Derivation and Analysis of a State-Space Model for Transient Control of Liquid-Propellant Rocket Engines

Pérez-Roca, Sergio; Langlois, Nicolas; Marzat, Julien; Piet-Lahanier, Hélène; Galeotta, Marco; Farago, François; Gonidec, Serge Le

doi:10.1109/icmae.2018.8467617

Cited by 8 publications

(12 citation statements)

References 8 publications

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“…Describing functions have been used in one reference [47]; in fact most authors have linearised their nonlinear models about steady-state points [29,31,24,40,41,42,43,44,5,26,45], which limits representativeness to a narrow region around those points, as explicitly stated by [43] for instance. The only control-oriented nonlinear modelling approaches present in the literature dealt with engine performance simulations [48,51,49], state-space analysis [50], OL optimisation [36,54,55], neural networks [52,53] and hybrid models [56]. These nonlinear models are representative in a wider region than linearised ones but imply a higher complexity.…”

Section: Summary and Discussionmentioning

confidence: 99%

“…This consists in the only nonlinear model found, on which a control algorithm has been designed (even if it is in OL), as explained later in Section 4. Pérez-Roca et al [56] presented a nonlinear LPRE statespace modelling approach aiming at filling this gap of LPRE CL control based on nonlinear models. The model is representative of the GG-cycle Vulcain engine, but the procedure can be extrapolated to other engines and cycles.…”

Section: Nonlinear Modellingmentioning

confidence: 99%

“…Apart from the fact that not many transient control studies [23] have been carried out, this discrete actuator is not normally considered as a control input, mainly because the system would become hybrid. It was considered as an input in [56], where it can modify engine dynamics, but its relevance in control strategies remains a matter of study.…”

Section: Sensors and Actuators Considerationsmentioning

confidence: 99%

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A survey of automatic control methods for liquid-propellant rocket engines

Pérez-Roca

Marzat

Piet-Lahanier

et al. 2019

Progress in Aerospace Sciences

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The main purpose of this survey paper is to review the field of convergence between the liquid-propellant rocketpropulsion and automatic-control disciplines. A comprehensive collection of academic works and some industrial developments are summarised and discussed, making the link to the current context of launcher reusability. The main control problem in liquid-propellant rocket engines (LPRE), the target of this survey, generally consists in tracking set-points in combustion-chamber pressure and mixture ratio, their main operating quantities. This goal is attained via the adjustment of flow-control valves while complying with operating constraints. Each aspect of control systems, ranging from modelling to the actual control techniques, is reviewed and subsequently related to the rest of aspects. The comparison of the different approaches points to the general use of linearised models about concrete operating points for deriving steady-state controllers, which in most cases are of PID type. Other more sophisticated approaches present in the literature, incorporating some nonlinear, hybrid or robust techniques, improve certain aspects of performance and robustness. Nevertheless, no fully nonlinear or hybrid frameworks, which may allow the control of a wider throttling domain, have been published. In addition, control during the thermally and structurally demanding transient phases is usually in open loop, and hence with low correction margins. This sort of control enhancements, probably together with more sophisticated monitoring architectures, would serve to extend the life of LPRE, a significant factor in their reusability. Therefore, this survey intends to draw a path for the future control design trends which will certainly be more suitable for reusable LPRE.

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Section: Summary and Discussionmentioning

confidence: 99%

Section: Nonlinear Modellingmentioning

confidence: 99%

Section: Sensors and Actuators Considerationsmentioning

confidence: 99%

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A survey of automatic control methods for liquid-propellant rocket engines

Pérez-Roca

Marzat

Piet-Lahanier

et al. 2019

Progress in Aerospace Sciences

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“…The modelling strategy used in this paper was introduced in Pérez- Roca S. et al (2018). Several types of models are employed in the control loop in this paper.…”

Section: Modellingmentioning

confidence: 99%

An MPC Approach to Transient Control of Liquid-Propellant Rocket Engines

et al. 2019

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The current context of launchers reusability requires the improvement of control algorithms for their liquid-propellant rocket engines. Their transient phases are generally still performed in open loop. In this paper, it is aimed at enhancing the control performance and robustness during the fully continuous phase of the start-up transient of a generic gas-generator cycle. The main control goals concern end-state tracking in terms of combustion-chamber pressure and chambers mixture ratios, as well as the verification of a set of hard operational constraints. A controller based on a nonlinear preprocessor and on linear MPC (Model-Predictive Control) has been synthesised, making use of nonlinear state-space models of the engine. The former generates the full-state reference to be tracked while the latter achieves the aforementioned goals with sufficient accuracy and verifying constraints for the required pressure levels. Robustness considerations are included in the MPC algorithm via an epigraph formulation of the minimax robust optimisation problem, where a finite set of perturbation scenarios is considered.

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“…The objective of our work is analogous to the investigation of Pérez-Roca et al [25], where a model predictive control (MPC) approach to control the start-up transient of a liquid rocket engine was studied. After the derivation of a suitable state-space model [26], a linear MPC controller was synthesized. The controller completes the start-up and can track the end-state references with sufficient accuracy.…”

Section: Introductionmentioning

confidence: 99%

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

Waxenegger-Wilfing¹,

Dresia²,

Deeken³

et al. 2021

IEEE Trans. Aerosp. Electron. Syst.

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Nowadays, liquid rocket engines use closed-loop control at most near steady operating conditions. The control of the transient phases is traditionally performed in open-loop due to highly nonlinear system dynamics. This situation is unsatisfactory, in particular for reusable engines. The open-loop control system cannot provide optimal engine performance due to external disturbances or the degeneration of engine components over time. In this paper, we study a deep reinforcement learning approach for optimal control of a generic gas-generator engine's continuous start-up phase. It is shown that the learned policy can reach different steady-state operating points and convincingly adapt to changing system parameters. Compared to carefully tuned open-loop sequences and PID controllers, the deep reinforcement learning controller achieves the highest performance. In addition, it requires only minimal computational effort to calculate the control action, which is a big advantage over approaches that require online optimization, such as model predictive control.

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Derivation and Analysis of a State-Space Model for Transient Control of Liquid-Propellant Rocket Engines

Cited by 8 publications

References 8 publications

A survey of automatic control methods for liquid-propellant rocket engines

A survey of automatic control methods for liquid-propellant rocket engines

An MPC Approach to Transient Control of Liquid-Propellant Rocket Engines

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

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