Development of a 6-Channel Power Controller for Simultaneous Actuation and Resistance Measurement of SMA Wires

2010 ◽  
Author(s):  
Rohan Hangekar ◽  
Stephen Furst ◽  
Stefan Seelecke
Keyword(s):  
Joule Heating ◽  
Position Control ◽  
Optimization Techniques ◽  
Sensor Data ◽  
Channel Power ◽  
Practical Applications ◽  
North Carolina State University ◽  
Power Controller ◽  
Calibration Methods ◽  
The Wire

The use of ‘multifunctional’ Shape Memory Alloy wires as embedded actuators and sensors has been proposed for numerous novel applications. The SMA wires are actuated as a result of the Joule heating induced by passing electric current through it. The resistance of the SMA wire can simultaneously be measured during its actuation enabling it to be used as sensor data that relates to the strain and temperature of the wire. In order to control actuation stroke from the SMA wire, the Joule heating (electric power supplied to the SMA wire) of the wire needs to be controlled. Therefore, a 6-channel power controller device has been developed that simultaneously controls the power supplied to six different SMA wires and measures the resistance of these wires during excitation. This paper continues from the previously presented concept of a multi-channel power controller implementation. The focus of this paper is to discuss the operation, calibration methods and optimization techniques to improve the performance and robustness of the device and to eliminate the issues in multi-channel implementation. Further, this device is implemented in a test setup to study the position control of SMA wire using resistance feedback. Results of these tests can be utilized in practical applications involving SMA wires as embedded actuators and sensors, such as Smart Inhaler system being developed at North Carolina State University.

A Multi-Channel Power Controller for Actuation and Control of Multiple SMA Actuators

2009 ◽  
Author(s):  
Rohan Hangekar ◽  
Stefan Seelecke
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Electric Power ◽  
Position Control ◽  
Electronic Device ◽  
Hysteretic Behavior ◽  
Graphic User Interface ◽  
Channel Power ◽  
Power Controller ◽  
Sma Actuators

This paper presents a multi-channel electronic power controller device for Shape Memory Alloy (SMA) actuators. The use of shape memory alloy wires as actuators has been proposed in numerous novel applications such as Smart Inhaler System [1], BAT Micro Air Vehicle [2], etc. These systems have multiple SMA wires for actuation of their mechanisms. The SMA wires can be actuated by controlling the joule heating or the electric power in that wire. This paper describes the development of a multi-channel power device that can control multiple SMA actuators simultaneously. The device presented herewith utilizes a Field Programmable Gate Array (FPGA) board and a custom built electronic device to independently and simultaneously control electric power in three different SMA actuators. The controller adapts to the non linear and hysteretic behavior of the resistance of the SMA actuators and adjusts the pulse width modulated voltage across them to maintain the desired value of power. The controller uses the resistance measurement of the SMA actuators as feedback. With the help of modeling efforts to relate resistance to strain, it is envisioned that feedback position control of these actuators can be implemented without the necessity of a sensor. The device is tested with graphic user interface which enables a user to control various parameters during operation of this device and to monitor the results. The design and implementation of this device is detailed in this paper along with its performance charts. The results relate the input power, observed actuation strokes and measured resistances in the SMA actuators under various conditions. A relevant discussion on implementing position control in Smart Inhaler System using this device is also presented.

