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Autom ation S y stem s using I ndustr ial S olutions S toj an P er š in, Bor is T ov or nik Laboratory for process automation U niv ersity of M aribor, F acul ty of E l ectrical E ng ineering and C omputer S cience S metanov a 1 7 , 2 0 0 0 M aribor, S l ov enia Abstract Fault Detection and Diagnosis systems offers enhanced availability and reduced risk of(More)
Underwater vehicles are highly nonlinear and complex systems, that makes designing autopilots extremely difficult. This paper presents autotuning as a method for tuning parameters of a micro-ROV autopilot. The main benefit of this procedure is that the model of the process does not have to be known. Autotuning is often used for industrial processes but not(More)
The paper integrates demands for safe processing and fault detection techniques. An early detection of the fault occurrence is vitally important since it contributes to avoidance of product deterioration, performance degradation, major damages to the machinery itself and damages to human health or even loss of lives. Some fault detection methods using(More)
In this paper fault detection and isolation schemes using an extended Luenberger observer for non-linear systems and linear fault sensitive filters are presented. The idea is to implement both approaches on the same plant, achieve on-line fault detection and show some practical issues related to on-line fault detection implementation on a real laboratory(More)
The paper deals with multivariate statistical methods used for failure prognostics in industrial processes. Modern on-line process monitoring system should support classic fault detection, isolation and diagnosis (FDI) subsystems to avoid process down-time, increase production, optimize parameters of the production line, etc. However faults usually demand(More)