We develop a Linear Matrix Inequality (LMI) tool for analyzing the stability and performance of adaptive controllers that employ σ−modification. The formulation involves recasting the error dynamics composed of the tracking error and the weight estimator error into a linear parameter varying form. We show how stability, convergence rate, domain of attraction, and the transient and steady state behavior of the adaptive control system can be analyzed using the developed LMI tool. It is guaranteed that less conservative estimates for the convergence rate and the size of the ultimate bound for the tracking error are obtained compared to the standard analysis in the literature
International audienceMatrix inequality based results are proposed for the design of direct adaptive...
We consider the adaptive tracking problem for a chain of integrators, where the uncertainty is stati...
International audienceMatrix inequality based results are proposed for the design of direct adaptive...
Abstract — We develop a Linear Matrix Inequality (LMI) tool for analyzing the stability and performa...
This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-d...
This thesis introduces two new extensions to L1 adaptive control theory. The first is an L1 adaptive ...
Linear matrix inequalities and convex optimization techniques have become popular tools to solve non...
In this paper, a new adaptive control framework for linear systems in which the matched uncertainty ...
A novel method of an adaptive linear quadratic (LQ) regulation of uncertain continuous linear time-i...
In this dissertation, new model reference adaptive control architectures are presented with stabilit...
In this dissertation, new model reference adaptive control architectures are presented with stabilit...
Passification-based adaptive control, also known as simple adaptive control, is studied with respect...
AbstractThis article deals with the reliable adaptive control with H ∞ performance for linear system...
The scope of this research is a problem of the direct model reference adaptive control of linear tim...
This thesis introduces two new extensions to L1 adaptive control theory. The first is an L1 adaptive ...
International audienceMatrix inequality based results are proposed for the design of direct adaptive...
We consider the adaptive tracking problem for a chain of integrators, where the uncertainty is stati...
International audienceMatrix inequality based results are proposed for the design of direct adaptive...
Abstract — We develop a Linear Matrix Inequality (LMI) tool for analyzing the stability and performa...
This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-d...
This thesis introduces two new extensions to L1 adaptive control theory. The first is an L1 adaptive ...
Linear matrix inequalities and convex optimization techniques have become popular tools to solve non...
In this paper, a new adaptive control framework for linear systems in which the matched uncertainty ...
A novel method of an adaptive linear quadratic (LQ) regulation of uncertain continuous linear time-i...
In this dissertation, new model reference adaptive control architectures are presented with stabilit...
In this dissertation, new model reference adaptive control architectures are presented with stabilit...
Passification-based adaptive control, also known as simple adaptive control, is studied with respect...
AbstractThis article deals with the reliable adaptive control with H ∞ performance for linear system...
The scope of this research is a problem of the direct model reference adaptive control of linear tim...
This thesis introduces two new extensions to L1 adaptive control theory. The first is an L1 adaptive ...
International audienceMatrix inequality based results are proposed for the design of direct adaptive...
We consider the adaptive tracking problem for a chain of integrators, where the uncertainty is stati...
International audienceMatrix inequality based results are proposed for the design of direct adaptive...