Practical Implementation of Resistance Feedback Measurement for Position Control of a Flexible Smart Inhaler Nozzle

2010 ◽  
Author(s):  
Stephen J. Furst ◽  
Rohan Hangekar ◽  
Stefan Seelecke
Keyword(s):  
Smart Materials ◽  
Position Control ◽  
Smart Structure ◽  
Practical Implementation ◽  
Sensors And Actuators ◽  
North Carolina State University ◽  
Functional Capabilities ◽  
Sma Actuator ◽  
The Wire ◽  
The Relationship

Many “smart materials” have the capacity to be used simultaneously as both an actuator and sensor. For example, SMA actuator wires can be heated by Joule heating to induce contraction; at the same time, the resistance across the SMA wire can be measured to give the user some indication of the strain in the wire. This multi-functional capability enables the design of applications requiring extremely light-weight and streamlined embedded sensors and actuators. One such “smart structure” application is the flexible nozzle used in the Smart Inhaler system under development at North Carolina State University. The Smart Inhaler allows a doctor to control the locations within the pulmonary system that are medicated by controlling the location at which medication is injected into an inhaled airflow. This can reduce the amount of healthy tissue that is exposed to potentially toxic medications, such as those used to treat lung cancer. However, the practical challenge of injecting medication into a flow without disturbing the flow requires a highly controllable yet non-obstructive nozzle. This paper presents a scheme that correlates the resistance measurement across an SMA actuator wire to the wire strain and the resulting deformation of the flexible nozzle. The relationship between resistance and nozzle deformation is nonlinear and hysteretic; however, the repeatability of the relationship allows the user to calibrate the feedback measurement. This enables the wire to be used as both position sensor and positioning actuator. The results represent the first experiments that exploit the multi-functional capabilities of SMA wires in the context of a practical embedded sensor and actuator application.

scholarly journals Extrinsic Calibration of 2D Laser Rangefinders Based on a Mobile Sphere

2018 ◽  
Vol 10 (8) ◽  
pp. 1176 ◽  
Author(s):  
Shoubin Chen ◽  
Jingbin Liu ◽  
Teng Wu ◽  
Wenchao Huang ◽  
Keke Liu ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Three Dimensional ◽  
Calibration Method ◽  
High Accuracy ◽  
Sensor Data ◽  
Extrinsic Calibration ◽  
Practical Applications ◽  
Calibration Methods ◽  
Simultaneous Location And Mapping ◽  
Automatic Matching

In the fields of autonomous vehicles, virtual reality and three-dimensional (3D) reconstruction, 2D laser rangefinders have been widely employed for different purposes, such as localization, mapping, and simultaneous location and mapping. However, the extrinsic calibration of multiple 2D laser rangefinders is a fundamental prerequisite for guaranteeing their performance. In contrast to existing calibration methods that rely on manual procedures or suffer from low accuracy, an automatic and high-accuracy solution is proposed in this paper for the extrinsic calibration of 2D laser rangefinders. In the proposed method, a mobile sphere is used as a calibration target, thereby allowing the automatic extrapolation of a spherical center and the automatic matching of corresponding points. Based on the error analysis, a matching machine of corresponding points with a low error is established with the restriction constraint of the scan circle radius, thereby achieving the goal of high-accuracy calibration. Experiments using the Hokuyo UTM-30LX sensor show that the method can increase the extrinsic orientation accuracy to a sensor intrinsic accuracy of 10 mm without requiring manual measurements or manual correspondence among sensor data. Therefore, the calibration method in this paper is automatic, highly accurate, and highly effective, and it meets the requirements of practical applications.

Enhanced second harmonic generation in individual barium titanate nanoparticles driven by Mie resonances

2017 ◽  
Vol 5 (19) ◽  
pp. 4810-4819 ◽  
Author(s):  
Churong Ma ◽  
Jiahao Yan ◽  
Yuming Wei ◽  
Pu Liu ◽  
Guowei Yang
Keyword(s):  
Barium Titanate ◽  
Harmonic Generation ◽  
Joule Heating ◽  
Nonlinear Optical ◽  
Second Harmonic ◽  
Plasmonic Nanostructures ◽  
Ohmic Loss ◽  
Complex Structures ◽  
Practical Applications ◽  
Barium Titanate Nanoparticles

Although previous designs of nonlinear optical (NLO) nanostructures have focused on photonic crystals and metal plasmonic nanostructures, complex structures, large ohmic loss, and Joule heating greatly hinder their practical applications.

