Jan Breeman

Bio: Jan Breeman is an academic researcher from National Aerospace Laboratory. The author has contributed to research in topics: Aircraft flight mechanics & Fault detection and isolation. The author has an hindex of 7, co-authored 12 publications receiving 185 citations.

A Simulation Benchmark for Integrated Fault Tolerant Flight Control Evaluation

Abstract: This paper presents a description of a large transp ort aircraft simulation benchmark that includes a suitable set of assessment criteria , for the integrated evaluation of fault tolerant flight control systems (FTFC). These syste ms consist of a combination of novel fault detection, isolation (FDI) and reconfigurable contr ol schemes. In 2004, a research group on Fault Tolerant Control, comprising a collaboration of nine European partners from industry, universities and research institutions, w as established within the framework of the Group for Aeronautical Research and Technology in Europe (GARTEUR) co-operation program. The aim of the research group, Flight Mechanics Action Group FM-AG(16), is to demonstrate the capability and viability of modern FTFC schemes when applied to a realistic, nonlinear design problem and to assess t heir capability to improve aircraft survivability. The test scenarios that are an integ ral part of the benchmark were selected to provide challenging assessment criteria to evaluate the effectiveness and potential of the FTFC methods being investigated. The application of fault reconstruction and modelling techniques based on (accident) flight data, as desc ribed in this paper, has resulted in high fidelity non-linear aircraft and fault models for t he design and evaluation of modern FTFC methods.

AUTAS: a tool for supporting FMECA generation in aeronautic systems

Abstract: The goal of the FMECA (Failure Mode, Effects and Criticality Analysis) process is to determine the consequences that failures may have on the function of a complex system. In aeronautic industries, this process is very important and must comply with international standards. Today, most of the process is performed manually. This can be problematic, since, although the basic process is not difficult, taking into account all behaviors and all the interactions between the behaviors of several components of a system can be very complex, error prone and costly. In the paper, we discuss how MBR (Model Based Reasoning) can support the process and we present a software environment which implements this concept.

RECOVER: A Benchmark for Integrated Fault Tolerant Flight Control Evaluation

Abstract: Fault tolerant flight control (FTFC), or intelligent self-adaptive control, enables improved survivability and recovery from adverse flight conditions induced by faults, damage and associated upsets. This can be achieved by ’intelligent’ utilisation of the control authority of the remaining control effectors in all axes consisting of the control surfaces and engines or a combination of both. In this technique, control strategies are applied to restore vehicle stability, manoeuvrability and conventional piloting techniques for continued safe operation and a survivable landing of the aircraft.

Handbook of Knowledge Representation

Abstract: Knowledge Representation, which lies at the core of Artificial Intelligence, is concerned with encoding knowledge on computers to enable systems to reason automatically. The Handbook of Knowledge Representation is an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field.This book is an essential resource for students, researchers and practitioners in all areas of Artificial Intelligence. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily

Identification of aerodynamic coefficients using computational neural networks

Abstract: Precise, smooth aerodynamic models are required for implementing adaptive, nonlinear control strategies. Accurate representations of aerodynamic coefficients can be generated for the complete flight envelope by combining computational neural network models with an Estimation-Before-Modeling paradigm for on-line training information. A novel method of incorporating first-partial-derivative information is employed to estimate the weights in individual feedforward neural networks for each aerodynamic coefficient. The method is demonstrated by generating a model of the normal force coefficient of a twin-jet transport aircraft from simulated flight data, and promising results are obtained.

Development of an Active Fault-Tolerant Flight Control Strategy

Abstract: This paper discusses the design of an active fault-tolerant flight control strategy for improvement of the operational control capability of the aircraft system. The research work draws expertise from actions undertaken within the European Flight Mechanics Action Group [FM-AG(16)] on fault-tolerant control, which develops a collaborative effort in Europe to create new fault-tolerant control technologies that significantly advance the goals of the aviation safety. The methodology is applied to a trimmable horizontal stabilizer runaway fault occurring in a large transport aircraft. The goal is to provide a self-repairing capability to enable the pilot to land the aircraft safely. The fault-tolerant control strategy works in such a way that once the fault is detected by the fault detection and isolation unit, a compensation loop is activated for safe recovery. A key feature of the proposed strategy is that the design of the fault-tolerant control loop is done independently of the nominal autopilot and the nominal flight control system in place. Nonlinear simulation results demonstrate the effectiveness of the proposed fault-tolerant control scheme.

Fault reconstruction using a LPV sliding mode observer for a class of LPV systems

Abstract: This paper proposes a new sliding mode observer for fault reconstruction, applicable for a class of linear parameter varying (LPV) systems. Observer schemes for actuator and sensor fault reconstruction are presented. For the actuator fault reconstruction scheme, a virtual system comprising the system matrix and a fixed input distribution matrix is used for the design of the observer. The fixed input distribution matrix is instrumental in simplifying the synthesis procedure to create the observer gains to ensure a stable closed-loop reduced order sliding motion. The ‘output error injection signals’ from the observer are used as the basis for reconstructing the fault signals. For the sensor fault observer design, augmenting the LPV system with a filtered version of the faulty measurements allows the sensor fault reconstruction problem to be posed as an actuator fault reconstruction scenario. Simulation tests based on a high-fidelity nonlinear model of a transport aircraft have been used to demonstrate the proposed actuator and sensor FDI schemes. The simulation results show their efficacy.