This paper investigates the simultaneous design of a controller and Luenberger state observer for systems with time-delays, external disturbances, uncertainties, modeling errors, unknown nonlinear perturbations. The state-feedback control approach state-observer existence conditions are formulated using Linear Matrix Inequalities (LMIs). By defining estimation error, equations closed-loop syste...

A neural network embedding learning control scheme is proposed in this paper, which addresses the performance optimization problem of a class nonlinear system with unknown dynamics and disturbance by combining novel function approximator an improved observer (DOB). We investigated mixture basic (MBF) to approximate system, allows approximation global scope, replacing traditional radial basis (R...

In this paper, we propose a nonlinear state feedback controller based on linear matrix inequality (LMI) for class of systems with parametric uncertainties and external disturbances. The primary goals the proposed are to guarantee system stability performance in presence time-dependent To meet specified objectives, LMI form is calculated as hierarchical control structure. Using Lyapunov function...

When geomagnetic disturbances (GMDs) occur, the reactive power loss (GIC-Q) caused by geomagnetically induced currents (GICs) flowing through transformers can lead to system instability. Previous studies have been focused on impacts of GMD static stability conventional systems, while transient hybrid systems left unexplored. In this article a based wind and energy sources are proposed as resear...

A fuzzy controller equipped with an adaptive algorithm and two supervisors is developed in this work to achieve tracking performances for a class of uncertain nonlinear single input single output (SISO) systems with external disturbances. The convergence of the training algorithm is guarantied by a gradient projection law. The effect of both the approximation errors and the external disturbance...

This paper addresses the problem of robust state estimation of switched uncertain systems subject to unknown disturbances. The proposed approach is based on switched interval observers which provide guaranteed lower and upper bounds allowing to evaluate the set of admissible values of the real state vector. The stability and cooperativity conditions of the proposed switched observer are express...

This paper focuses on the stability and convergence analysis of a neuro-identification scheme for uncertain nonlinear systems. Based on linearly parameterized neural networks and the previous knowledge of upper bounds for the approximation error and disturbances, a robust modification of the descent gradient algorithm is proposed to make the overall identification process stable, and, in additi...

An asymptotically stable direct adaptive fuzzy PI sliding mode controller is proposed for a class of nonlinear uncertain systems. In contrast to other existing approaches of handling disturbances, the proposed approach does not require this bound to be known, only requiring that it exists. Moreover, a PI control structure is used to attenuate chattering. The approach is applied to stabilize an ...