Share Email Print
cover

Proceedings Paper

Computational methods for the verification of adaptive control systems
Author(s): Ravi K. Prasanth; Jovan Boskovic; Raman K. Mehra
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Intelligent and adaptive control systems will significantly challenge current verification and validation (V&V) processes, tools, and methods for flight certification. Although traditional certification practices have produced safe and reliable flight systems, they will not be cost effective for next-generation autonomous unmanned air vehicles (UAVs) due to inherent size and complexity increases from added functionality. Affordable V&V of intelligent control systems is by far the most important challenge in the development of UAVs faced by both commercial and military aerospace industry in the United States. This paper presents a formal modeling framework for a class of adaptive control systems and an associated computational scheme. The class of systems considered include neural network-based flight control systems and vehicle health management systems. This class of systems and indeed all adaptive systems are hybrid systems whose continuum dynamics is nonlinear. Our computational procedure is iterative and each iteration has two sequential steps. The first step is to derive an approximating finite-state automaton whose behaviors contain the behaviors of the hybrid system. The second step is to check if the language accepted by the approximating automaton is empty (emptiness checking). The iterations are terminated if the language accepted is empty; otherwise, the approximation is refined and the iteration is continued. This procedure will never produce an "error-free" certificate when the actual system contains errors which is an important requirement in V&V of safety critical systems.

Paper Details

Date Published: 9 August 2004
PDF: 9 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.546128
Show Author Affiliations
Ravi K. Prasanth, Scientific Systems Co., Inc. (United States)
Jovan Boskovic, Scientific Systems Co., Inc. (United States)
Raman K. Mehra, Scientific Systems Co., Inc. (United States)


Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)

© SPIE. Terms of Use
Back to Top