Intelligent fault tolerant control for telerobotic system in operational space
Abstract (Summary)
Telerobotic systems combine conventional teleoperation with industrial automation
techniques, such as control, vision, planning, etc, to improve work efficiency, and have
been expanding their applications from hazardous and remote areas to unstructured
industrial uses. Unstructured environments and uncertainties in task space require humanin-the
loop control to ensure and supervise safe operation since present autonomous
capabilities cannot handle the vast range of tasks and uncertainties. The inherent
characteristics of telerobotic systems make operational faults more likely, and require
autonomous fault detection, isolation (FDI) and recovery abilities since the nature of task
space makes it difficult for human operators to detect and recover from faults in a timely
manner.
This dissertation addresses the issues of developing operational fault detection, isolation,
and recovery strategies, and combines the developed methodologies with overall
telerobotic system design. First, the framework for FDI and the associated supervisory
control scheme are proposed to effectively integrate the FDI approaches into telerobotic
systems. Secondly, for the generalization of the proposed FDI methodologies, the
characteristics of operational faults and the relevant sensor signals are classified, and then
typical operational faults, which can represent the other operational faults and telerobotic
systems, are selected using classification and appropriate criteria. Next, the fault detection
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methodologies for the selected operational faults are proposed considering the
characteristics of the sensory data. In this way, the proposed methodologies are
generalized for operational FDI of telerobotic systems. The proposed methodologies are
tested with an experimental telerobotic system or a computer simulation, and test results
demonstrate the methodologies are feasible.
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Bibliographical Information:
Advisor:
School:The University of Tennessee at Chattanooga
School Location:USA - Tennessee
Source Type:Master's Thesis
Keywords:
ISBN:
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