This paper deals with the control of uninterruptible power supplies via the combination of repetitive and resonant controllers. Combining the controllers is motivated by performance criteria: while ...the resonant controller is designed to guarantee asymptotic tracking of the reference, a good level of disturbance rejection and dynamic performance is achieved by the repetitive controller. Complementary filters will be used to integrate the controllers so that a simple implementation strategy is devised. A numerical example evidencing the benefits of the proposed approach is presented.
Direct synthesis of recursive digital filters, whose characteristic function belongs to the new IIR filters class, is described in this article. Attenuation characteristic in the passband lies ...between the Butterworth's and the Elliptic's attenuation characteristics. All zeros of transfer function are placed on the unit circle so that the condition for complementary decomposition is fulfilled. Complementary decomposition into parallel connection of two allpass filters is performed. Then, lowpass filter is obtained summing these two filters and its complementary highpass filter - by their subtraction. The main advantage of this kind of filters is its smaller sensitivity to digital word length change compared to standard filters.
Stability is the key to maintain and control the drone, which is challenged by significant noise from drone motors during operation. The paper presents the Kalman filter and Complementary filter ...based on the quaternion to optimize drone stability. An exponential moving average (EMA) filter is used to minimize the significant vibration noise inside angular rates. The designed models optimize the misleading data from the Inertial Measurement Unit (IMU) sensor on the drone caused by noise. A real test bench was constructed to verify the proposed methods. An MPU 6050 (triaxial accelerometer and triaxial gyroscope) is equipped with a Racing Drone; then, the sensor data is logged in a MicroSD Card for signal analysis. The results demonstrate that the Complementary filter attenuates variation due to the noise, but it has an issue with drift. On the other hand, the Kalman filter accomplishes more stable output surrounding the drone's balanced point.
Another FIR lattice structure Roy, S. C. Dutta; Vishwanath, R.
International journal of circuit theory and applications,
07/2005, Letnik:
33, Številka:
4
Journal Article
The purpose of this study was to investigate if tracking of kinematical parameters (longitudinal acceleration, velocity and pitch angle) in swimming sport is feasible using data acquired with ...inertial sensors: accelerometer and gyroscope. Video data analysis combined "video + inertial sensor" and "inertial sensors only" methods are presented for estimation of kinematical parameters. The equation for estimation of longitudinal acceleration from inertial sensors data is derived and complementary filter for estimation of pitch angle variation is proposed. The inertial sensor based kinematical parameters are compared with video data analysis and electromagnetic tracking system derived parameters.
Orientation estimation is very important for development of unmanned aerial systems (UASs), and is performed by combining data from several sources and sensors. Kalman filters are widely used for ...this task, however they typically assume linearity and Gaussian noise statistics. While these assumptions work well for high-quality, high-cost sensors, it does not work as well for low-cost, low-quality sensors. For low-cost sensors, complementary filters can be used since no assumptions are made with regards to linearity and noise statistics. In this paper, the concepts of filtering based on fractional-order calculus are applied to the complementary filter, and the efficacy of non-integer-order filtering on systems with non-gaussian noise is explored with good success.
GPS aided IMU for Unmanned Air Vehicles1 Vasconcelos, J.F.; Calvário, J.; Oliveira, P. ...
IFAC Proceedings Volumes,
July 2004, Letnik:
37, Številka:
8
Journal Article
This paper presents the development of a strapdown navigation system to determine the pose (position and attitude) of unmanned air vehicles, using GPS, accelerometers, magnetometers and rate gyros ...triads. The current work resorts to complementary filtering to implement a navigation system developed on Earth coordinates and Euler angles. Special features include bias estimation and removal in inertial sensors. An attitude aiding device, referredto as Magneto-Pendular Sensor, is introduced and detailed. Multirate filter synthesis is outlined, and a time-varying attitude transformation is briefly discussed. The navigation system performance is evaluated in simulationusing a typical model-scale helicopter maneuver.
The problem of designing and implementing filters able to satisfy high precision requirements in the estimate of the depth of variable configuration unmanned underwater vehicles for marine science ...applications is tackled in this paper. Two classes of modelbased filters are considered. A conventional extended Kalman filter is compared to a complementary filter able to complement the information at low frequency supplied by the depth-meter with the information at high frequency given by the dynamic model of the system. Both the filters have been tested on real data recorded during at sea trials of Romeo, the variable configuration ROV developed by CNR-IAN. An extended record and discussion of experimental results is reported.
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