Abstract :
This paper proposes a model reference adaptive neural control of a variable structure plant, described by an implicit realization with variable order and parameters, using only output feedback. The neural control scheme proposed, is composed of two recurrent neural networks: the neuro-identifier and neurocontroller. A variable structure plant model, together with the realized adaptive neural control, are simulated by means of the MatLAb-Simulink, and the obtained simulation results are compared with those obtained by the use of an ideal implicit control, applying the true descriptor variable. The simulation results show a great similarity of the obtained graphics for the two control schemes, which demonstrate the applicability of the proposed adaptive neural control
Keywords :
feedback; learning (artificial intelligence); model reference adaptive control systems; neurocontrollers; recurrent neural nets; variable structure systems; learning algorithm; model reference adaptive control; neural-identifier; neurocontrol; output feedback; recurrent neural networks; variable structure system; Adaptive control; Automatic control; Mathematical model; Neural networks; Output feedback; Predictive models; Programmable control; Recurrent neural networks; System identification; Variable structure systems;