scholarly journals Asymmetric Residual Neural Network for Accurate Human Activity Recognition

Information ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 203 ◽  
Author(s):  
Jun Long ◽  
Wuqing Sun ◽  
Zhan Yang ◽  
Osolo Ian Raymond
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Time Window ◽  
Research Problem ◽  
Human Activity Recognition ◽  
Sensor Data ◽  
Practical Applications ◽  
Long Time ◽  
Benchmark Datasets ◽  
High Level

Human activity recognition (HAR) using deep neural networks has become a hot topic in human–computer interaction. Machines can effectively identify human naturalistic activities by learning from a large collection of sensor data. Activity recognition is not only an interesting research problem but also has many real-world practical applications. Based on the success of residual networks in achieving a high level of aesthetic representation of automatic learning, we propose a novel asymmetric residual network, named ARN. ARN is implemented using two identical path frameworks consisting of (1) a short time window, which is used to capture spatial features, and (2) a long time window, which is used to capture fine temporal features. The long time window path can be made very lightweight by reducing its channel capacity, while still being able to learn useful temporal representations for activity recognition. In this paper, we mainly focus on proposing a new model to improve the accuracy of HAR. In order to demonstrate the effectiveness of the ARN model, we carried out extensive experiments on benchmark datasets (i.e., OPPORTUNITY, UniMiB-SHAR) and compared the results with some conventional and state-of-the-art learning-based methods. We discuss the influence of networks parameters on performance to provide insights about its optimization. Results from our experiments show that ARN is effective in recognizing human activities via wearable datasets.

Design of Nonovershoot MRACS With Application to D.C. Servo Motor System

1991 ◽  
Vol 113 (1) ◽  
pp. 75-81 ◽  
Author(s):  
K. Tamura ◽  
K. Ogata ◽  
P. N. Nikiforuk
Keyword(s):  
Adaptive Control ◽  
Motor System ◽  
Position Control ◽  
Input Sequence ◽  
Control Input ◽  
Servo Motor ◽  
Unknown Parameters ◽  
Practical Applications ◽  
Existence Region ◽  
Model Reference Adaptive

Excessive overshoots in a transient response are undesirable in a model reference adaptive control system (MRACS) and have to be avoided in practical applications. This paper discusses the design of an MRACS with no overshoot. In this design a d-step ahead estimator is introduced to evaluate the expected maximum and minimum values of the plant output. According to these estimates, the adaptive control input is adjusted so that the output has no overshoot. For the estimator and the input adjustment an existence region of the unknown plant parameters must be known. It is obvious that the smaller the existence region is, the better is the estimation and adjustment, and, consequently, the MRACS performance. First, an algorithm which successively reduces the region is presented. An initial polyhedron region V(0), which includes the unknown parameters, assumed to be given. The volume of V(k) containing the unknown parameters is then successively reduced by a projection-type algorithm which uses the input and output of the plant. Next, the design of an MRACS is discussed in which this region V(k) plays an important role. The proposed controller generates an adaptive control input sequence which makes the plant output follow the reference output without any overshoot. The proposed MRACS was applied to the adaptive position control of a D.C. servo motor system with an unknown load. Experimental results demonstrate the usefulness of the proposed design.

PATTERN RECOGNITION BY GRAPH MATCHING—COMBINATORIAL VERSUS CONTINUOUS OPTIMIZATION

1988 ◽  
Vol 02 (03) ◽  
pp. 527-542 ◽  
Author(s):  
PETER KUNER ◽  
BIRGIT UEBERREITER
Keyword(s):  
Graph Matching ◽  
Fault Tolerant ◽  
Continuous Optimization ◽  
Optimization Techniques ◽  
Quadratic Assignment ◽  
Relaxation Labeling ◽  
Practical Applications ◽  
Relational Structures ◽  
Complete Problems ◽  
Quadratic Assignment Problems

