Search

Up-down counters are commonly used in the aerospace industry for fault detection thresholding. This paper applies the up-down counter technique to detect wind turbine faults. The thresholding problem involves a tradeoff between false alarms and missed detections. Counter based thresholding can detect smaller faults with higher probability and lower false alarms than is possible using simple constant thresholds. This improvement is achieved by effectively introducing dynamics into the thresholding logic as opposed to decisioning based on a single time step. Up down counters are applied to the development of a fault detection system for a commercial sized 4.8MW wind turbine. Realistic fault scenarios in the sensing, actuation and drivetrain subsystems are considered. It is seen that most faults can be detected with fast detection times and minimal false alarms without implementation of more complex filtering and detection techniques on residuals.

Air data probes provide essential sensing capabilities to aircraft. The loss or corruption of air data measurements due to sensor faults jeopardizes an aircraft and its passengers. To address such faults, sensor hardware redundancy is typically combined with a voting system to detect and discard erroneous measurements. This approach relies on redundancy, which may lead to unacceptable increases in system weight and cost. This paper presents an alternative, model-based approach to fault detection for a non-redundant air data system. The model-based fault detection strategy uses robust linear filtering methods to reject exogenous disturbances, e.g. wind, and provide robustness to model errors. The proposed algorithm is applied to NASA's Generic Transport Model aircraft with an air data system modeled based on manufacturer data provided by Goodrich Corporation. The fault detection filters are designed using linearized models at one flight condition. The detection performance is evaluated at a particular reference flight condition using linear analysis and nonlinear simulations.

Geometric fault detection and isolation filters are known for having excellent fault isolation, fault reconstruction and sensitivity properties under small modeling uncertainty and noise. However they are assumed to be sensitive to model uncertainty and noise. This paper proposes a method to incorporate model uncertainty into the design. First, a geometric filter is designed on the nominal plant. Next a robust model matching problem is solved to design a filter that robustly matches the performance of the geometric filter over the set of uncertain plants. Several existing methods for robust filter synthesis are described to solve the robust model matching problem. It is then shown that the robust model matching problem has an interesting self-optimality property for multiplicative input uncertainty sets. Finally, an aircraft dynamics example is presented to detect and isolate aileron actuator faults to asses the performance of the geometric filter.

A recent architecture based on the Youla parameterization is analyzed for the nominal and uncertain case. This special architecture is characterized by a separation principle for the controller. In this paper, several stability results that allow to extend the structure to the integrated control/filter approach are presented. Two algorithms based on the recursive design and nesting of the integrated controller are also outlined.

This paper presents a survey of the control techniques being used by aviation industry in Brazil, Europe, Russia and the United States of America to design flight control laws for fixed-wing aircraft.

This paper describes application of parameter‐dependent control design methods to a turbofan engine. Parameter‐dependent systems are linear systems, whose state‐space descriptions are known functions of time‐varying parameters. The time variation of each of the parameters is not known in advance, but is assumed to be measurable in real‐time. Three linear, parameter‐varying (LPV) approaches to control design are discussed. The first method is based on linear fractional transformations which relies on the small gain theorem for bounds on performance and robustness. The other methods make use of either a single (SQLF) or parameter‐dependent (PDQLF) quadratic Lyapunov function to bound the achievable level of performance. The latter two techniques are used to synthesize controllers for a high‐performance turbofan engine. A LPV model of the turbofan engine is constructed from Jacobian linearizations at fixed power codes for control design. The control problem is formulated as a model matching problem in the ℋ︁∞and LPV framework. The objective is decoupled command response of the closed‐loop system to pressure and rotor speed requests. The performance of linear, ℋ︁∞point designs are compared with the SQLF and PDQLF controllers. Nonlinear simulations indicate that the controller synthesized using the SQLF approach is slightly more conservative than the PDQLF controller. Nonlinear simulations with the SQLF and PDQLF controllers show very robust designs that achieve all desired performance objectives. Copyright © 2002 John Wiley & Sons, Ltd.

Trigger line models for the behaviour within the pseudoelastic hysteresis of shape memory alloys are considered in the analysis of the dynamic response of a cantilevered beam constrained by shape memory wires. Quantitative results of damping and shift in natural frequencies of the structure are presented. The results are compared to theoretical predictions of the effect of inner hysteresis loops on structural dynamics. The comparison suggests that there may be two trigger lines, one for loading and one for unloading, within the hysteresis loop.

The structured singular value (μ) synthesis technique is used to design controllers for the Active Mass Damper (AMD) Benchmark problem. The motivation for using μ synthesis is its ability to directly incorporate performance and robustness objectives into a multivariable control design framework. In addition to stated performance objectives, robustness of the controllers to high-frequency unmodelled dynamics (the neglected high-frequency modes of the evaluation model), modelling error in the actuator dynamics and variations in the first structural natural frequency and damping value are considered in the design. The resulting controller achieves similar performance levels on the nominal evaluation model and the evaluation model with significant variations in its first natural frequency and damping values. © 1998 John Wiley & Sons, Ltd.