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Optimal Incremental-containment Control of Two-order Swarm System Based on Reinforcement Learning
Haipeng Chen,Wenxing Fu,Kang Chen,Junmin Liu,Dengxiu Yu 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.10
In this paper, the optimal incremental-containment control of two-order swarm system based on reinforcement learning (RL) is proposed to avoid the dilemma that the number of agents in a swarm system is immutable, which is essential for a swarm system that cannot meet the containment demands and need more agents to expand the containment range. Notably, the number of agents in a swarm system with a traditional containment controller is immutable, which limits the containment range that the swarm system can achieve. Besides, in traditional optimal control theory, it is obtained by solving the Hamilton-Jacobi-Bellman (HJB) equation, which is difficult to solve due to the unknown nonlinearity. To overcome these problems, several contributions are made in this paper. Firstly, in order to overcome the dilemma that the number of agents in the swarm system is immutable, the incremental-containment control is proposed. Secondly, considering the error and control input as the optimization goal, the optimal cost function is introduced and the optimal incremental-containment control is proposed to reduce resource waste and increase hardware service life. Furthermore, based on the proposed optimal incrementalcontainment control, the controller is designed by a new RL based on the backstepping method. The Lyapunov function is used to prove the stability of controller. The simulation show the efficiency of the proposed controller.
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Xiaofeng Zhang,Kang Chen,Wenxing Fu 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10
In this paper, a fuzzy adaptive control scheme is developed for a class of generic Hypersonic Vehicles (GHVs) subjected to non-affine aerodynamics. With the aid of the nonlinear mapping, the dynamics of the attitude tracking errors are transformed to a stochastic uncertain control system. By utilizing several specific smooth function vectors and estimating the boundaries of the uncertainties, the unknown changing uncertainties can be handled. Based on the mean-value theorem, the difficulties caused by non-affine aerodynamics can be circumvented. Meanwhile, two fuzzy logic systems (FLSs) are introduced for dealing with the aerodynamic nonlinearities. The constraints of the attitude angular tracking errors can be ensured simultaneously. Finally, simulation results demonstrated the effectiveness of the proposed algorithm.
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Three-Dimensional Prescribed-Time Impulsive Pinning Cooperative Guidance
Wenhui Ma,Yangwang Fang,Wenxing Fu,Xiaogeng Liang 한국항공우주학회 2023 International Journal of Aeronautical and Space Sc Vol.24 No.5
This paper studies the problem of multiple interceptors with intermittent communication cooperatively intercepting a stationary target. Given the difficulties in real-time online information transmission, a three-dimensional (3D) two-stage prescribed-time impulsive pinning cooperative guidance law (PTIPCGL) is proposed. It can achieve the simultaneous arrival of multiple interceptors based on the directed internal communication and impulsive pinning external communication. In the first stage, the PTIPCGL incorporates a time scaling function into the second-order impulsive pinning consensus to realize the desired convergence performance. Theoretically, the convergence time can be arbitrarily pre-specified and independent of tuning parameters. In the second stage, the switching occurs at the pre-specified convergence time, and the interceptors switch to pure proportional navigation (PPN) guidance with suitable initial conditions to achieve simultaneous arrival. Finally, numerical simulations demonstrate that the PTIPCGL exhibits satisfactory effectiveness and robustness under intermittent communication.
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