Observer Design for Self-Sensing of Solenoid Actuators With Application to Soft Landing

Braun, Tristan; Reuter, Johannes; Rudolph, Joachim

doi:10.1109/tcst.2018.2821656

Cited by 19 publications

(10 citation statements)

References 21 publications

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“…There is considerable literature concerning the representation of reluctance actuators with lumped-parameter models. However, most works neglect the effect of the magnetic hysteresis [4,5,6]. Some works do propose hysteresis models for actuators, but neglect the motion dynamics [7,8,9].…”

Section: Introductionmentioning

confidence: 99%

An efficient dynamical model of reluctance actuators with flux fringing and magnetic hysteresis

Moya-Lasheras

Sagüés

Llorente³

2021

Mechatronics

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Section: Introductionmentioning

confidence: 99%

An efficient dynamical model of reluctance actuators with flux fringing and magnetic hysteresis

Moya-Lasheras

Sagüés

Llorente³

2021

Mechatronics

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“…Then, some proposals directly account for the motion dynamics by including a model of the mechanical subsystem. These are based on traditional state observers, such as slidingmode observers [17], or Kalman filter extensions for nonlinear systems [18], [19]. Nonetheless, these observers still neglect certain electromagnetic phenomena, most notably the magnetic hysteresis.…”

Section: Introductionmentioning

confidence: 99%

Rauch-Tung-Striebel Smoother for Position Estimation of Short-Stroke Reluctance Actuators

Moya-Lasheras

Schellekens

Sagüés

2022

IEEE Trans. Contr. Syst. Technol.

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This paper presents a novel state estimator for shortstroke reluctance actuators, intended for soft-landing control applications in which the position cannot be measured in real time. One of the most important contributions regards the system modeling for the estimator. The discrete state of the hybrid system is treated as an input. Moreover, the model is simplified to facilitate the identification of parameters and the implementation of the estimator. Thus, auxiliary variables are added to the state vector in order to indirectly account for modeling errors. Another important contribution is the state estimation approach. It is based on the Rauch-Tung-Striebel fixed-interval smoother, which allows refining past data from later observations. Numerous simulations are performed to analyze and compare the proposal and several alternatives. In addition, experimental testing is presented to evaluate and validate the estimator. As the simulated and experimental analyses demonstrate, the combined effect of the novel additions results in significantly smaller estimation errors of position and velocity.

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“…State-of-the-art self-sensing techniques for reluctance actuators mainly exploit three physical quantities: the back-induced voltage of the actuator during motion [8,9], the differential respectively the incremental inductance [5,[10][11][12][13][14][15][16][17][18][19][20][21][22][23] as well as the eddy current losses [24][25][26][27]. Methods based on the back-induced voltage usually apply an observer for position tracking.…”

Section: Introductionmentioning

confidence: 99%

A Self-Sensing Method for Electromagnetic Actuators with Hysteresis Compensation

et al. 2021

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Self-sensing techniques are a commonly used approach for electromagnetic actuators since they allow the removal of position sensors. Thus, costs, space requirements, and system complexity of actuation systems can be reduced. A widely used parameter for self-sensing is the position-dependent incremental inductance. Nevertheless, this parameter is strongly affected by electromagnetic hysteresis, which reduces the performance of self-sensing. This work focuses on the design of a hysteresis-compensated self-sensing algorithm with low computational effort. In particular, the Integrator-Based Direct Inductance Measurement (IDIM) technique is used for the resource-efficient estimation of the incremental inductance. Since the incremental inductance exhibits a hysteresis with butterfly characteristics, it first needs to be transformed into a B-H curve-like hysteresis. Then, a modified Prandtl–Ishlinskii (MPI) approach is used for modeling this hysteretic behavior. By using a lumped magnetic circuit model, the hysteresis of the iron core can be separated from the air gap, thus allowing a hysteresis-compensated estimation of the position. Experimental studies performed on an industrial switching actuator show a significant decrease in the estimation error when the hysteresis model is considered. The chosen MPI model has a low model order and therefore allows a computationally lightweight implementation. Therefore, it is proven that the presented approach increases the accuracy of self-sensing on electromagnetic actuators with remarkable hysteresis while offering low computational effort which is an important aspect for the implementation of the technique in cost-critical applications.

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Observer Design for Self-Sensing of Solenoid Actuators With Application to Soft Landing

Cited by 19 publications

References 21 publications

An efficient dynamical model of reluctance actuators with flux fringing and magnetic hysteresis

An efficient dynamical model of reluctance actuators with flux fringing and magnetic hysteresis

Rauch-Tung-Striebel Smoother for Position Estimation of Short-Stroke Reluctance Actuators

A Self-Sensing Method for Electromagnetic Actuators with Hysteresis Compensation

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