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D. Barroso Plata
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Controllers currently used by aerospace vehicles such as helicopters and aircraft are able to reject almost completely the disturbances introduced by wind in their attitude and position. Once attenuated, wind gusts just create some random, low amplitude oscillations in the vehicle, whose more severe consequence in common flight scenarios is a reduction in crew and passengers comfort. However, for certain high-precision operations, these oscillations can put the mission at risk. This is the case for rescue helicopters, which need to hover over precise spots in the sea or mountains to allow personnel to assist injured people in difficult-access areas. In many occasions, the accuracy with which helicopters are able to hold a desired position in adverse weather conditions is not enough to safely perform a rescue mission.
The disturbance rejection performance of helicopters can be improved by providing their controllers with angular acceleration information of the vehicle. Although angular acceleration sensors are available on the market, their current cost and weight prevent their widespread use.
This master thesis covers the design and testing of a novel estimation method for angular acceleration in aerospace vehicles based on linear acceleration measurements. The proposed estimator is a Stationary Kalman Filter with Modified Input (MISKF), which outperforms current approaches found in industry in terms of accuracy and time delay, while being lightweight and Linear-Time-Invariant (LTI). This observer relies only on gyroscopes and linear accelerometers, which are usually present in most vehicles. In addition to this, it does not require the dynamic model of the system in which it is used, nor the accurate position of its Center of Gravity (C.G.). These advantages make the MISKF applicable in a broad range of aerospace vehicles, including helicopters. The proposed observer is compared to other angular estimation methods such as speed differentiators using real flight data, showing a faster convergence and lower noise amplification, as well as to other observers like an Extended Kalman Filter (EKF), leading to similar performance while being more compact and lightweight. ...
The disturbance rejection performance of helicopters can be improved by providing their controllers with angular acceleration information of the vehicle. Although angular acceleration sensors are available on the market, their current cost and weight prevent their widespread use.
This master thesis covers the design and testing of a novel estimation method for angular acceleration in aerospace vehicles based on linear acceleration measurements. The proposed estimator is a Stationary Kalman Filter with Modified Input (MISKF), which outperforms current approaches found in industry in terms of accuracy and time delay, while being lightweight and Linear-Time-Invariant (LTI). This observer relies only on gyroscopes and linear accelerometers, which are usually present in most vehicles. In addition to this, it does not require the dynamic model of the system in which it is used, nor the accurate position of its Center of Gravity (C.G.). These advantages make the MISKF applicable in a broad range of aerospace vehicles, including helicopters. The proposed observer is compared to other angular estimation methods such as speed differentiators using real flight data, showing a faster convergence and lower noise amplification, as well as to other observers like an Extended Kalman Filter (EKF), leading to similar performance while being more compact and lightweight. ...
Controllers currently used by aerospace vehicles such as helicopters and aircraft are able to reject almost completely the disturbances introduced by wind in their attitude and position. Once attenuated, wind gusts just create some random, low amplitude oscillations in the vehicle, whose more severe consequence in common flight scenarios is a reduction in crew and passengers comfort. However, for certain high-precision operations, these oscillations can put the mission at risk. This is the case for rescue helicopters, which need to hover over precise spots in the sea or mountains to allow personnel to assist injured people in difficult-access areas. In many occasions, the accuracy with which helicopters are able to hold a desired position in adverse weather conditions is not enough to safely perform a rescue mission.
The disturbance rejection performance of helicopters can be improved by providing their controllers with angular acceleration information of the vehicle. Although angular acceleration sensors are available on the market, their current cost and weight prevent their widespread use.
This master thesis covers the design and testing of a novel estimation method for angular acceleration in aerospace vehicles based on linear acceleration measurements. The proposed estimator is a Stationary Kalman Filter with Modified Input (MISKF), which outperforms current approaches found in industry in terms of accuracy and time delay, while being lightweight and Linear-Time-Invariant (LTI). This observer relies only on gyroscopes and linear accelerometers, which are usually present in most vehicles. In addition to this, it does not require the dynamic model of the system in which it is used, nor the accurate position of its Center of Gravity (C.G.). These advantages make the MISKF applicable in a broad range of aerospace vehicles, including helicopters. The proposed observer is compared to other angular estimation methods such as speed differentiators using real flight data, showing a faster convergence and lower noise amplification, as well as to other observers like an Extended Kalman Filter (EKF), leading to similar performance while being more compact and lightweight.
The disturbance rejection performance of helicopters can be improved by providing their controllers with angular acceleration information of the vehicle. Although angular acceleration sensors are available on the market, their current cost and weight prevent their widespread use.
This master thesis covers the design and testing of a novel estimation method for angular acceleration in aerospace vehicles based on linear acceleration measurements. The proposed estimator is a Stationary Kalman Filter with Modified Input (MISKF), which outperforms current approaches found in industry in terms of accuracy and time delay, while being lightweight and Linear-Time-Invariant (LTI). This observer relies only on gyroscopes and linear accelerometers, which are usually present in most vehicles. In addition to this, it does not require the dynamic model of the system in which it is used, nor the accurate position of its Center of Gravity (C.G.). These advantages make the MISKF applicable in a broad range of aerospace vehicles, including helicopters. The proposed observer is compared to other angular estimation methods such as speed differentiators using real flight data, showing a faster convergence and lower noise amplification, as well as to other observers like an Extended Kalman Filter (EKF), leading to similar performance while being more compact and lightweight.