Increasing the efficiency of wind farms is important for speeding up the transition from fossil fuels to renewable energy sources. Current wind farm control relies on maximization of power generation of individual turbines. However, research has demonstrated that plant-wide wind farm control could optimize the performance of a wind farm. Wind farm simulation tools are crucial in designing, testing, and validating wind farm controllers. Fatigue, Aerodynamics, Structures, and Turbulence Farm tool (FAST.Farm) is a recently developed multi-physics engineering tool for modeling power performance and structural loads by solving the aero-hydro-servoelastic dynamics of each individual turbine within a farm. FAST.Farm aims to balance the need for accurate modeling of the relevant physics while maintaining low computational costs. However, designing controllers in FAST.Farm lacks flexibility and interactivity compared with MATLAB/Simulink. The capabilities of FAST.Farm for control design purposes can be extended through a co-simulation with MATLAB/Simulink. Therefore this thesis presents a FAST.Farm and MATLAB/Simulink interface. Consequently, this interface was used to implement and simulate wind farm controllers in FAST.Farm. FAST.Farm and MATLAB/Simulink are coupled by linking the individual Open Fatigue, Aerodynamics, Structures, and Turbulence tool (OpenFAST) instances in FAST.Farm to MATLAB with the use of an Message Passing Interface (MPI) and MATLAB Executable (MEX) functions. An Active Power Controller (APC) was implemented and simulated in FAST.Farm with the use of this interface. The APC responds to grid requirements through the control of wind farm power output. Comparing FAST.Farm and Simulator fOr Wind Farm Applications (SOWFA) simulation results of the APC shows that FAST.Farm reduces the computation time for a 10-minute simulation from 24 hours to 15 minutes, with little detriment to the accuracy of the simulation results. Although SOWFA remains the preferred validation tool, the FAST.Farm and MATLAB/Simulink interface supports developing and accelerates testing advanced closed-loop control at the wind turbine and wind farm levels.

Hydrogen is a promising fuel for both reducing greenhouse gas emissions and being used as an energy carrier for renewable energy sources. The adaption of hydrogen instead of natural gas as a fuel in gas turbine combustors introduces additional challenges regarding flame stability. One instabilities is boundary layer flashback. This phenomenon occurs if the flame speed exceeds the local flow velocity. Then the flame can propagate upstream, which can result in equipment failure. Lean premixed hydrogen mixtures are more prone to boundary layer flashback because hydrogen flames have both a smaller quenching distance and higher flame speed compared to natural gas. Therefore, operating at 100% hydrogen fuel content is an enormous challenge. Active control strategies are a promising strategy to prevent and withstand possible occurrences of boundary layer flashback in gas turbine combustors. In this work, the detection, prevention, and counteraction of flashback are investigated in unconfined Bunsen burners. After an experimental analysis of suitable sensors, a tracking controller is therefore designed and different control design approaches evaluated.

Both the increase in flame fluctuations and in flame angle are reasonable as indicators for a flame moving towards flashback as the flow velocity is reduced. However, the complex nature of a flame makes it challenging to measure these effects in a flame. Four types of sensors, i.e. an ion sensor, a thermocouple, a photo-detector and a microphone, were investigated for their ability to detect flashback and to find precursors that indicate the onset of flashback. A Bunsen burner equipped with the different types of sensors was used in an experiment to determine the most suitable sensor type. Of the investigated sensors, the thermocouple is the most promising sensor for both flashback detection and use the temperature signal as a control variable. The temperature is a precursor for the onset of flashback since the temperature increases with increasing flame angle. Also, by placing multiple thermocouples in $360^oC$ configuration on the burner rim, it is possible to estimate the position, where the flame entered the burner.

