A comparative analysis of fault detection schemes for stochastic continuous-time dynamical systems

This paper addresses a comparative analysis of the existing schemes for fault detection in continuous-time stochastic dynamical systems. Such schemes prove to be efficient when dealing with specific types of fault functions; on the other hand, they show very different performance sensitivity when dealing with new fault profiles and system noise. The study suggests the use of a combined scheme, supervised by a high level decision rule set

Control optimization, stabilization and computer algorithms for aircraft applications

The analysis and design of complex multivariable reliable control systems are considered. High performance and fault tolerant aircraft systems are the objectives. A preliminary feasibility study of the design of a lateral control system for a VTOL aircraft that is to land on a DD963 class destroyer under high sea state conditions is provided. Progress in the following areas is summarized: (1) VTOL control system design studies; (2) robust multivariable control system synthesis; (3) adaptive control systems; (4) failure detection algorithms; and (5) fault tolerant optimal control theory

Entanglement Stabilization using Parity Detection and Real-Time Feedback in Superconducting Circuits

Fault tolerant quantum computing relies on the ability to detect and correct errors, which in quantum error correction codes is typically achieved by projectively measuring multi-qubit parity operators and by conditioning operations on the observed error syndromes. Here, we experimentally demonstrate the use of an ancillary qubit to repeatedly measure the $ZZ$ and $XX$ parity operators of two data qubits and to thereby project their joint state into the respective parity subspaces. By applying feedback operations conditioned on the outcomes of individual parity measurements, we demonstrate the real-time stabilization of a Bell state with a fidelity of $F\approx 74\%$ in up to 12 cycles of the feedback loop. We also perform the protocol using Pauli frame updating and, in contrast to the case of real-time stabilization, observe a steady decrease in fidelity from cycle to cycle. The ability to stabilize parity over multiple feedback rounds with no reduction in fidelity provides strong evidence for the feasibility of executing stabilizer codes on timescales much longer than the intrinsic coherence times of the constituent qubits.Comment: 12 pages, 10 figures. Update: Fig. 5 correcte

Final report on the development of methodologies for the detection of system failures, for the design of fault-tolerant control systems, and for the analysis of systems containing switches and subject to abrupt changes.

"March 1984."Bbliography: leaves 14-15.ONR Grant N00014-77-C-022

FD-ZKF: A Zonotopic Kalman Filter optimizing fault detection rather than state estimation

Enhancing the sensitivity to faults with respect to disturbances, rather than optimizing the precision of the state estimation using Kalman Filters (KF) is the subject of this paper. The stochastic paradigm (KF) is based on minimizing the trace of the state estimation error covariance. In the context of the bounded-error paradigm using Zonotopic Kalman Filters (ZKF), this is analog to minimize the covariation trace. From this analogy and keeping a similar observer-based structure as in ZKF, a criterion jointly inspired by set-membership approaches and approximate decoupling techniques coming from parity-space residual generation is proposed. Its on-line maximization provides an optimal time-varying observer gain leading to the so-called FD-ZKF filter that allows enhancing the fault detection properties. The characterization of minimum detectable fault magnitude is done based on a sensitivity analysis. The effect of the uncertainty is addressed using a set-membership approach and a zonotopic representation reducing set operations to simple matrix calculations. A case study based on a quadruple-tank system is used both to illustrate and compare the effectiveness of the results obtained from the FD-ZKF approach compared to a pure ZKF approachPostprint (author's final draft

Sensor Fault Detection and Diagnosis: Methods and Challenges

As modern industrial and physical systems evolve to enhance their reliability, sensor faults emerge as a critical challenge, posing a potential weak link in integrated health management. Redundancies in hardware sensors have become a common approach to mitigate these issues and bolster overall system reliability. However, this solution brings about higher system costs, augmented hardware, and increased complexity in system control. Consequently, there is a growing focus on research aimed at comprehending various sensor faults to enhance the effectiveness of sensor fault detection and diagnosis (FDD). This paper delves into the advancements in sensor fault diagnosis methodologies, outlines prevalent challenges, and identifies promising avenues for further research in the implementation of sensor FDD systems