A Tool for Verification and Validation of Neural Network Based Adaptive Controllers for High Assurance Systems
Eighth IEEE International Symposium on High Assurance Systems Engineering, 2004. Proceedings. (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.
P. Gupta and J. Schumann, "A Tool for Verification and Validation of Neural Network Based Adaptive Controllers for High Assurance Systems," Eighth IEEE International Symposium on High Assurance Systems Engineering, 2004. Proceedings.(HASE), Tampa, Florida, 2004, pp. 277-278.