Nonlinear motion and force control of shape memory alloy actuators

Benzaoui, H.; Chaillet, Nicolas; Lexcellent, Christian; Bourjault, A.

doi:10.1117/12.350125

Cited by 10 publications

(11 citation statements)

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“…3 whereV is the voltage input to the actuator and y is the displacement of the weight. This system can be partly addressed by a simple thermal model [12] given by (1) where m is the mass of the actuator per unit length of wire, h is the convection coefficient, A is the surface area of the SMA wire actuator, andθ is the difference between the internal and the ambient temperatures. The resistance of the wire is given by…”

Section: B Modelmentioning

confidence: 99%

“…The identification process is analyzed in Table I by calculating the Mean Square Error (MSE) and the percentage of Best Fit given by [22] ( 12) where T N is the total number of samples, ( ) y k and ( ) y k are the output of the physical system and Laguerre filter respectively and y is the mean of y . From the Table I it can be seen that the MSE increases along with the forgetting factor, and so is the percentage of data fitted.…”

Section: B Influence Of Forgetting Factormentioning

confidence: 99%

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Identification of dynamics and hysteresis of Shape Memory Alloy (SMA) actuator using Laguerre filters

Kannan

Giraud-Audine

Patoor

2008

2008 IEEE International Symposium on Industrial Electronics

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Recursive approximation of a hysteretic system namely a Shape Memory Alloy (SMA) Actuator using Laguerre filters is experimentally tested in this paper. This approach permits us to capture simultaneously the Nonlinearity and the Dynamic of the system as opposed to most of the strategies dealt within the literature, where hysteresis is first compensated, then the dynamic is controlled. Two schemes using Linear Laguerre filter and Nonlinear Volterra Laguerre filters have been implemented to identify the SMA actuator with Hysteresis. An output prediction error model using classical Recursive Least Square (RLS) has been used to approximate the Hysteretic SMA. The Linear and Nonlinear Laguerre models have proven to be efficient with the choice of appropriate Laguerre pole. The two models have been compared and studied under different circumstances.

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Section: B Modelmentioning

confidence: 99%

Section: B Influence Of Forgetting Factormentioning

confidence: 99%

Identification of dynamics and hysteresis of Shape Memory Alloy (SMA) actuator using Laguerre filters

Kannan

Giraud-Audine

Patoor

2008

2008 IEEE International Symposium on Industrial Electronics

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“…Passivity property of the system is used in [16] to prove stability of a proposed proportional law. Nonlinear control techniques based on the Lie algebra are also used in [17]. Even if their model are quite good enough, using a dynamic model for computing the control law, need firstly to identify the model parameter.…”

Section: Introductionmentioning

confidence: 99%

A new control strategy for shape memory alloys actuators

Gédouin

Join

Delaleau

et al. 2009

ESOMAT 2009 - 8th European Symposium on Martensitic Transformations

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Abstract. Shape memory alloys (SMA) are more and more integrated in engineering applications. These materials with their shape memory effect permit to simplify mechanism and to reduce the size of actuators. SMA parts can easily be activated by Joule effect but their modelling and consequently their control remains difficult, it is principally due to their hysteretic thermomechanical behaviour. Another difficulty is that the characteristics of the material are timevarying, especially during cyclic loadings. So, most of successful control strategy applied to SMA actuator are particularly heavy and used the Preisach model or neural networks to model the hysteretic behaviour of these material but this kind of models are difficult to identify and to use in real time. That is why this study deals with an application of the new framework of model-free control and restricted model control applied to a SMA spring based actuator. This control strategy is based on new results on fast derivative s estimation of noisy signals, its main advantages are: its simplicity, its robustness and the fact that it is easy to compute. Experimental results and comparisons with PID control are exposed that demonstrate the efficiency of this new control strategy despite thermal perturbations.

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“…Passivity property of the system is used in Madill and Wang [1998] to prove stability of a proposed proportional law. Nonlinear control techniques based on the Lie algebra are also used in Benzaoui et al [1999]. Even if their model are quite good enough, using a dynamic model for computing the control law, need firstly to identify the model parameter.…”

Section: Introductionmentioning

confidence: 99%