Discrete-time sliding mode speed observer for sensorless control of induction motor drives

Vieira, Rodrigo Padilha; Gastaldini, Cristiane Cauduro; Azzolin, Rodrigo Zelir; Gründling, Hilton Abílio

doi:10.1049/iet-epa.2011.0269

Cited by 36 publications

(16 citation statements)

References 33 publications

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“…Consequently, the current research focuses on reducing the chattering and implements high frequency switching control. RP Vieira et al, [14] proposes a discrete time SMO for estimating the rotor speed. He also discusses traditional algorithms aimed at chattering reduction, high frequency switching, stability analysis and parameter convergence requirements.…”

Section: Sliding Mode and Intelligent Control Based Speed Estimation mentioning

confidence: 99%

Machine model based Speed Estimation Schemes for Speed Encoderless Induction Motor Drives: A Survey

Srinivasan

2015

Bulletin EEI

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Speed Estimation without speed sensors is a complex phenomenon and is overly dependent on the machine parameters. It is all the more significant during low speed or near zero speed operation. There are several approaches to speed estimation of an induction motor. Eventually, they can be classified into two types, namely, estimation based on the machine model and estimation based on magnetic saliency and air gap space harmonics. This paper, through a brief literature survey, attempts to give an overview of the fundamentals and the current trends in various machine model based speed estimation techniques which have occupied and continue to occupy a great amount of research space.

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Section: Sliding Mode and Intelligent Control Based Speed Estimation mentioning

confidence: 99%

Machine model based Speed Estimation Schemes for Speed Encoderless Induction Motor Drives: A Survey

Srinivasan

2015

Bulletin EEI

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“…Many approaches implemented for sensorless rotor speed observer of induction machines such as in [12] is common. Recently, in [13], [14] DTSMC is designed for sensor-less vector control of permanent magnet synchronous machine, and sensorless control on induction motor drives is implemented. In [15], chattering-free digital sliding mode control with state observer and disturbance rejection is presented and in [16], the design of estimator-based sliding-mode output-feedback controllers for discrete-time systems is simulated.…”

Section: Introductionmentioning

confidence: 99%

Robust Control Design using Discrete Sliding Mode Control for Higher Order Uncertain Systems

Patil,

Patel

2020

IJEAT

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This paper considers a tracking problem on discrete-time higher-order linear time-delay systems. The improved observer-model following sliding mode controller (OMF-SMC) is proposed. The combination uses a classical Luyenberger observer based controller to achieve predefined process output and sliding mode controller is added to assure the robustness despite of uncertainty and external disturbances. To show the effectiveness of proposed method, four error performance indices, maximum peak overshoot and settling time are considered rigorously. The simulations results on the non-oscillatory, moderate oscillatory, integrating, unstable and non-minimum phase system demonstrates that the proposed approach performs better compared with classical PID controller, continuous and discrete sliding mode controllers.

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“…They usually are divided into two categories, the fundamental model based observers and anisotropies model based observers. Model-based estimation strategies include open-loop observers [5], sliding-mode observers [6], Extended Kalman Filter [7], Backstepping [8], model reference adaptive systems (MRAS) [9] and artificial intelligence (AI) [10]. Recent research also used predictive current control for sensorless IM drives [11].…”

Section: Introductionmentioning

confidence: 99%

Sensorless Control for High Performance SPIM Drives Based on the Improved Rotor Flux Identifier Using Sliding Mode

Pham¹,

Nguyen²

2019

IJIES

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In this paper, a novel Stator Current Based Model Reference Adaptive System (SC_MRAS) speed estimation scheme using neural network (NN) and Sliding Mode (SM) is proposed to improve the performance of the MRAS speed observer for high-performance Six Phases Induction Motor (SPIM) drives, especially at low and zero speed region, where the poor performance of observers is still always a large challenge. In this paper, a twolayer linear NN, which has been trained online by means of the Least Squares (LS) algorithm, is used as an adaptive model to estimate the stator current and this model is employed in prediction mode. These novel proposed can ensure that the whole drive system achieves faster satisfactory torque and speed control and strong robustness, the observer operate better accuracy and stability both in transient and steady-state operation. Especially, in this proposed observer, the rotor flux, which is needed for the stator current estimation of the adaptive model and providing to the controller, is identified based on adaptive SM technique. The improvement of Rotor Flux Estimation for SC_MRAS-Based Sensorless SPIM Drives help to eliminate the disadvantages in SC_MRAS based observer such as stator resistance sensitivity, and flux open loop integration which may cause dc drift and initial condition problems or instability in the regenerating mode of operation, therefore, enhancing the rotor flux estimation, speed estimation and control accuracy at very low and zero stator frequency operation help improve the observer and overall drive system performance. The indirect field oriented control (IFOC) for speed control of a sensorless SPIM drive using the proposed observer is built by MATLAB/ Simulink. The simulation results have proven that the observer give the good dynamic performance, quick convergence, low estimation errors both in transient and steady state operation. The proposed sensorless increase the system's accuracy, reliability and robustness. Parameter sensitivity, computational effort and stability at low and zero speed are significantly improved.

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Discrete-time sliding mode speed observer for sensorless control of induction motor drives

Cited by 36 publications

References 33 publications

Machine model based Speed Estimation Schemes for Speed Encoderless Induction Motor Drives: A Survey

Machine model based Speed Estimation Schemes for Speed Encoderless Induction Motor Drives: A Survey

Robust Control Design using Discrete Sliding Mode Control for Higher Order Uncertain Systems

Sensorless Control for High Performance SPIM Drives Based on the Improved Rotor Flux Identifier Using Sliding Mode

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