An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

control of well drilling operations poses a challenging issue to be tackled. the loss of well control could lead to the occurrence of blowout as a severe threat, involving the risk of human lives and environmental and economic consequences. conventional proportional-integral (pi) controller is a common practice in the well control operation. the small existing margin between pore pressure and f...

1 Abstract—Utilizing model reference adaptive control approach and multiple Lyapunov functions method, we propose a switched adaptive controller for uncertain switched linear systems in control canonical form. These systems exist naturally in many practical applications, such as variable capacity hydraulic pump involving discrete changes that are specified by the valve position. We show that th...

Extreme nonlinearity and exhibition of severe interaction effects of multivariable pH processes makes it an appropriate test bed for evaluation of advanced controllers. This paper studies different multiple model methods for Generalized Predictive Control using Independent Model approach (GPCI) with adaptive weighting matrices. New method for adaptive determination of weighting matrices, propos...

Model predictive control (MPC) for uncertain systems in the presence of hard constraints on state and input is a non-trivial problem, challenge increased manyfold absence measurements. In this paper, we propose an adaptive output feedback MPC technique, based novel combination observer robust MPC, single-input single-output discrete-time linear time-invariant systems. At each time instant, prov...