This paper considers black-and grey-box continuous-time transfer function estimation from frequency response measurements. The first contribution is a bilinear mapping of the original problem from the imaginary axis onto the unit disk. This improves the numerics of the underlying Sanathanan-Koerner iterations and the more recent instrumental-variable iterations. Orthonormal rational basis functions on the unit disk are utilized. Each iteration step necessitates a minimal state-space realization with these basis functions. One such derivation is the second contribution. System identification with these basis functions yield zero-pole-gain models. The third contribution is an efficient method to express transfer function coefficient constraints in terms of the orthonormal rational basis functions. This allows for estimating transfer function models with arbitrary relative degrees (including improper models), along with other fixed and bounded parameter values. The algorithm is implemented in the tfest function in System Identification Toolbox (Release 2016b, for use with MATLAB) for frequency domain data. Two examples are presented to demonstrate the algorithm performance.

This paper investigates application of model-based fault detection techniques on wind turbines. Fault residuals are generated through physically redundant sensors, parity equations and common filtering methods. Up-down counters are used for decisioning on these fault residuals. These simple counters are commonly used in the aerospace industry to improve missed detection rates. These techniques constitute an easily implementable fault detection and isolation system on an industrial turbine. The performance of the developed algorithm is evaluated on a model of 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.

Recent work has demonstrated the benefits of preview wind measurements for turbine control. This paper investigates the basic design trade-offs between turbine performance, preview time, and pitch actuator rate limits. A Region 3 rotorspeed tracking problem is formulated in continuous-time as an optimal control problem using a simple one-state rigid body turbine model. The exact, analytical solution to this problem provides insight into the fundamental performance limits. These analytical results are compared with the performance of an H∞ preview controller simulated on a higher fidelity, nonlinear turbine model with realistic wind sensor models. The performance versus preview time characteristics of the H∞ controllers are in agreement with the predictions from the lower fidelity model. Thus the analytical results obtained with the low-order model can provide design guidelines for the use of preview information in turbine control.