A New Approach to the Precision Tracking Control of Shape-Memory Alloy Actuators using Neural Networks and a Sliding-Mode Based Robust Controller

2002 ◽  
Vol 394-395 ◽  
pp. 83-86 ◽  
Author(s):  
G. Song ◽  
V. Chaudhry ◽  
C. Batur
Author(s):  
G Song

This paper presents design and experiment results of active position control of a shape memory alloy (SMA) wire actuator using a sliding mode based robust approach. In this research, an SMA wire was chosen as an actuating element for position control owing to its high recovery stress (gt;500MPa) and tolerance to high strain (up to 5 per cent). To compensate for the inherent non-linearity associated with the SMA, a sliding mode based robust controller was designed and implemented actively to control the position of the SMA wire actuator. Experiments demonstrated the effectiveness of the robust control. For a 12 in long SMA wire actuator, the position can be controlled within 30m.


2001 ◽  
Author(s):  
G. Song ◽  
V. Chaudhry ◽  
C. Batur

Abstract Tracking control of shape memory alloy (SMA) actuators is essential in many applications such as vibration controls. Due to the hysteresis, an inherent nonlinear phenomenon associated with SMAs, open-loop control design has proven inadequate for tracking control of these actuators. Aimed at to eliminate the position sensor to reduce cost of an SMA actuator system, in this paper, a neural network open loop controller is proposed for tracking control of an SMA actuator. A test stand, including a titanium-nickel (TiNi, or Nitinol) SMA wire actuator, a position sensor, bias springs, and a programmable current amplifier, is used to generate training data and to verify the neural networks open loop controller. A digital data acquisition and real-time control system was used to record experimental data and to implement the control strategy. Based on the training data obtained from the test stand, two neural networks are used to respectively model the forward and inverse hysteresis relations between the applied voltage and the displacement of the SMA wire actuator. To control the SMA actuator without using a position sensor, the neural network inverse model is used as a feedforward controller. The experimental results demonstrate the effectiveness of the neural network open loop controller for tracking control of the SMA wire actuator.


2000 ◽  
Author(s):  
Gangbing Song ◽  
Dane Quinn

Abstract Tracking control of shape memory alloy (SMA) actuators is essential in many applications such as vibration isolation. Due to the hysteresis, an inherent nonlinear phenomenon associated with SMAs, control design based on linear methods has proven inadequate for tracking control of these actuators. In this paper, a novel tracking controller employing a nonlinear robust compensator is proposed for SMA actuators. The control design uses the sliding-mode approach and requires no detailed information of the SMA model. To test the effectiveness of the proposed controller, a single SMA wire test stand is built. A titanium-nickel SMA wire stretched by a bias spring is used as an actuator for tracking control. Experimental results show that the SMA wire actuator under the robust control can precisely follow a sinusoidal path and the effectiveness of the proposed control strategy is demonstrated.


2004 ◽  
Vol 126 (3) ◽  
pp. 674-677 ◽  
Author(s):  
G. Song ◽  
D. D. Quinn

This paper presents an experimental study of a tracking control of a shape memory alloy (SMA) wire actuator using a nonlinear robust compensator. The control design uses the sliding-mode approach and requires no detailed information about the SMA model. To test the effectiveness of the proposed controller, experiments of the tracking control of an SMA wire actuator are conducted. Experimental results show that the SMA wire actuator under the robust control can precisely follow a sinusoidal path, and the effectiveness of the proposed control strategy is thus demonstrated.


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