A Tool for Verification and Validation of Neural Network Based Adaptive Controllers for High Assurance Systems
Ninth IEEE International Symposium on High-Assurance Systems Engineering (HASE'05) (2004)
Mar. 25, 2004 to Mar. 26, 2004
Pramod Gupta , QSS Inc.
Johann Schumann , RIACS/NASA Ames
High reliability of mission- and safety-critical software systems has been identified by NASA as a high-priority technology challenge. We present an approach for the performance analysis of a neural network (NN) in an advanced adaptive control system. This problem is important in the context of safety-critical applications that require certification, such as flight software in aircraft. We have developed a tool to measure the performance of the NN during operation by calculating a confidence interval (error bar) around the NN's output. Our tool can be used during pre-deployment verification as well as monitoring the network performance during operation. The tool has been implemented in Simulink and simulation results on a F-15 aircraft are presented.
Pramod Gupta, Johann Schumann, "A Tool for Verification and Validation of Neural Network Based Adaptive Controllers for High Assurance Systems", Ninth IEEE International Symposium on High-Assurance Systems Engineering (HASE'05), vol. 00, no. , pp. 277-278, 2004, doi:10.1109/HASE.2004.1281757