Model based failure detection using test signals from linearizations: A case study

An active approach for failure detection based on the use of minimal auxiliary signals has recently been introduced for linear systems with both additive and model uncertainty. This paper discusses the extension of this approach to nonlinear systems. A nonlinear case study is performed to carefully examine this approach. Evaluation of the performance of the new test signal on the nonlinear system is discussed and an evaluation algorithm presented. The extension and its evaluation requires integration of a variety of control, simulation, and optimization software. Both the application to failure detection and the software and numerical issues involved are discussed.