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Solid Launcher Dynamical Analysis and Autopilot Design
Author(s) -
Ping Sun
Publication year - 2011
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2011.01.08
Subject(s) - autopilot , aerospace engineering , computer science , aeronautics , control theory (sociology) , engineering , control (management) , artificial intelligence
The dynamics of a small solid launch vehicle has been investigated. This launcher consists of a liquid upper stage and three fundamental solid rocket boosters aligned in series. During the ascent flight phase, lateral jets and grid fins are adopted by the flight control system to stable the attitude of the launcher. The launcher is a slender and aerodynamically unstable vehicle with sloshing tanks. A complete set of six-degrees-of-freedom dynamic models of the launcher, incorporation its rigid body, aerodynamics, gravity, sloshing, mass change, actuator, and elastic body, is developed. Dynamic analysis results of the structural modes and the bifurcation locus are calculated on the basis of the presented models. This complete set of dynamic models is used in flight control system design. A methodology for employing numerical optimization to develop the attitude filters is presented. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics, propellant slosh, and flex. Later a control approach is presented for flight control system of the launcher using both State Dependent Riccati Equation (SDRE) method and Fast Output Sampling (FOS) technique. The dynamics and kinematics for attitude stable problem are of typical nonlinear character. SDRE technique has been well applied to this kind of highly nonlinear control problems. But in practice the system states needed in the SDRE method are sometimes difficult to obtain. FOS method, which makes use of only the output samples, is combined with SDRE to accommodate the incomplete system state information. Thus, the control approach is more practical and easy to implement. The resulting autopilot can provide stable control systems for the vehicle.

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