LQG/LTR, H-infinity and Mu robust controllers design for line of sight stabilization

Download

index.pdf

Date

2015

Author

Baskın, Mehmet

Metadata

Show full item record

Item Usage Stats

328
views

268
downloads

Line of sight stabilization against various disturbances is an essential property of gimbaled vision systems mounted on mobile platforms. As the vision systems are designed to function at longer operating ranges with relatively narrow field of views, the expectations from stabilization loops have increased in recent years. In order to design a good stabilization loop, high gain compensation is required. While satisfying high loop gains for disturbance attenuation, it is also required to satisfy sufficient loop stability. Structural resonances and model uncertainties put strict restrictions on achievable stabilization loop bandwidth for gimbaled vision systems. For that reason, satisfying high stabilization performance under modeling errors requires utilization of robust control methods. In this thesis, robust controller design in LQG/LTR, H-infinity and Mu frameworks is described for a two-axis gimbal. First, the modeling errors are found by investigating the locally linearized models under different conditions. Next, the performance indices and weights are determined by considering the allowable stabilization error and possible platform disturbance profile. Then generalized plants are obtained by using the nominal model and corresponding weights for three different design methods. Using these generalized plants, LQG/LTR, H-infinity and Mu controllers are synthesized. Stabilities and performances of the three designs are investigated in detail. After that, comparison of the controllers is made by investigating the robustness of corresponding closed loops. The thesis work is finished with the experimental studies and performances to validate the designed robust controllers.

Subject Keywords

Robot vision., Computer vision., Image processing., Motion control devices.

URI

http://etd.lib.metu.edu.tr/upload/12619633/index.pdf
https://hdl.handle.net/11511/25358

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Robust control for line-of-sight stabilization of a two-axis gimbal system Baskin, Mehmet; Leblebicioğlu, Mehmet Kemal (The Scientific and Technological Research Council of Turkey, 2017-01-01) Line-of-sight stabilization against various disturbances is an essential property of gimbaled imaging systems mounted on mobile platforms. In recent years, the importance of target detection from higher distances has increased. This has raised the need for better stabilization performance. For that reason, stabilization loops are designed such that they have higher gains and larger bandwidths. As these are required for good disturbance attenuation, sufficient loop stability is also needed. However, model un...
Stabilization of an image based tracking system Şener, Irmak Ece; Leblebicioğlu, Mehmet Kemal; Department of Electrical and Electronics Engineering (2015) Vision based tracking systems require high resolution images of the targets. In addition, tracking system will try to hold the tracked objects at the center of field of view of the camera to achieve robust and successful tracking. Such systems are usually placed on a platform which is to be controlled by a gimbal. The main job of the gimbal is to get rid of jitters and/or undesirable vibrations of the image platform. In this thesis, such an image platform together with its gimbal, and its controller will be...
Multi-Frame motion deblurring of video using the natural oscillatory motion of dexterous legged robots Gultekin, Gokhan Koray; Saranlı, Afşar (2019-07-18) Motion blur is a common problem for machine vision applications in legged mobile robotic platforms. Due to the oscillatory walking nature of these platforms, the cameras on them experience disturbances so that most of the captured frames are motion blurred. Motion blur results in loss of information in individual image frames and therefore makes single-frame deblurring an ill-posed problem. The variation in the magnitude of motion blur in consecutive video frames can be exploited to better restore these fra...
FPGA-based infrared image deblurring using angular position of IR detector Doner, Tugay; GÖKCEN, DİNÇER (Springer Science and Business Media LLC, 2020-08-01) The motion of the object or the infrared (IR) imaging system during the integration time causes blurring of the IR image. This study covers real-time field programmable gate array (FPGA)-based deblurring for IR detectors, and an inertial measurement unit (IMU) was used to quantify the blur caused by the IR detector movement. Point spread function for each pixel was calculated using the angular position data of the IR detector obtained from IMU. Both spatially invariant and spatially variant blur cases can b...
Visual object detection and tracking using local convolutional context features and recurrent neural networks Kaya, Emre Can; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2018) Visual object detection and tracking are two major problems in computer vision which have important real-life application areas. During the last decade, Convolutional Neural Networks (CNNs) have received significant attention and outperformed methods that rely on handcrafted representations in both detection and tracking. On the other hand, Recurrent Neural Networks (RNNs) are commonly preferred for modeling sequential data such as video sequences. A novel convolutional context feature extension is introduc...

Citation Formats

M. Baskın, “LQG/LTR, H-infinity and Mu robust controllers design for line of sight stabilization,” M.S. - Master of Science, Middle East Technical University, 2015.