基于改进DDPG的宽速域几何可调燃烧室压力分布控制

doi:10.7527/S1000-6893.2024.31092

Abstract

Abstract:

Generally， the variable geometry combustor can ensure suitable performance of scramjets. However， its multivariate and strong coupling characteristics make it difficult to develop high-performance control algorithms， and also become an intractable problem hindering the development of the scramjet field. To solve the contradiction between control design and mechanical coupling， this paper firstly proposes a multipoint fuel injection structure for the conventional variable geometry combustor. The newly proposed structure can provide more operable inputs， thereby ensuring a theoretical ability to improve the system performance. On the basis of the multipoint fuel injection structure， a new LSTM/DDPG-based control scheme is proposed to solve the problem of distributed pressure control in the case of supersonic combustion. This scheme can effectively improve the potential performance of the scramjet at wide range velocities and in long flight time. The effectiveness of the proposed scheme is then verified with the simulation results， i.e.， the LSTM/DDPG-based control scheme can significantly optimize the combustion performance of variable geometry combustor under different operating conditions. Finally， the applicability of the proposed scheme is validated on the Hardware-In-the-Loop （HIL） simulation platform， and the pressure distribution can be effectively controlled at different expansion ratios. The high-accuracy control of multipoint pressure distribution at wide range velocities for the variable geometry combustor is shown to be realized.

Key words: variable geometry combustor, supersonic combustion, hardware-in-the-loop, deep reinforcement learning, multipoint pressure distribution control

CLC Number:

V231.2

Wenhui LING, Chunhui MU, Lingcong NIE, Xian DU, Ximing SUN. Improved DDPG-based multipoint pressure distribution control of variable geometry scramjet combustor at wide range velocities[J]. Acta Aeronautica et Astronautica Sinica, 2025, 46(12): 131092.

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算法组成	网络参数	数值
样本池	记忆容量	10 000
回合数	回合数	30
循环次数	循环次数	2 000
最小样本数	样本数	32
执行者（Actor）	输入神经元输出神经元每一层的神经元个数激活函数学习率软更新因子	8 2 8，200， 100， 100， 2 Relu，Relu，Tanh 0.000 1 0.01
评估者（Critic）	输入神经元输出神经元每一层的神经元个数激活函数学习率软更新因子	10 1 10， 200， 100， 100， 1 Relu，Relu，Linear 0.000 2 0.01

扩张比	燃油总当量比	状态	控制周期/ms
1.4	0.7	状态1	26
1.4	1.0	状态2	26
1.6	0.7	状态3	31 31 34
	0.9	状态4
	1.2	状态5
1.8	1	状态6	29
1.8	1.2	状态7	29

Improved DDPG-based multipoint pressure distribution control of variable geometry scramjet combustor at wide range velocities

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