Modeling and L/sub 2/-stability of a shape memory alloy position control system

Shape memory alloys are among the highly applicable smart materials that have recently appealed to scientists from various fields of study. In this article, a novel shape memory alloy actuator, in the form of a rod, is introduced, and an adaptive model predictive control system is designed for position control of the developed actuator. The need for such an advanced control system emanates from the fact that modeling and controlling of shape memory alloy actuators are thwarted by their hysteresis nonlinearity, dilatory response, and high dependence on environmental conditions. Real-time identification and dynamic parameter estimation of the model are addressed according to orthogonal Laguerre functions and recursive least square algorithm. In the end, the designed control system is implemented on the experimental setup of the fabricated shape memory alloy actuator. It is observed that the designed control system successfully tracks the variable step and sinusoidal control references with startling accuracy of ±1 μm.

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Neural Network Direct Control with Online Learning for Shape Memory Alloy Manipulators

Sensors ◽

10.3390/s19112576 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2576

Author(s):

Alfonso Gómez-Espinosa ◽

Roberto Castro Sundin ◽

Ion Loidi Eguren ◽

Enrique Cuan-Urquizo ◽

Cecilia D. Treviño-Quintanilla

Keyword(s):

Neural Network ◽

Online Learning ◽

Control System ◽

Shape Memory Alloy ◽

Shape Memory ◽

Position Control ◽

Reference Signal ◽

Angular Position ◽

Hysteresis Model ◽

Direct Control

New actuators and materials are constantly incorporated into industrial processes, and additional challenges are posed by their complex behavior. Nonlinear hysteresis is commonly found in shape memory alloys, and the inclusion of a suitable hysteresis model in the control system allows the controller to achieve a better performance, although a major drawback is that each system responds in a unique way. In this work, a neural network direct control, with online learning, is developed for position control of shape memory alloy manipulators. Neural network weight coefficients are updated online by using the actuator position data while the controller is applied to the system, without previous training of the neural network weights, nor the inclusion of a hysteresis model. A real-time, low computational cost control system was implemented; experimental evaluation was performed on a 1-DOF manipulator system actuated by a shape memory alloy wire. Test results verified the effectiveness of the proposed control scheme to control the system angular position, compensating for the hysteretic behavior of the shape memory alloy actuator. Using a learning algorithm with a sine wave as reference signal, a maximum static error of 0.83° was achieved when validated against several set-points within the possible range.

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Application of Shape Memory Alloy Actuators to Control the Displacement of an Adaptive Beam

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.415-417.2196 ◽

2011 ◽

Vol 415-417 ◽

pp. 2196-2201

Author(s):

Rong Liu ◽

Ping He ◽

Chang Shui Feng

Keyword(s):

Shape Memory Alloy ◽

Shape Memory ◽

Real Time ◽

Control Strategy ◽

Pid Control ◽

Position Control ◽

Real Time Control ◽

Precise Position ◽

Time Control ◽

Position Control System

Shape memory alloy (SMA) wire actuators have broad application prospects in many fields. But due to the nonlinearity of inherent hysteresis of SMA, the precise position control system is difficult to be obtained to these kinds of actuators. Therefore, it is significant to research the control technology of SMA wire actuators to extend the application of SMA wire actuators. In the current paper, a shape memory alloy wire actuator is designed to control the displacement of an adaptive beam. The dynamic model of SMA wire actuator is derived based on Brinson’s model and two types of inputs are used to produce different displacements. Then, PID control strategy for the SMA actuators is established and implemented to active control the position. Also, real-time control (RTC) is applied to the SMA wire actuators, which can concurrently generate real-time codes and accelerate the process of simulation. Through the comparison of different amplitudes and frequencies of current inputs, the different control abilities and characteristics to acquire the maximal displacement can be approximately achieved. Significantly, the position can basically remain stable. The results demonstrate the SMA wire actuators can be used to stably control the displacement of the adaptive beam.

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A novel differential shape memory alloy actuator for position control

Robotica ◽

10.1017/s0263574700018853 ◽

1995 ◽

Vol 13 (4) ◽

pp. 423-430 ◽

Cited By ~ 32

Author(s):

Robert B. Gorbet ◽

R. Andrew Russell

Keyword(s):

Shape Memory Alloy ◽

Shape Memory ◽

Heat Sink ◽

Position Control ◽

Heat Sinks ◽

Niti Shape Memory Alloy ◽

Shape Memory Alloy Actuator ◽

Loop Bandwidth ◽

Novel Design ◽

Position Control System

SummaryThis paper discusses a novel design for a rotary differential NiTi shape memory alloy actuator, which incorporates a mobile heat sink. The new mechanism is described in detail, and its performance in a position control system is compared with that of the same actuator without heat sink. Experimental results are presented which show an improvement in actuator response time, as well as closed-loop bandwidth. The design of the mechanism gives enhanced performance, without the increased power consumption associated with fixed heat sinks.

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