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Distributed Fuzzy Adaptive Backstepping Optimal Control for Nonlinear Multimissile Guidance Systems With Input Saturation

机译:输入饱和的非线性多导弹制导系统的分布式模糊自适应反演最优控制

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This paper investigates the distributed optimal tracking control problem for nonlinear multiagent systems with a fixed directed graph. The dynamics of followers are in strict-feedback form with unknown nonlinearities and input saturation. Fuzzy logic systems and auxiliary system are introduced to identify the unknown nonlinearities and compensate the effect of input saturation, respectively. Then, by using the command-filtered backstepping technique, the distributed optimal tracking control problem is transformed into a distributed optimal regulation problem of tracking error dynamics in affine form. Subsequently, the distributed optimal feedback controller is derived via adaptive dynamic programming technique, in which a critic network is constructed to approximate the associated cost function online with a designed weight update law. Therefore, the whole controller, consisting of distributed adaptive feedforward tracking controller and distributed optimal feedback controller, not only guarantees that all signals in the closed-loop system are uniformly ultimately hounded, but also guarantees that the cooperative cost function is minimized. The effectiveness of the proposed method is demonstrated by simulation on the cooperative guidance problem of multimissile systems.
机译:本文研究了带有固定有向图的非线性多主体系统的分布式最优跟踪控制问题。跟随器的动态为严格反馈形式,具有未知的非线性和输入饱和度。引入模糊逻辑系统和辅助系统分别识别未知的非线性并补偿输入饱和的影响。然后,通过使用命令过滤的反推技术,将分布式最优跟踪控制问题转化为仿射形式的跟踪误差动态的分布式最优调节问题。随后,通过自适应动态规划技术导出分布式最优反馈控制器,在该控制器中,构造了评论器网络以使用设计的权重更新定律在线近似关联的成本函数。因此,由分布式自适应前馈跟踪控制器和分布式最优反馈控制器组成的整个控制器,不仅保证了闭环系统中的所有信号最终都受到一致约束,而且还保证了协作成本函数最小化。通过仿真验证多导弹系统协同制导问题的有效性。

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