Nonlinearity is the inherent characteristics of all the industrial processes. The Classical control approach used for a generation often fails to show better results particularly for non-linear systems and in the systems, whose parameters changes over a period of time for a variety of reasons. Alternatively, adaptive control strategies provide very good performance. The Model Reference Adaptive...

 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...

This paper presents a novel method for the rotor resistance identification of an indirect rotor field oriented (IRFO) control system of a saturated induction motor. A saturated induction motor is an induction motor with a variable (saturable) mutual inductance. Saturation of the mutual inductance appears in operating conditions with variable rotor flux levels in the IRFO control system of an in...

With the aim to achieve high dynamic performances under system uncertainties and load torque even at very low speed range, this paper presents a novel robust sensorless speed vector control strategy for single phase induction motor (SPIM). The proposed strategy includes a speed controller and a model reference adaptive system (MRAS) estimation algorithm of rotor speed both are based sliding mod...

This paper proposes a rotor speed identification method for sensorless induction motor drives based on a model reference adaptive system (MRAS). In this scheme, the error between estimated stator current and real stator current is regarded as the system error to estimate the rotor speed. Adaptive fullorder flux observers for estimating the rotor speed are developed using Lyapunov’s stability th...

We propose a randomized search method called Stochastic Model Reference Adaptive Search (SMRAS) for solving stochastic optimization problems in situations where the objective functions cannot be evaluated exactly, but can be estimated with some noise (or uncertainty), e.g., via simulation. The method is a generalization of the recently proposed Model Reference Adaptive Search (MRAS) method for ...

Abstract: This paper presents an exact input-output linearization control scheme for rotor speed and rotor flux control of induction motor drive. In this scheme the motor model, is described in the fixed stator frame, and it is linearized, using exact inputoutput linearization technique, allowing a decoupled control of rotor flux and torque. To avoid the use of mechanical sensor, the rotor spee...

To simplify the system structure of permanent magnet synchronous linear motor (PMSLM), optimize kinematic performance control system, and further improve speed tracking accuracy PMSLM, a model-free regulation design PMSLM based on adaptive observer is proposed. Aiming at instability problem caused by parameter uncertainty PI in controller (MFC) ultra-local model proposed, which has strong robus...