A Novel Cooperative Control System of Multi-Missile Formation Under Uncontrollable Speed

Zhang, Zhenlin; Zhang, Ke; Han, Zhizhong

doi:10.1109/access.2021.3049571

Cited by 8 publications

(5 citation statements)

References 28 publications

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“…The trajectories of the two situations are shown in Figures 5 and 6, and the corresponding analytical results are presented in Figures 7 and 8. It can be observed that the convergent resultant error was maintained in a small interval (within 0.05) in both cases, and the results were of comparable if not better accuracy than the comparison results in [33], which kept the position error within 50 m. In addition, good synchronization of the speed and heading angles among the missiles was achieved, although the neighboring speed information was not provided.…”

Section: Basic Formation Controlmentioning

confidence: 74%

“…First, we incorporate a policy constraint approach to enhance the stability of the algorithm in order to optimize the objective function and find the Nash equilibrium strategy. The proposed algorithm is more flexible for adapting to varying control objectives compared with conventional approaches [4,[31][32][33]. Then, an adaptive topology scheme is designed to address the common node failure problem in formation control, and this method can achieve stable communication connections at a relatively low communication cost.…”

Section: Introductionmentioning

confidence: 99%

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Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy

et al. 2022

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Formation control is one of the most concerning topics within the realm of swarm intelligence. This paper presents a metaheuristic approach that leverages a natural co-evolutionary strategy to solve the formation control problem for a swarm of missiles. The missile swarm is modeled by a second-order system with a heterogeneous reference target, and the exponential of the resultant error is accumulated to be the objective function such that the swarm converges to optimal equilibrium states satisfying specific formation requirements. Focusing on the issue of the local optimum and unstable evolution, we incorporate a novel model-based policy constraint and a population adaptation strategy that significantly alleviates the performance degradation of the existing natural co-evolutionary strategy in terms of slow training and instability of convergence. With application of the Molloy–Reed criterion in the field of network communication, we developed an adaptive topology method that assures connectivity under node failure, and its effectiveness is validated theoretically and experimentally. The experimental results demonstrate that the accuracy of formation flight achieved by this method is competitive with that of conventional control methods and is much more adaptable. More significantly, we show that it is feasible to treat the generic formation control problem as an optimal control problem for finding a Nash equilibrium strategy and solving it through iterative learning.

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Section: Basic Formation Controlmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy

et al. 2022

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“…However, since the information of missile guidance control system is transmitted via wireless channel, there will have some undesired effects during the information transmission, e.g., data dropout (packet drop) and network-induced delay. On the other hand, different than the conventional single missile system, the multi-missile system is a popular issue and it has been widely addressed by researchers in recent years [49]- [51]. In this situation, to achieve more difficult missions, a set of missile systems are controlled to maintain the desired formation during the maneuvering process.…”

Section: Discussionmentioning

confidence: 99%

“…The above LMIs-constrained optimization problem is also called eigenvalue problem (EVP) and can be solved very efficiently by convex optimization algorithm [48]. More specifically, this problem can be solved by decreasing ρ 2 until W 1 > 0 and P 2 > 0 cannot be found in (40) and (49).…”

Section: Proof See Appendix Bmentioning

confidence: 99%

Robust Stochastic Observer-Based Attack-Tolerant Missile Guidance Control Design Under Malicious Actuator and Sensor Attacks

2021

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In this study, the robust H ∞ stochastic observer-based attack-tolerant guidance control strategy is designed for the nonlinear stochastic missile guidance control system under the external disturbance and measurement noise as well as actuator attack signal and sensor attack signal. To simplify the attack signal estimation, a novel nonsingular smoothed dynamic model is introduced to efficiently describe the actuator and sensor attack signals. Consequently, the state/attack signal estimation can be easily achieved by using conventional Luenberger observer. Next, to attenuate the effect of external disturbance, measurement noise and approximation errors of attack signal on the missile guidance control system, the robust H ∞ attack-tolerant guidance control performance is considered and the design condition is derived in terms of nonlinear Hamilton-Jacobi inequality (HJI) constrained problem. Since HJI can not be easily solved analytically or numerically, the Takagi-Sugeno (T-S) fuzzy modelling method is utilized to facilitate the robust H ∞ attack-tolerant guidance control strategy design. Thereafter, the H ∞ observer-based attacktolerant control design problem is transformed into linear matrix inequalities problem (LMIP) which can be solved very efficiently by using the convex optimization techniques. Simulation example, with the comparison between the proposed method and conventional robust missile guidance strategy, is given to illustrate the design procedures and validate the performance of the proposed method.

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“…They introduced a proposed abstraction of an aerial swarm system architecture to help developers to understand the main required modules. Zhang et al [13] investigated a novel cooperative control system based on the sliding mode variable structure control theory for multimissile formation flight. According to numerical simulations, the method proposed in this article could achieve similar relative position errors under the condition of uncontrollable speed.…”

Section: Introductionmentioning

confidence: 99%

A Deep $Q$ -Network-Based Collaborative Control Research for Smart Ammunition Formation

Shen

Zhang

Zhu

et al. 2022

International Journal of Aerospace Engineering

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The smart ammunition formation (SAF) system model usually has the characteristics of complexity, time variation, and nonlinearity. With the consideration of random factors, such as sensor error and environmental disturbance, the system model cannot be modeled accurately. To deal with this problem, this paper investigated an intelligent deep Q -network- (DQN-) based control algorithm for the SAF collaborative control, which deals with the high dynamics and uncertainty in the SAF flight environment. In the environment description of the SAF, we built a dynamic model to represent the system joint states, which referred to the smart ammunition’s velocity, the trajectory inclination angle, the ballistic deflection angle, and the relative position between different formation nodes. Next, we describe the SAF collaborative control process as a Markov decision process (MDP) with the application of the reinforcement learning (RL) technique. Then, the basic framework ε -imitation action-selecting strategy and the algorithm details were developed to address the SAF control problem based on the DQN scheme. Finally, the numerical simulation was carried out to verify the effectiveness and portability of the DQN-based algorithm. The average total reward curve showed a reasonable convergence, and the relative kinematic relationship among the formation nodes met the requirements of the controller design. It illustrated that the DQN-based algorithm obtained a novel performance in the SAF collaborative control.

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A Novel Cooperative Control System of Multi-Missile Formation Under Uncontrollable Speed

Cited by 8 publications

References 28 publications

Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy

Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy

Robust Stochastic Observer-Based Attack-Tolerant Missile Guidance Control Design Under Malicious Actuator and Sensor Attacks

A Deep $Q$ -Network-Based Collaborative Control Research for Smart Ammunition Formation

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A Novel Cooperative Control System of Multi-Missile Formation Under Uncontrollable Speed

Cited by 8 publications

References 28 publications

Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy

Formation Control with Connectivity Assurance for Missile Swarms by a Natural Co-Evolutionary Strategy

Robust Stochastic Observer-Based Attack-Tolerant Missile Guidance Control Design Under Malicious Actuator and Sensor Attacks

A Deep Q -Network-Based Collaborative Control Research for Smart Ammunition Formation

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A Deep $Q$ -Network-Based Collaborative Control Research for Smart Ammunition Formation