dr inż. Mariusz Domżalski | Politechnika Gdańska

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dr inż. Mariusz Domżalski

Kontakt:

email:
mariusz.domzalski@pg.edu.pl
strona:
https://mostwiedzy.pl/mariusz-domzalski,20022-1

Zajmowane stanowiska:

Adiunkt

miejsce pracy:
Katedra Systemów Decyzyjnych i Robotyki
Budynek A Wydziału Elektroniki, Telekomunikacji i Informatyki, EA 205
telefon:
(58) 347 14 57
dr inż. Mariusz Domżalski

Publikacje:

  1. Publikacja

    Advanced mobile vehicles and robots have long been one of the main issues in engineering. They have various applications in emergency, lifeguarding and entertainment as well as in various industrial, civil and military systems. Among them, you can distinguish robots that can move in an open environment or operate only in predetermined confined spaces. Open world robots are very demanding because they have...

  2. Publikacja

    In this work, we consider a difficult problem of state estimation of nonlinear stochastic partial differential equations (SPDE) based on uncertain measurements. The presented solution uses the method of lines (MoL), which allows us to discretize a stochastic partial differential equation in a spatial dimension and represent it as a system of coupled continuous-time ordinary stochastic differential equations (SDE). For such a system...

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  3. The goal of this paper is to present a development of a low cost flight simulator, that allows to simulate flight controls failures. Cessna 172 has been chosen as an example of a general aviation aircraft and the flight model has been implemented in Simulink. The model allows for easy integration of an experimental autopilot, using various strategies. Aerodynamic coefficients have been calculated using software called DATCOM. Such...

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  4. Publikacja

    In this paper we consider the problem of state estimation of a dynamic system whose evolution is described by a nonlinear continuous-time stochastic model. We also assume that the system is observed by a sensor in discrete-time moments. To perform state estimation using uncertain discrete-time data, the system model needs to be discretized. We compare two methods of discretization. The first method uses the classical forward Euler...

  5. Publikacja

    In this paper we consider the problem of state estimation of a dynamic system whose evolution is described by a nonlinear continuous-time stochastic model. We also assume that the system is observed by a sensor in discrete-time moments. To perform state estimation using uncertain discrete-time data, the system model needs to be discretized. We compare two methods of discretization. The first method uses the classical forward Euler...

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