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This paper presents a robust actuator fault reconstruction scheme for linear uncertain systems using sliding mode observers. In existing work, fault reconstruction via sliding mode observers is limited to either linear certain systems subject to unknown inputs, relative degree one systems or a specific class of relative degree two systems. This paper presents a new method that is applicable to a wider class of systems with relative degree higher than one, and can also be used for systems with more unknown inputs than outputs. The method uses two sliding mode observers in cascade. Signals from the first observer are processed and used to drive the second observer. Overall, this results in actuator fault reconstruction being feasible for a wider class of systems than using existing methods. A simulation example verifies the claims made in this paper. as to whether a fault condition is present and also an attempt is made to determine its location.A useful alternative to residual generation is fault reconstruction [8-10], which not only detects and isolates the fault, but also provides an estimate of the fault so that its shape and magnitude can be better understood and more precise corrective action can be taken. However, a fault reconstruction scheme is usually designed about a model of the system. This model usually does not perfectly represent the system, as certain dynamics are either unknown or do not fit exactly into the framework of the model. These dynamics are usually represented as a class of disturbances within the model [11]. The disturbances corrupt the reconstruction, and could produce a non-zero reconstruction when there are no faults, or worse, mask the effect of a fault, producing a 'zero' reconstruction in the presence of faults. Therefore, the scheme needs to be designed so that the reconstruction is robust to disturbances.Edwards et al. [8,9] used a sliding mode observer [12] to reconstruct faults, but there was no explicit consideration of the disturbances. Tan and Edwards [13] built on the work in [8,9] and presented a design algorithm for the observer, using linear matrix inequalities (LMIs) [14], such that the L 2 gain from the disturbances to the fault reconstruction is minimized. Saif and Guan [10] aggregated the faults and disturbances to form a new 'fault' vector and used a linear observer to reconstruct the new 'fault' vector. One of the necessary conditions in [8-10, 13] is that the transfer function from the faults to the output has a relative degree of one. This limits the class of systems where the schemes [8-10, 13] are applicable.Recently, there have been developments in the area of fault reconstruction for systems with relative degree greater than one. Floquet and Barbot [15] transformed the system into an 'output information' form such that existing sliding mode observer techniques could be implemented to perfectly estimate the states in finite time and reconstruct faults. However, their algorithm does not consider disturbances (unless as in [10] the unknown inputs (faults) are a...

Despite the use of high safety standards in aircraft design and operations, accidents do occur. In a process of continuous improvement it is essential that we learn from each accident so we can take measures to prevent such accidents from happening in the future. It is often the case that an accident is the result of a sequence of, seemingly minor and often unrelated, events. The challenge is to identify the major causes, which can include deficiencies in organisational processes which may have been present well before the accident itself. This paper discusses tools which can be used to identify key organisational factors which contribute to aviation accidents. The research uses a thoroughly-investigated helicopter accident as a case study, to determine the extent to which analytical and visualisation tools can be used to assess maintenance organisational issues which contributed to the accident.

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Potential advantages offered by multichannel luminaires with regards to spectral tuning are frequently overshadowed by its design challenges, a major one being the non-uniformity in illuminance and color distribution. In this paper, we present a formulation using genetic algorithm (GA) to optimize the Light Emitting Diode (LED) placement, yielding 40% superior uniformity in illuminance and color distributions compared to existing analytical formulations, substantially reducing the reliance on optical design for this purpose. It is specifically shown that our approach is employable for circadian tuning applications, even when heavily constrained by industry specifications on panel size and minimum LED separation.