Force Control for Anthropomorphic Fingers Actuated by Shape Memory Alloy Wires

2021 ◽  
pp. 58-62
Author(s):  
Mircea Hulea ◽  
Keyword(s):  
Neural Network ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Inhibitory Neurons ◽  
Human Hand ◽  
Artificial Muscles ◽  
Contraction Force ◽  
Sma Actuators ◽  
The Neural Network ◽  
Artificial Neurons

High accuracy in modelling the behavior of human hand and fingers is obtained using control devices of high biological plausibility. Such devices are typically based on neural networks and are able to control in parallel multiple artificial muscles. This paper presents the structure of an electronic spiking neural network that was implemented to control the force of two opposing fingers of an anthropomorphic hand. In order to increase the level of bio-inspiration, the artificial muscles are implemented using shape memory alloy wires which actuates by contraction as the natural muscles. Moreover, the contraction force of the SMA actuators is directly related to the spiking frequency that is generated by the artificial neurons. The results show that using few excitatory and inhibitory neurons the neural network is able to set and regulate the contraction force of the SMA actuators.

Vibration Control of Cylindrical Shell Panel With Shape Memory Alloy Actuators

2013 ◽  
Author(s):  
Huiyu Li ◽  
Hua Li ◽  
H. S. Tzou
Keyword(s):  
Neural Network ◽  
Cylindrical Shell ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Vibration Control ◽  
Neutral Network ◽  
Sma Actuators ◽  
The Neural Network ◽  
Network Method ◽  
Shell Panel

This paper studies the vibration control of cylindrical shell panel. Shape memory alloy (SMA) wires are adopted as actuators and neural network training method is applied to enable SMA to output desired force. The proposed SMA actuators are fixed on the cylindrical shell panel and generate contracting forces while be heated electronically. The SMA actuators need to generate forces opposite to the external loading, and thus they can suppress the effect of external force. However, as SMAs present nonlinear relationship between temperature and force, it is difficult to output the desired stress profile. In this research, the hysteresis characteristics of SMAs are fitted by neural networks. The neural network model of SMA plant model is established based on the temperature input and force output; and the inverse model is generated with the force as input and temperature as output. The desired forces are obtained based on these neural network models. To validate the effectiveness of SMA actuators, the vibration response of cylindrical shell panel is analyzed with modal expansion method. The modal response under the controlling of SMA actuators is calculated based on the modal dynamic equation. The results show that SMA actuators controlled by the neural network method are effective to suppress the vibration of cylindrical panel shell. Primary experiments were performed to verify the proposed neutral network method. The results show that the SMA wire actuator generated desired force profile while heating using the neutral network method.

Neural Network Tracking Control of a Shape Memory Alloy Wire Actuator Without a Position Sensor

2001 ◽  
Author(s):  
G. Song ◽  
V. Chaudhry ◽  
C. Batur
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Tracking Control ◽  
Open Loop ◽  
Training Data ◽  
Position Sensor ◽  
The Neural Network ◽  
Sma Actuator

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.

Modeling and Analysis of Compressive Properties of Porous NiTi Shape Memory Alloy Using Artificial Neural Network

2008 ◽  
Vol 41-42 ◽  
pp. 135-140 ◽  
Author(s):  
Qiang Li ◽  
Xu Dong Sun ◽  
Jing Yuan Yu ◽  
Zhi Gang Liu ◽  
Kai Duan
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Thermal Explosion ◽  
Process Parameters ◽  
Niti Shape Memory Alloy ◽  
Compressive Properties ◽  
Porous Niti ◽  
Bp Model