A complete fault-tolerant framework to control a flashback event is proposed. This framework increases the flashback resistance of the system and it counteracts possible flashback events, which is considered as a fault in the system. A supervisor block has two functions. Firstly, the supervisor uses a fault detection method, known as trend checking, to detect flashback. Secondly, it decides which strategy should be applied, based on the temperature measurements. The fault-tolerant control strategy is threefold. First, the prevention controller closes the loop, so it can steer away from flashback conditions by rejecting disturbances and tracking a desired reference path using the temperature data. Different tuning methodologies based on the traditional proportional and integral (PI), linear-quadratic-integral (LQI) and pole placement regulator (PPR) are explored for this purpose. The robustness of the proposed controller was verified through loop shaping interpretation. However, flashback could be consider as an stochastic process that still could be triggered. Therefore, the second task is to detect present flashback events and apply counteraction to oppose the fault. A design is proposed by the injection of pressurized air upstream of the burner rim to push back the flame by diluting the boundary layer and increasing the flow speed. A proof-of-concept is validated in the experimental set-up as a possible and feasible counteraction. The third task is a final safety measure. A safety switch would be applied to shut off the fuel supply to fail safe after a potential unsuccessful counteraction attempt. The fault-tolerant control framework was simulated in Simulink for a demonstration purpose, where the models were identified from experimental data.

The proposed fault tolerant control framework is intended to increases the flashback resistance of the system by being more robust towards disturbances and flashback events that would normally require a restart of the system. Its potential to do so has been confirmed by simulations. However, further research on the prediction of flashback and controller implementation are still required to run burners on 100% hydrogen without flashback.

Noise pollution is a major health threat to society. Active noise control systems that attenuate noise through open windows have the potential to create quieter homes while maintaining ventilation and sight. Such systems are commonly realized with closed-loop LMS algorithms. However, these algorithms require a large number of error microphones inside the room and provide only local attenuation. Using many error microphones leads to slow convergence and high computational effort, having additional disadvantages. Therefore, closed-loop active noise control algorithms are undesired for real-world application. In this study, we develop an open-loop wave-domain algorithm that converges instantaneously and operates with low computational effort. As it is open-loop, it does not require error microphones. We position a control region in the far-field that covers all directions from the aperture into the room. In the algorithm, we minimize the sound in that control region. Hence, it inherently ensures cancellation in the whole room. We derive acoustic transfer functions to obtain frequency responses of the aperture and loudspeakers. Those are used for soundfield calculation. The sum of the soundfields, from the aperture and the loudspeaker array, is then expressed in orthonormal basis functions. By minimizing this sum in least mean square sense, we can calculate the filter-weights that minimize the sound energy in the control region. Implementation of these filter-weights with block-wise processing using the Short-Time Fourier Transform generates the signals for the loudspeaker array. However, this processing induces a delay. To compensate for this algorithmic delay, two methods are compared. The first is positioning a reference microphone further in front of the aperture. The second method uses an autoregressive model for signal prediction. Both lead to a loss in attenuation performance compared to the optimal algorithm. We compare the optimal wave-domain algorithm with a LMS-based reference algorithm, as well as both the algorithmic delay compensation methods. The algorithms are tested with a sparse and grid loudspeaker array, and we use rumbler-siren, airplane, and white noise signals as incoming noise. Furthermore, we compare performance for three incident angles. Our simulation results indicate that wave-domain processing has the potential to outperform LMS-based methods in practical active noise control for apertures. More specifically, we obtain an average -10dB global reduction up to 2~kHz for all signal types with the optimal wave-domain approach. In comparison, the performance of the closed-loop algorithm ranges between -5.2 and -9.2dB, depending on the signal type. Furthermore, we indicate the limited impact of the incident angle on performance for the wave-domain algorithm. Positioning a reference microphone in front of the aperture outperforms the predictor approach in all scenarios, and its performance compares to that of the closed-loop LMS algorithms. Eventually, the absence of error microphones and inherent global control ensure that the wave-domain algorithm can be used for a practical active noise control system for apertures. Future work could improve the algorithm by reducing loss of performance with small window-sizes due to time-delay wrapping in the block-wise processing. Furthermore, a natural continuation of this study is to develop and test the wave-domain algorithm for scenarios with a moving primary noise source to further emphasize its advantage over the closed-loop LMS algorithm.