4 research outputs found
Hibadetektálás korszerű analitikus módszerei járműipari alkalmazásokkal = Advanced analytic methods to fault detection with application to vehicle systems
1) A rendszer modelljĂ©nek invertálásán alapulĂł detektálĂłszűrĹ‘k tulajdonságainak kutatása során kapott eredmĂ©nyek, ideĂ©rtve elsĹ‘sorban az inverz geometriai tulajdonságait Ă©s az inverz dinamika előállĂtására vonatkozĂł mĂłdszereket, lehetĹ‘vĂ© tettĂ©k az optimális zavargyengĂtĂ©s mĂłdszerĂ©nek a zavarokkal terhelt hibahatások teljes szĂ©tcsatolása rĂ©vĂ©n törtĂ©nĹ‘ alkalmazását az irodalom által eddig nem ismert mĂłdokon. Ezzel kapcsolatos legfontosabb eredmĂ©nyĂĽnk az inverz dinamikájának on-line becslĂ©sĂ©re Ă©pĂĽlĹ‘ H-infinity optimális szűrĂ©s mĂłdszerĂ©nek kidolgozása volt, ami jelentĹ‘s nemzetközi visszhangot kiváltĂł, elismert, Ăşj tudományos eredmĂ©nyek megalkotásához vezetett. 2) A szakterĂĽlet kutatĂłit általánosan Ă©rintĹ‘ jelentĹ‘s tudományos eredmĂ©ny a Draper Lab. munkatársaival vĂ©gzett kutatási tevĂ©kenysĂ©g rĂ©vĂ©n szĂĽletett folyĂłirat közlemĂ©ny, amely a dinamikus rendszerekben Ă©s a kĂ©p illetve jelfeldolgozásban használatos detektálási mĂłdszerek eddig kĂĽlönállĂłnak vĂ©lt elmĂ©leti mĂłdszereit helyezi közös alapokra, az invariáns alterek geometriai elmĂ©letĂ©nek közös alapjaira. 3) JelentĹ‘s Ă©rdeklĹ‘dĂ©st kiváltĂł eredmĂ©nyĂĽnk az elosztott dinamikus rendszerekben az állapotbecslĂ©s hibatűrĂ©sĂ©nek Ă©s performancia mutatĂłinak javĂtására alkalmazhatĂł elosztott szűrĂ©si mĂłdszer kidolgozása, amely a szövetsĂ©gi (federated) szűrĹ‘bankok továbbfejlesztĂ©se rĂ©vĂ©n jött lĂ©tre. | 1) The novel theory of detection filters, based on the idea of direct input reconstruction, which relies on the inverse representation of the system, can be used to construct novel filter structures, such as those which combine the advantages of optimal disturbance suppression and exact fault decoupling. The research also helped to clarify the geometric principles of the inverse. The algebraic-geometric methods can be used for the construction of the inverse. The most important result is the development of the H-infinity filtering method which is capable for optimally enhanced disturbance cancellation and exact fault decoupling based on the estimation of the inverse state. 2) The joint research with co-workers at Draper Laboratory has revealed a number of methodological parallelisms and similarities, as well as differences, in the game theoretic, stochastic, and geometric subspace formulations and solution approaches to robust detection in dynamic systems and in signal processing. It is a synthesizing result deserving the attention of both the control and the signal processing community. 3) The decentralized approach to state estimation of distributed dynamical systems over unreliable communication networks subject to uncertain and limited measurements has been addressed by federated filtering. The solution enhances fault tolerance and filter performance in sparsely distributed dynamical systems
Ultra-tight GPS/IMU Integration based Long-Range Rocket Projectile Navigation
Accurate navigation is important for long-range rocket projectile’s precise striking. For getting a stable and high-performance navigation result, a ultra-tight global position system (GPS), inertial measuring unit integration (IMU)-based navigation approach is proposed. In this study, high-accuracy position information output from IMU in a short time to assist the carrier phase tracking in the GPS receiver, and then fused the output information of IMU and GPS based on federated filter. Meanwhile, introduced the cubature kalman filter as the local filter to replace the unscented kalman filter, and improved it with strong tracking principle, then, improved the federated filter with vector sharing theory. Lastly simulation was carried out based on the real ballistic data, from the estimation error statistic figure. The navigation accuracy of the proposed method is higher than traditional method.
State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties
State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-membership uncertainties can be taken into consideration simultaneously. Different solutions for implementing these estimation algorithms in distributed networked systems are presented