Abstract
In this paper, a closed-loop, smart transducer design is proposed, based on artificial neural network (ANN) techniques. The design aims to improve the performance of open-loop, off-the-shelf capacitive acceleration sensors and increase their robustness to manufacturing tolerances. A "model reference" control strategy was adopted for the design of the smart transducer. Multilayer perceptron (MLP) type networks were chosen for implementing the control strategy. While a static MLP was used for the feedback arrangement, a tap delayed lines MLP was necessary for implementing the controller due to the dynamic nonlinear behaviour exhibited by the sensing device. A dynamic version of the back-error propagation algorithm was used for training the networks. The resulting closed-loop transducer had a dynamic range of ±10g and a stable behaviour for input stimuli up to ±100g.
| Original language | English |
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| Title of host publication | 2000 International Conference on Modeling and Simulation of Microsystems |
| Publisher | NSTI |
| Pages | 513-516 |
| Number of pages | 4 |
| Publication status | Published - 2000 |
| Event | International Conference on Modeling and Simulation of Microsystems - San Diego, United States Duration: 27 Mar 2000 → 29 Mar 2000 http://www.nsti.org/Nanotech2000/MSM2000/ |
Conference
| Conference | International Conference on Modeling and Simulation of Microsystems |
|---|---|
| Abbreviated title | MSM |
| Country/Territory | United States |
| City | San Diego |
| Period | 27/03/00 → 29/03/00 |
| Internet address |
Keywords
- Accelerometers
- Closed loop control systems
- Electrostatic actuators
- Feedback control
- Machine design
- Microelectromechanical devices
- Micromachining
- Nonlinear systems
- Robustness (control systems)
- Transducers, Electrostatic actuation
- Micromachined accelerometers
- Model reference control
- Multilayer perceptron (MLP) neural networks, Neural networks