This paper presents a nonlinear adaptive observer based on multilayer perceptron (MLP) neural networks, which is indeed a nonlinear-in-parameters neural network (NLPNN), for a class of nonlinear systems including chaotic systems in which all MLP weights are tuned on-line. These systems can be decomposed into linear and nonlinear parts. It is assumed that the linear part is known while the nonli...

Abstract: A robust/adaptive stochastic observer is presented for stochastic nonlinear dynamics having excessive uncertainties. It was shown through a new theorem that the proposed nonlinear robust sliding mode observer has very accurate state estimate error characteristic. The observer uses the sliding mode technique for the robustness and a deterministic adaptive law to guarantees a globally a...

This paper presents a new extended output depending nonlinear observer normal form. A sufficient geometrical conditions that guarantee a change of coordinates allowing the transformation of a given nonlinear dynamical system into the proposed observer form are given. Throughout this work, it will be showed that, unlike to the existing observer normal forms, this new form enables to design an ob...

In this paper, a nonlinear model of the underactuated six degrees of freedom (6 DOF) quadrotor helicopter was derived based on the Newton-Euler formalism. A new nonlinear robust control strategy was proposed to solve the stabilizing and path following problems in presence of external disturbances and parametric uncertainties. The proposed control structure consist of a sliding mode control base...

This paper presents a nonlinear canonical form which is used for the design of a reduced order observer. Sufficient and necessary geometric conditions are given in order to transform a special class of nonlinear systems to the proposed nonlinear canonical form and the corresponding reduced order observer is analyzed.

In this works, we use the approach based on observers such as the Luenberger observer and the sliding mode observer in order to introduce the diagnosis of nonlinear systems. The robustness of the proposed observers is tested through a physical example. The obtained results show that for non linear systems the performances of sliding mode observer observer is better than using a classic kind of ...

Abstract: In this study, a dynamic surface controller based on a nonlinear disturbance observer is investigated to control mobile wheeled inverted pendulum system. By using a coordinate transformation, the underactuated system is presented as a semi-strict feedback form which is convenient for controller design. A dynamic surface controller together with a nonlinear disturbance observer is desi...

This paper considers the use of neural networks for nonlinear state estimation, system identification and control. As a case study we use data taken from a nonlinear injection valve for a superheater attemporator at a power plant. One neural network is trained as a nonlinear simulation model of the process, then another network is trained to act as a combined state and parameter estimator for t...