A generalization of subgraph isomorphism for the fault-tolerant interpretation of disturbed line images has been achieved. Object recognition is effected by optimal matching of a reference graph to the graph of a distorted image. This optimization is based on the solution of linear and quadratic assignment problems. The efficiency of the procedures developed for this objective has been proved in practical applications. NP-complete problems such as subgraph recognition need exhaustive computation if exact (branch-and-bound) algorithms are used. In contrast to this, heuristics are very fast and sufficiently reliable for less complex relational structures of the kind investigated in the first part of this paper. Constrained continuous optimization techniques, such as relaxation labeling and neural network strategies, solve recognition problems within a reasonable time, even in rather complex relational structures where heuristics can fail. They are also well suited to parallelism. The second part of this paper is devoted exclusively to them.

scholarly journals Communication techniques and challenges for wireless food quality monitoring

2014 ◽  
Vol 372 (2017) ◽  
pp. 20130304 ◽  
Author(s):  
Reiner Jedermann ◽  
Thomas Pötsch ◽  
Chanaka Lloyd
Keyword(s):  
Communication Protocols ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
High Signal ◽  
Remote Measurement ◽  
Signal Attenuation ◽  
Practical Applications ◽  
Battery Lifetime ◽  
Food Transport

Remote measurement of product core temperature is an important prerequisite to improve the cool chain of food products and reduce losses. This paper examines and shows possible solutions to technical challenges that still hinder practical applications of wireless sensor networks in the field of food transport supervision. The high signal attenuation by water-containing products limits the communication range to less than 0.5 m for the commonly used 2.4 GHz radio chips. By theoretical analysis of the dependency of signal attenuation on the operating frequency, we show that the signal attenuation can be largely reduced by the use of 433 MHz or 866 MHz devices, but forwarding of messages over multiple hops inside a sensor network is mostly unavoidable to guarantee full coverage of a packed container. Communication protocols have to provide compatibility with widely accepted standards for integration into the global Internet, which has been achieved by programming an implementation of the constrained application protocol for wireless sensor nodes and integrating into IPv6-based networks. The sensor's battery lifetime can be extended by optimizing communication protocols and by in-network pre-processing of the sensor data. The feasibility of remote freight supervision was demonstrated by our full-scale ‘Intelligent Container’ prototype.

scholarly journals A mixture-density-based tandem optimization network for on-demand inverse design of thin-film high reflectors

Nanophotonics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Rohit Unni ◽  
Kan Yao ◽  
Xizewen Han ◽  
Mingyuan Zhou ◽  
Yuebing Zheng
Keyword(s):  
Thin Film ◽  
High Efficiency ◽  
Periodic Structures ◽  
Probability Distributions ◽  
Optimization Techniques ◽  
Training Data ◽  
Inverse Design ◽  
Practical Applications ◽  
Mixture Density ◽  
On Demand

Abstract Deep learning (DL) has emerged as a promising tool for photonic inverse design. Nevertheless, despite the initial success in retrieving spectra of modest complexity with nearly instantaneous readout, DL-assisted design methods often underperform in accuracy compared with advanced optimization techniques and have not proven competitive in handling spectra of practical usefulness. Here, we introduce a tandem optimization model that combines a mixture density network (MDN) and a fully connected (FC) network to inversely design practical thin-film high reflectors. The multimodal nature of the MDN gives access to infinite candidate designs described by probability distributions, which are iteratively sampled and evaluated by the FC network to allow for rapid optimization. We show that the proposed model can retrieve the reflectance spectra of 20-layer thin-film structures. More interestingly, it reproduces with high precision the periodic structures of high reflectors derived from physical principles, even though no such information is included in the training data. Improved designs with extended high-reflectance zones are also demonstrated. Our approach combines the high-efficiency advantage of DL with the optimization-enabled performance improvement, enabling efficient and on-demand inverse design for practical applications.

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