Adaptive sliding mode and model predictive control of linear variable reluctance motor

Habeeb, Irfan; Ismail, El-Fallah

doi:10.1109/aicera.2014.6908262

Cited by 1 publication

(3 citation statements)

References 5 publications

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“…To verify the improved performance, the robustness against parameter variation, and tracking capability of the proposed AFSMC, some simulations were done. First, the proposed AFSMC was applied to the LSRM and its performance was compared to the ASMC [38]. The obtained results are displayed in Fig.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…According to the definitions and proofs described in [31], the system described in (9) is UUB using the proposed controller. The equations of the LSRM can be expressed as the state equation as [38]…”

Section: Sliding Mode Controllermentioning

confidence: 99%

“…The equations of the LSRM can be expressed as the state equation as [38]

(][, \begin{matrix} 1em4pt \\ \dot{e} false(t false) \\ \ddot{e} false(t false) \end{matrix}) = (][, \begin{matrix} 1em4pt \\ 0 & 1 \\ 0 & - \frac{C}{M} + Δ p \end{matrix}) (][, \begin{matrix} 1em4pt \\ e false(t false) \\ \dot{e} false(t false) \end{matrix}) + (][, \begin{matrix} 1em4pt \\ 0 \\ - \frac{1}{M} \end{matrix}) {\dot{F}}_{e} ()(, t) + (][, \begin{matrix} 1em4pt \\ 0 \\ 1 \end{matrix}) normalΔ normald

where

normalΔ p

and

normalΔ d

are considered the internal parameters varying and external disturbances.…”

Section: Design Of the Controllermentioning

confidence: 99%

See 2 more Smart Citations

New adaptive fuzzy sliding mode scheme for speed control of linear switched reluctance motor

Azadru

Masoudi

Ghanizadeh

et al. 2019

IET Electric Power Applications

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This study presents a new control system for a linear switched reluctance motor (LSRM). Type-2 Takati-Sugeno fuzzy system is used for the motor approximation. The uncertain parameters of the motor are described by the lower and upper membership functions. By constructing an integral sliding mode surface, an adaptive sliding mode controller is designed and dynamic stability of the sliding motion is verified using the Lyapunov function. The design of the proposed sliding mode surface is independent of the number of fuzzy rules and thus, computational complexity is significantly decreased. The control system is implemented on a double-sided four-phase LSRM and its performance is demonstrated by means of modelling and experimental results.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Sliding Mode Controllermentioning

confidence: 99%