Position Control of Switched Reluctance Motor Using Super Twisting Algorithm

Abstract

The inherent problem of chattering in traditional sliding mode control is harmful for practical application of control system. This paper pays a considerable attention to a chattering-free control method, that is, higher-order sliding mode (super twisting algorithm). The design of a position controller for switched reluctance motor is presented and its stability is assured using Lyapunov stability theorem. In order to highlight the advantages of higher-order sliding mode controller (HOSMC), a classical first-order sliding mode controller (FOSMC) is also applied to the same system and compared. The simulation results reflect the effectiveness of the proposed technique.

Design of a robust interval type-2 fuzzy adaptive super twisting control for a given class of disturbed MIMO nonlinear systems

“…wherꈈˆˆ 1(2) ( ) (5), the IT2-AFSs described by equations (6) and (21), and the adaptation laws given by equations (13) and (24), then, the global control law presented by equation (23) ensures the stability of the closed loop system with the best tracking performance while avoiding the chattering, despite all the constraints that influence the control system, such as unknown dynamics, approximation errors and unknown disturbances.…”

“…To eliminate or at least attenuate the chattering phenomenon, several control techniques have been employed in various technical and technological applications [11][12][13][14][15][16][17]. And in particular, those using super twisting algorithm (STA) algorithm, have recently been extensively used in the literature [18][19][20][21][22]. The STA has been introduced by Levant [23] to attenuate the chattering phenomenon while simultaneously ensuring a finite time convergence and the stability of the closed loop control system.…”

“…vectors of fuzzy basis functions, as described by equation(4); of the corresponding IT2-AFS defined by the above equation(21); N denotes the fuzzy rules number.The optimal parameters of the IT2-AFSs ˆ( )…”

Switched reluctance motor circuit drive system using adaptive nonlinear backstepping control with mended recurrent Romanovski polynomials neural network and mended particle swarm optimization

“…The performance of the SRM greatly depends on magnetic properties of core material since it consists of only iron cores and windings . Many investigators dedicated to the control and drive of the SRM owing to tremendous progress in the design methods and converters of the motor. Koblara presented a speed control scheme of the SRM using a fuzzy logic controller.…”

“…Wang proposed an adaptive inverse position control of SRM with simplified interval type 2 fuzzy neural networks. Mufti et al evolved a higher‐order sliding mode controller of the SRM. Shao et al proposed a new sensorless control approach for SRM in the single pulse control mode in high‐speed operation.…”