Design Considerations in Actuators for Aerospace Applications

Kakosimos, Panagiotis; Tsampouris, Evangelos M.; Kladas, Antonios G.

doi:10.1109/tmag.2013.2239975

Cited by 6 publications

(6 citation statements)

References 10 publications

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“…Moreover, feedback compensation has low sensitivity to uncertain parameters variations and it weakens the influences of the disturbance to the EMA system. From Equations (1) and (16), the transfer function of the cascaded control system in Figure 11 Similarly, the transfer function of the feedback compensated control system in Figure 11(b) can be written as…”

Section: Bandwidthmentioning

confidence: 99%

“…[1][2][3] EMA is subjected to uncertainties for several reasons including operating point changes, perpetual parametric variations because of temperature changes, aging, un-modeled dynamics, load changes, and asymmetric behavior. Consequently, the desired EMA's performance will be unachievable and, in some cases, its stability may be lost.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Electromechanical actuator (EMA) is highly demanded in robotic and aerospace applications since it has attractive characteristics such as simplicity, reliability, low cost, good dynamic characteristics, momentary overdrive capability, and easy control. [1][2][3] EMA is subjected to uncertainties for several reasons including operating point changes, perpetual parametric variations because of temperature changes, aging, un-modeled dynamics, load changes, and asymmetric behavior. Consequently, the desired EMA's performance will be unachievable and, in some cases, its stability may be lost.…”

Section: Introductionmentioning

confidence: 99%

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Identification, uncertainty modeling and robust controller design for an electromechanical actuator

Salloum

Arvan

Moaveni

2016

Proceedings of the Institution of Mechanical Engineers, Part C:

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Electromechanical actuators (EMAs) are of interest for applications which require easy control and high dynamics. This paper addresses the experimental identification, structured and unstructured uncertainties modeling, and robust control design for an EMA system with harmonic drive. Two robust controllers are designed by two proposed approaches: The first is based on Kharitonov theorem, which not only robustly stabilizes the uncertain EMA system but also maintains the pre-specified margins and bandwidth constraints. The second is feedback compensation design procedure based on H 1 control theory, verifying good tradeoff between the powerful H 1 controller and the unique features of feedback compensation, such as simplicity, effectiveness, low sensitivity to parameters variations, low cost, and easy implementation. Simulation and experiments prove the robustness and high tracking performance of the robust EMA systems which reveals the affectivity of the proposed robust control design methods.

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Section: Bandwidthmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identification, uncertainty modeling and robust controller design for an electromechanical actuator

Salloum

Arvan

Moaveni

2016

Proceedings of the Institution of Mechanical Engineers, Part C:

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show abstract

“…Some machine types contain a great deal of saliency; cylindrical rotor theory is not valid and thus dq-transformation is the most appropriate way to analyze their operation, although additional difficulties to the analysis emerge from [9][10][11]. The extraction of model parameters in d-and q-axis is more complicated than the conventional approach used to be employed [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Parameter Extraction of a PM Machine Employing 3D Finite Element Analysis Tools for Model Predictive Control Schemes

Kakosimos

Beniakar

Kimoulakis

et al. 2014

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This paper introduces a permanent magnet (PM) machine model accounting for saturation effects and non-sinusoidal electromotive force (EMF) employed in model predictive control schemes. The procedure of the model parameters determination is based on the three dimensional finite element analysis (FEA) considering saturation and cross-coupling effects. The conventional equivalent circuit model is subject to modifications so as to incorporate data derived from FEA enabling the model predictive control strategies to obtain proper actions for the converter operation based on the accurate prediction of the machine performance. The regeneration of the n-order harmonic components of the non-sinusoidal EMF is attained by combining methods of superposition and approximation estimating the output voltage at the machine terminals for different loading and speed. Developed model simulation results have been validated by experiments performed on an inset PM machine prototype.

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Multiobjective Evolutionary Optimization of a Surface Mounted PM Actuator With Fractional Slot Winding for Aerospace Applications

et al. 2014

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Design Considerations in Actuators for Aerospace Applications

Cited by 6 publications

References 10 publications

Identification, uncertainty modeling and robust controller design for an electromechanical actuator

Identification, uncertainty modeling and robust controller design for an electromechanical actuator

Parameter Extraction of a PM Machine Employing 3D Finite Element Analysis Tools for Model Predictive Control Schemes

Multiobjective Evolutionary Optimization of a Surface Mounted PM Actuator With Fractional Slot Winding for Aerospace Applications

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