This note is concerned with the problem of stabilizing a class of linear continuous‐time systems with completely unknown system dynamics subject to input energy constraint. To deal with this problem, a model‐based low gain feedback law is designed firstly by establishing a special algebraic Riccati equation. Such a low gain feedback law can semiglobally stabilize the linear systems subject to input energy constraint with the exact system model. In order to relax the assumption that the system model is exactly known, an off‐policy reinforcement learning approach is designed to solve the same problem without requiring the completely knowledge of the system dynamics. Finally, in order to verify the effectiveness of the proposed model‐free approach, simulation result on the spacecraft rendezvous problem is introduced.

中文翻译：

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不受输入能量约束的线性系统无模型稳定的非策略方法及其在航天器交会中的应用

该注释涉及稳定一类线性连续时间系统的问题，该系统具有完全未知的系统动力学，受输入能量约束。为了解决这个问题，首先通过建立一个特殊的代数Riccati方程来设计基于模型的低增益反馈定律。这样的低增益反馈定律可以使用精确的系统模型在全局范围内稳定受到输入能量约束的线性系统。为了放宽系统模型是确切已知的假设，设计了一种脱离策略的强化学习方法来解决相同的问题，而无需完全了解系统动力学。最后，为了验证所提出的无模型方法的有效性，介绍了有关航天器交会问题的仿真结果。