Artificial neural network (ANN) is an intriguing data processing technique. Over the last decade, it was applied widely in the chemistry field, but there were few applications in the porous NiTi shape memory alloy (SMA). In this paper, 32 sets of samples from thermal explosion experiments were used to build a three-layer BP (back propagation) neural network model. According to the registered BP model, the effect of process parameters including heating rate ( ), green density ( ) and particle size of Ti ( d ) on compressive properties of reacted products including ultimate compressive strength ( v D σ ) and ultimate compressive strain (ε ) was analyzed. The predicted results agree with the actual data within reasonable experimental error, which shows that the BP model is a practically very useful tool in the properties analysis and process parameters design of the porous NiTi SMA prepared by thermal explosion method.

scholarly journals Shape Memory Alloy Artificial Muscles for Treatments of Fecal Incontinence

2004 ◽  
Vol 45 (2) ◽  
pp. 272-276 ◽  
Author(s):  
Yun Luo ◽  
Toshiyuki Takagi ◽  
Shintaro Amae ◽  
Motoshi Wada ◽  
Tomoyuki Yambe ◽  
...  
Keyword(s):  
Fecal Incontinence ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Artificial Muscles

Structural fatigue and fracture of shape memory alloy actuators: Current status and perspectives

2021 ◽  
pp. 1045389X2110572
Author(s):  
Md Mehedi Hasan ◽  
Theocharis Baxevanis
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Current Status ◽  
Structural Fatigue ◽  
Sma Actuators ◽  
Empirical Relations ◽  
Fatigue And Fracture ◽  
And Performance ◽  
Commercial Applications ◽  
Crack Growth Rates

Shape Memory Alloy (SMA)-actuators are efficient, simple, and robust alternatives to conventional actuators when a small volume and/or large force and stroke are required. The analysis of their failure response is critical for their design in order to achieve optimum functionality and performance. Here, (i) the existing knowledge base on the fatigue and overload fracture response of SMAs under actuation loading is reviewed regarding the failure micromechanisms, empirical relations for actuation fatigue life prediction, experimental measurements of fracture toughness and fatigue crack growth rates, and numerical investigations of toughness properties and (ii) future developments required to expand the acquired knowledge, enhance the current understanding, and ultimately enable commercial applications of SMA-actuators are discussed.

On a Finger Model Actuated With Shape Memory Alloy Artificial Muscles

2003 ◽  
Author(s):  
Veturia Chiroiu ◽  
Ligia Munteanu ◽  
Traian Badea ◽  
Cornel Mihai Nicolescu
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Aluminum Matrix ◽  
Electrical Current ◽  
Longitudinal Axis ◽  
Damping Capacity ◽  
Artificial Muscles ◽  
Niti Wires ◽  
Finger Model ◽  
Start Temperature

The simulation of a flexible finger, actuated with the shape memory alloys (SMAs) artificial muscles, is presented in the paper. The finger is modeled as a cylindrically rod with three embedded NiTi wires in a n aluminum matrix. Forces between NiTi wires causes bending in any plane perpendicular to the longitudinal axis of the finger. The NiTi wires are heated above the austenitic start temperature by passing an electrical current, and the deflected wire tends to return to the initial configuration. Using characteristics of SMAs such as high damping capacity, super-elasticity, thermo-mechanical behavior and shape memory, the actuation for the finger is theoretically introduced and discussed.

Optimal H∞ Control of Structural Vibrations Using Shape Memory Alloy Actuators

1999 ◽  
Author(s):  
Jian Sun ◽  
Ali R. Shahin
Keyword(s):  
Mathematical Model ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Model Uncertainty ◽  
High Frequency ◽  
Structural Vibrations ◽  
Design Procedures ◽  
Sma Actuators ◽  
Temperature Dynamics ◽  
The Mathematical Model

Abstract This paper investigates robust control problem of structural vibrations using shape memory alloy (SMA) wires as actuators. The mathematical model for these SMA actuators is derived with emphasis in model uncertainty. The linearization of the relation between stress and temperature dynamics of SMA actuators is analyzed for active control. To handle the uncertainties caused by the linearization and the neglected high frequency dynamics, optimal H∞ control was employed to design a controller. An example is used to demonstrate the design procedures and the control system is tested in a nonlinear environment.

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