Mohamed Chemachema

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A direct adaptive control algorithm, based on neural networks (NN) is presented for a class of single input single output (SISO) nonlinear systems. The proposed controller is implemented without a priori knowledge of the nonlinear systems; and only the output of the system is considered available for measurement. Contrary to the approaches available in the(More)
Abstract: In this paper, the controller introduced represent, at the best knowledge of the authors, the first application of feedback linearization technique to control a Twin Rotor Multi-input Multi-output System (TRMS). With the coupling effects considered as the uncertainties, the highly coupled nonlinear TRMS is decomposed into a horizontal and a(More)
This paper deals with indirect adaptive control using fuzzy systems for a class of uncertain SISO systems with unknown control gain sign. The uncertain nonlinearities of the systems are captured by fuzzy systems that have been proven to be universal approximators and the Nussbaum -type function is used to deal with the unknown control gain sign. The(More)
In this paper, a new decentralized adaptive control with modified Minimal Controller Synthesis MCS is proposed to position the beam of the Twin Rotor Multi-input multi-output System (TRMS) at the desired positions quickly and accurately. A new hyperstability based adaptive control technique, called decentralized Error-based minimal controller synthesis with(More)