust stability analysis is performed using Integral Linear Constraints (ILCs) for which several classes ...

The problem of optimal HI disturbance rejection while tracking uncertain constant or sinusoidal reference commands is considered. The internal model principle is used to ensure that the tracking error approaches zero asymptotically. Necessary conditions are given for controllers that minimize an HI disturbance rejection cost plus a worst-case integral square tracking error for transient trackin...

In this paper we look at the Line Integral Convolution method for flow visualization and ways in which this can be applied to the visualization of two dimensional, steady flow fields in the presence of uncertainty. To achieve this, we start by studying the method and reviewing the history of modifications other authors have made to it in order to improve its efficiency or capabilities, and usin...

The theory of integral quadratic constraints (IQCs) allows verification of stability and gain-bound properties of systems containing nonlinear or uncertain elements. Gain bounds often imply exponential stability, but it can be challenging to compute useful numerical bounds on the exponential decay rate. This work presents a generalization of the classical IQC results of Megretski and Rantzer [1...