W3C | | Fault Detection | W3D | SALA BIANCA | 15:30―16:50 | SALA TURCA | Roland Siegwart, Switzerland | CHAIR | | Jean-Claude Gentina, France | CO-CHAIR | Francesco Basile, Italy | Automated, Integrated Modules for Fluid Handling, Thermal Cycling and Purification of DNA Samples for High Throughput Sequencing and Analysis
Deirdre R. Meldrum, University of Washington, William H. Pence, Stephen E. Moody, David L. Cunningham, Orca Photonic Systems, Mark Holl, University of Washington, Peter J. Wiktor, Engineering Arts, Mohan Saini, Matthew P. Moore, Ling-Sheng Jang, Molly Kidd, Charles Fisher, Andrew Cookson, University of Washington, USA
Over the past 5 years the Genomation Laboratory at the University of Washington has developed an automated fluid handling system called "Acapella" to prepare microliter reactions for genome analysis. Reactions such as restriction enzyme digests, polymerase chain reactions (PCRs), and sequencing reactions are … | 15:30―15:50 | Coulomb and Viscous Friction Fault Detection with Application to a Pneumatic Actuator
W.B. Dunbar, R.A. de Callafon, J.B. Kosmatka, UC San Diego, USA
Generally fault detection is the process of monitoring a physical dynamic system accompanied by confirmation and assessment of any degradation of system performance. These systems are modelled and terms that are representative of a specific fault are identified and monitored for detection. In this paper a fault detection algorithm is developed to isolate and detect friction changes in a high precision positioning mechanism. The designed fault detection algorithm addresses dynamic model estimation dynamic filtering and recursive parameter estimation techniques to monitor on-line friction changes. The procedure is illustrated on a high precision servo pneumatic cylinder that drives a translational air bearing apparatus designed to permit the addition of friction. Side loading of the cylinder rod …
| Control of Bioconvection and Its Mechanical Application
Akitoshi Itoh, Hideki Toida, Tokyo Denki University, Japan
High-density culture medium of protozoa autonomously generates bioconvection because of its property of negative gravitaxis and of its density heavier than the culture medium. Many species of protozoa also have the property of negative galvanotaxis. Therefore, this study aims to control bio-convection by applying the electrical field and to apply bioconvection for the energy source or the mechanical power source. In this study, downward flow of bio-convection was controlled by the negative electrode allay installed on the top plate. The results show that the position of the downward flow can be controlled by this system. As an example of the mechanical application, small seesaw was continuously driven by the controlled downward flow. | 15:50―16:10 | Fault Detection for Wheeled Mobile Robots with Parametric Uncertainty
W.E. Dixon, Oak Ridge National Laboratory, I.D. Walker, D.M. Dawson, Clemson University, USA
In this paper we develop a new method for Wheeled Mobile Robot (WMR) fault detection. Specifically we develop kinematic and dynamic models of the WMR in the presence of faults such as a change in the wheel radius (e.g. deformation broken spoke flat tire) or general kinematic disturbances that model slipping or skidding faults. Utilizing the WMR models we employ a torque filtering technique to develop a prediction error based fault detection residual. The structure of the prediction error allows for fault detection despite parametric uncertainty in the WMR model. | In-Pipe Inch-Worm Pneumatic Flexible Robot
A. Manuello Bertetto, M. Ruggiu, Università di Cagliari, Italy
A pneumatic flexible robot prototype for pipes inspection was built. A dynamic model which takes into account the flexibility, damping and friction was developed. Numerous experiments were carried out in order to characterize the robot and in order to provide the input for the numerical model. The model was validated by comparing the experimental and numerical robot gait in time. The robot motion for different pipes network geometry is presented.
| 16:10―16:30 | Minimal Resource Allocating Networks for Aircraft SFDIA
Mario L. Fravolini, Università di Perugia, Italy, Giampiero Campa, Marcello Napolitano, West Virginia University, USA, Yongkyu Song, Hankuk Aviation University, Korea
This paper presents an on-line learning approach for the problem of sensor failure detection, identification and accommodation (SFDIA) for aircraft systems using Neural Networks (NNs). The SFDIA scheme exploits the analytical redundancy of the system to provide sensor validation capability to a measurement device by employing learning NNs as on-line non-linear approximators. In the context of online learning some issues are of critical importance as learning speed, number of parameters to be updated, and stability of the learning algorithm. To address these problems a Minimal Resource Allocating Network (MRAN) is proposed featuring a fully tuned Radial Basis Functions (RBF). The purpose of this study is to evaluate … | A Time-Delayed Dynamic Inversion Scheme for Mechatronic Control of Hydraulic Systems
Klaus Six, Ty A. Lasky, Bahram Ravani, University of California at Davis, USA
A method is presented for robust control of hydraulic systems. Hydraulic systems with high-fidelity electronic control are considered as a special class of mechatronic systems where mechanical motion is achieved using hydraulic actuation. In this paper such systems are referred to as hydrotronic systems. A control system is presented for such systems consisting of hybrid position/force control where the outer-loop position control is based on Time-Delay Control for robust and simplified dynamic inversion for a nonlinear system. Simulation results are presented that show advantages of the new method as compared to other methods reported in the literature.
| 16:30―16:50 | Fault Diagnosis for Nonlinear Mechanic Systems
Vladimir V. Filaretov, Alexey N. Zhirabok, Sergey A. Usoltsev, Far Eastern State Technical University, Russia
The problem of observer-based fault diagnosis in mechatronic systems is studied. To solve this problem, the following approach is suggested: replacing the initial nonlinear system by certain linear logic-dynamic system, obtaining the bank of linear logic-dynamic observers, and transforming these observes into the nonlinear ones. |
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