Combined system identification and robust control of a gimbal platform

Gimbaled imaging systems require very high performance inertial stabilization loops to achieve clear image acquisition, precise pointing, and tracking performance. Therefore, higher bandwidths become essential to meet recent increased performance demands. However, such systems often posses flexible dynamics around target bandwidth and time delay of gyroscope sensors which put certain limit to achievable bandwidths. For inertial stabilization loops, widely used design techniques have difficulty in achieving large bandwidth and satisfying required robustness simultaneously. Clearly, high performance control design hinges on accurate control-relevant model set. For that reason, combined system identification and robust control method is preferred. In the system identification step, accurate nominal model is obtained, which is suitable for subsequent robust control synthesis. Model validation based uncertainty modeling procedure constructs the robust-control-relevant uncertain model set, which facilitates the high performance controller design. Later, with skewed-mu synthesis, controller is designed which satisfies large bandwidth and robustness requirements. Finally, the experimental results show that significant performance improvement is achieved compared to common manual loop shaping methods. In addition, increased performance demands for new imaging systems are fulfilled

Proportional Fair Resource Allocation on an Energy Harvesting Downlink

This paper considers the allocation of time slots in a frame, as well as power and rate to multiple receivers on an energy harvesting downlink. Energy arrival times that will occur within the frame are known at the beginning of the frame. The goal is to optimize throughput in a proportionally fair way, taking into account the inherent differences of channel quality among users. Analysis of structural characteristics of the problem reveals that it can be formulated as a biconvex optimization problem, and that it has multiple optima. Due to the biconvex nature of the problem, a Block Coordinate Descent (BCD) based optimization algorithm that converges to an optimal solution is presented. However, finding the optimal allocation with BCD entails a computational complexity that increases sharply in terms of the number of users or slots. Therefore, certain structural characteristics of the optimal power-time allocation policy are derived. Building on those, two simple and computationally scalable heuristics, PTF and ProNTO are proposed. Simulation results suggest that PTF and ProNTO can closely track the performance of BCD which achieves a good balance between total throughput and fairness

Görev amaçlı döner kanat İHA tasarımı

TÜBİTAK EEEAG01.04.20162014 yılının Ekim ayında, TÜBİTAK desteği alınarak başlayan “Görev Amaçlı Döner Kanat İHA Tasarımı” isimli ve 114E149 kodlu TÜBİTAK-1005 projemiz, 18 ay sonra, 2016 yılının Nisan ayında sona ermiştir. Proje kapsamında döner kanat İHA sistemlerinin tasarımında kullanılan temel parametrelerin görev amaçlı bir yaklaşıkla ele alınarak en iyileştirmesi yapılmaktadır. Bu çerçevede tedarik edilen motor, pervane, batarya vb. bileşenleri test edilerek matematiksel modelleri oluşturulmuş, elde edilen modlar arasından görev amaçlı başarımın arttırılmasına yönelik parametreler eniyileştirme yöntemleri ve bilgisayar ortamındaki simülasyonlarla belirlenmiş ve elde edilen simülasyon sonuçlarına göre hava araçlarının tasarımı elde edilmiştir. Görev amaçlı tasarıma uygun olarak gerçek malzemelerle inşa edilen örnek platformlar olan döner kanatlı hibrit İHA ve döner kanatlı X5 İHA platformları uçuş testlerine tabi tutularak kullanılan yöntemlerin sağladığı faydalar ortaya konulmuştur. Ayrıca bu çalışmada, “Çoklu İnsansız Hava Aracının (İHA) Koordineli Güdümü ve Yol Planlama” isimli ve 110E192 numaralı TÜBİTAK 1001 projesi kapsamında; ODTÜ Elektrik ve Elektronik Mühendisliği Bölümünde 2011-2014 yılları arasında yapılan araştırmalardan, sabit ve döner kanat İHA sistemlerinin tasarımı, idamesi, uçurulması, koordineli güdümü ve yol planlaması ile ilgili bilgi birikimi, altyapı ve kabiliyetlerden faydalanılmıştır

Real Time Path Planning for Unmanned Air Vehicles

This study is about developing an online (real-time) path planning algorithm for multiple Unmanned Aerial Vehicles (UAV). The proposed algorithm dynamically finds the path of each vehicle by solving an optimization problem over a planning horizon. The main objective of the optimization problem is to maximize the collected amount of information from targets within a certain interval of time. The importance of the information collected from a targets, if no UAV is flying on the target, decreases with time. The proposed solution is centralized and can handle the dynamics and uncertainity in the region of interest where there are also forbidden zones into which vehicles are not supposed to enter during their missions. The solution method offered is similar to Receding Horizon method and it produces near optimum solutions based on some basic rule sets. Simulations are realized in the MATLAB environment. The planning algorithm has been tested on various scenarios, and the results are presented

Robust control for line-of-sight stabilization of a two-axis gimbal system

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 uncertainties around structural resonances impose strict restrictions on sufficient loop stability. Therefore, to satisfy high stabilization performance in the presence of model uncertainties, robust control methods are required. In this paper, a robust controller design in LQG/LTR, H-infinity, and mu-synthesis framework is described for a two-axis gimbal. First, the performance criteria and weights are determined to minimize the stabilization error with moderate control effort under known platform disturbance profile. Second, model uncertainties are determined by considering locally linearized models at different operating points. Next, robust LQG/LTR, H-infinity and mu controllers are designed. Robust stability and performance of the three designs are investigated and compared. The paper finishes with the experimental performances to validate the designed robust controllers