Optimal controller based servo system design for the thrust vector control of liquid propellant engine of three stage launch vehicle

Suchitra, P.; Kurian, Priya C.; Jones, Stephen B.

doi:10.1109/aicera.2014.6908286

Cited by 7 publications

(1 citation statement)

References 13 publications

(12 reference statements)

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“…The thrust vectoring is not only used for changing the rocket attitude during powered flight, but it is also suitable for correcting both deviation from the expected trajectory and the misalignment of the thrust. As shown in Figure 1, the TVC with a single nozzle can be classified into four different categories, based on how the thrust vector is gimballed [5,6].…”

Section: Thrust Vector Controlmentioning

confidence: 99%

Thrust Vector Controller Comparison for a Finless Rocket

et al. 2023

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The paper focuses on comparing applicability, tuning, and performance of different controllers implemented and tested on a finless rocket during its boost phase. The objective was to evaluate the advantages and disadvantages of each controller, such that the most appropriate one would then be developed and implemented in real-time in the finless rocket. The compared controllers were Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG), and Proportional Integral Derivative (PID). To control the attitude of the rocket, emphasis is given to the Thrust Vector Control (TVC) component (sub-system) through the gimballing of the rocket engine. The launcher is commanded through the control input thrust gimbal angle δ, while the output parameter is expressed in terms of the pitch angle θ. After deriving a linearized state–space model, rocket stability is addressed before controller implementation and testing. The comparative study showed that both LQR and LQG track pitch angle changes rapidly, thus providing efficient closed-loop dynamic tracking. Tuning of the LQR controller, through the Q and R weighting matrices, illustrates how variations directly affect performance of the closed-loop system by varying the values of the feedback gain (K). The LQG controller provides a more realistic profile because, in general, not all variables are measurable and available for feedback. However, disturbances affecting the system are better handled and reduced with the PID controller, thus overcoming steady-state errors due to aerodynamic and model uncertainty. Overall controller performance is evaluated in terms of overshoot, settling and rise time, and steady-state error.

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Section: Thrust Vector Controlmentioning

confidence: 99%