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Ron J. Patton
Researcher at University of Hull
Publications - 359
Citations - 20222
Ron J. Patton is an academic researcher from University of Hull. The author has contributed to research in topics: Fault detection and isolation & Robustness (computer science). The author has an hindex of 57, co-authored 351 publications receiving 19210 citations. Previous affiliations of Ron J. Patton include Universities UK & York University.
Papers
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Book ChapterDOI
Interpretation of Trained Neural Networks by Rule Extraction
TL;DR: The paper focuses on the problem of rule extraction from neural networks, with the aim of transforming the knowledge captured in a trained neural network into a familiar form for human user to develop human friendly shells for neural network based systems.
Journal ArticleDOI
Decentralized Output Sliding-Mode Fault-Tolerant Control for Heterogeneous Multiagent Systems
TL;DR: A continuous fault-tolerant protocol in the observer-based integral sliding-mode design is developed to guarantee the asymptotic stability of MASs and the ultimate boundedness of the estimation errors.
Proceedings ArticleDOI
Polytopic and TS models are nowhere dense in the approximation model space
TL;DR: It is shown that the set of functions, consisting of polytopic or TS models constructed from finite number of components, is nowhere dense in the approximation model space, if that is defined as a subset of continuous functions.
Journal ArticleDOI
Distributed Fault-Tolerant Consensus Tracking Control of Multi-Agent Systems Under Fixed and Switching Topologies
TL;DR: Two kinds of distributed fault-tolerant consensus tracking control schemes with average dwelling time technique are developed to guarantee the mean-square exponential consensus convergence of multi-agent systems, respectively, on the basis of the relative neighboring output information as well as the estimated information in fault estimation.
Journal ArticleDOI
Robust fault estimation using an LPV reference model: ADDSAFE benchmark case study
TL;DR: In this paper, a mixed H − / H ∞ linear parameter varying (LPV) fault estimator using an LPV reference estimator is proposed to detect yaw rate sensor faults in the Air Data Inertial Reference System in the presence of parametric uncertainties.