Toward Sensor Fault Detection for Autonomous Underwater Vehicles: A Zonotopic Approach

In this work, we consider the detection of velocity sensor faults for autonomous underwater vehicles in a bounded error context. The nonlinearity of autonomous underwater vehicles is handled via a Takagi–Sugeno fuzzy technique. The fault detection is achieved by solving a zonotopic enclosure problem based on zonotopic reachability analysis. To improve fault detection performance, a novel observer structure and H<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_{-}$</tex-math></inline-formula> performance index are introduced. The performance of the presented approach is analyzed utilizing a hidden fault set. Experimental examples are given to validate the effectiveness of the presented approach.