Observer design for induction motor: an approach based on the mean value theorem

Robust Observer Design for Uncertain Lipschitz Nonlinear Systems Based on Differential Mean Value Theorem: Application to Induction Motors

“…Inspired by the work presented out by Thau's, many authors have addressed observer design for Lipschitz nonlinear systems using a variety of approaches (see for instance (Abbaszadeh and Marquez 2006;Pertew et al 2006;Phanomchoeng and Rajamani 2010;Rajamani 1998;Song and Hedrick 2011;Zhu and Han 2002). Unfortunately, the main drawback of all these above mentioned approaches relies on the fact that the LMI conditions may become infeasible for some high values of the Lipschitz constant (Hammoudi et al 2014). In order to conquer this restriction, an alternative approach was proposed by Zemouche et al (2005) for nonlinear observer design.…”

“…In the same context, other works have also been focused on the application of the same concept to induction motor, which is the subject of this paper. For instance, the observer proposed by Ichalal et al (2011) was used by Hammoudi et al (2014) to estimate the state variables of induction motor. In Zeghib et al (2019), the DMVT approach combined with sector nonlinearity has been applied to design a robust extended observer of an IM (the ordinary states, and the rotor position), by taking the H ∞ norm into account to minimize the effect of the external disturbance on the estimation error.…”

“…Despite the importance of sensitivity to parametric variations in stability studies, but the previous works (Hammoudi et al 2014;Zeghib et al 2019) did not incorporate them due to the additional complexity and its implication (Dinesh and Sharma 2019). The first discussions about the problem of robust observer design for a class of Lipschitz nonlinear systems in the presence of disturbance and model uncertainties go back to the works of de Souza et al (1993).…”

Observer for nonlinear systems with unknown input using mean value theorem and genetic algorithm

“…In the work of Ichalal et al, the dynamics of state estimation errors was written in Takagi‐Sugeno system (this system type is consider by several authors) form using the mean value theorem and the sector nonlinearity transformation. The design developed in the work of Zemouche et al was used for the observer design of an induction motor system . In the work of Sharma et al, an extension for unknown input observer for nonlinear discrete and continuous systems using the mean value theorem was discussed.…”

A Metric Observer for Induction Motors Control

“…The most well-known and popular ones are given in [11,12], in which authors have proposed the model reference adaptive system (MRAS) for the estimation of the induction motor speed, from measured phase voltages and currents, based on the adaptive control theory. Some other observer has been proposed based on the context of more advanced and/or intelligent control technique such as sliding mode [13], high gain observer [14], and the mean value theorem [15].…”