UAV Formation Control Under Communication Constraints Based on Distributed Model Predictive Control

Chen, Qi-jie; Jin, Yuqiang; Wang, Taoyu; Wang, Yao; Yan, Tinglong; Long, Yue

doi:10.1109/access.2022.3225434

Cited by 12 publications

(8 citation statements)

References 25 publications

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“…At the same time, it should be noted that the necessary calculations must be performed in real-time and often under conditions of limited onboard computing resources. Real-time actions and timely decision making are needed, for example, to solve dynamic path planning [29], formation control [30], and pursuit-evasion problems. We note significant research [31] devoted to the collective behavior of robots when interaction is based on the use of a geometric acute angle test (AAT).…”

Section: Related Workmentioning

confidence: 99%

“…The geometric module is aimed at solving optimization problems of trajectory motion control with the given constraints [49] and accurate calculation of flight parameters. The intelligent control module is activated in unstable conditions to select among strategies (30) and (31) in accordance with the current situation. In accordance with the proposed scheme, the pursuer receives the coordinates of the evader and all closest obstacles (other pursuers).…”

Section: Matlab Simulation Schemementioning

confidence: 99%

“…0), 5(20,30), 4 (−20, 20), 4 (−20, −20), 4 (100, 20), 4 (−20, −90), 4 (−5, −100) Yes/Yes No 2 (0, 0), 5 (30, 20), 4 (−30, −50), 4 (−70, 40), 3 (100, −20), 4 (100, −90), 4 (100, 150) Yes/Yes Yes 3 (0, 0), 5 (30, 30), 4 (−30, 30), 4 (−30, −30), 4 (200, −20), 4 (50, −190), 0), 5 (20, 20), 4 (−20, 20), 4 (−20, −20), 4 (100, −20), 4 (100, −90), 4 (−50, −50) Yes/Yes No…”

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Modeling the Solution of the Pursuit–Evasion Problem Based on the Intelligent–Geometric Control Theory

Khachumov,

Khachumov

2023

Mathematics

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An important action-planning problem is considered for participants of the pursuit–evasion game with multiple pursuers and a high-speed evader. The objects of study are mobile robotic systems and specifically small unmanned aerial vehicles (UAVs). The problem is complicated by the presence of significant wind loads that affect the trajectory and motion strategies of the players. It is assumed that UAVs have limited computing resources, which involves the use of computationally fast and real-time heuristic approaches. A novel and rapidly developing intelligent–geometric theory is applied to address the discussed problem. To accurately calculate the points of the participant’s rapprochement, we use a geometric approach based on the construction of circles or spheres of Apollonius. Intelligent control methods are applied to synthesize complex motion strategies of participants. A method for quickly predicting the evader’s trajectory is proposed based on a two-layer neural network containing a new activation function of the “s-parabola” type. We consider a special backpropagation training scheme for the model under study. A simulation scheme has been developed and tested, which includes mathematical models of dynamic objects and wind loads. The conducted simulations on pursuit–evasion games in close to real conditions showed the prospects and expediency of the presented approach.

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Section: Related Workmentioning

confidence: 99%

Section: Matlab Simulation Schemementioning

confidence: 99%

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Modeling the Solution of the Pursuit–Evasion Problem Based on the Intelligent–Geometric Control Theory

Khachumov,

Khachumov

2023

Mathematics

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“…Reference [16] further considered the state information of the neighboring train system in the performance index function of the DMPC algorithm and achieved a better control effect. Although DMPC is not widely used in the field of VCTS control, it has been studied in the field of vehicle formation [17,18] and unmanned aircraft formation [19,20] control.…”

Section: Introductionmentioning

confidence: 99%

Distributed Cooperative Tracking Control Strategy for Virtual Coupling Trains: An Event-Triggered Model Predictive Control Approach

Li,

Zhong,

Yang

et al. 2023

Processes

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Virtual coupling (VC) technology has received much attention because of its significant advantages in enhancing the railway transport capacity; it achieves efficient train coupling operation through advanced communication technology. However, due to the uncertainty of the operating environment, a stable and effective control system is the key enabler for realization. In this paper, an event-triggered distributed model predictive control (ET-DMPC) method is proposed for the cooperative tracking control of virtual coupling trains (VCTS), considering resource limitations and multiple constraints. Firstly, a distributed model predictive control (DMPC) framework is designed. Based on the established VCTS dynamics model of the dual-leader communication topology, a distributed optimization objective function and safety constraints containing state information of the neighboring train system are constructed. Secondly, due to the limitations of communication and computational resources, the event triggering (ET) mechanism is further introduced, and an ET-DMPC method suitable for VCTS is proposed. The trigger condition of each unit train is designed on the premise of guaranteeing system stability, under which the system can guarantee the input-state stability (ISS), and the recursive feasibility of the system is proven via theoretical analysis. Finally, the VCTS composed of four CRH380A unit trains is used as the control object for simulation experiments, and through two sets of experimental simulation analysis, the effectiveness of the proposed method is verified.

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“…20 proposed a position control algorithm based on MPC to improve the position-tracking accuracy of synchronous machines. To achieve optimal control of constrained UAVs, 21 proposed an algorithm based on MPC and uses an ant colony algorithm to accelerate the solution process of MPC. 22 proposed an MPC network control strategy to efficiently handle the negative effect of time delays and attacks in S-C communication channels on multi-motors.…”

Section: Introductionmentioning

confidence: 99%

Resilient dual-mode model predictive control for constrained linear networked control systems with random DoS attacks

Wu,

Qiu,

Lin

et al. 2023

Preprint

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This paper proposes a resilient dual-mode model predictive control (MPC) framework that simultaneously considers system constraints and Denial-of-Service (DoS) attacks for linear time-invariant networked control systems (NCS). The DoS attacks is random and occurs at the both sensor-to-controller ( S - C ) communication channel and controller-to-actuator ( C - A ) communication channel. The MPC can well compensate the effect of the DoS attacks on the constrained system. At the same time, to address the problem of repeated oscillations caused by the inaccurate model near the equilibrium point of the MPC, and to reduce the computational effort, the resilient two-mode MPC is used. To guarantee the stability of NCS, a resilient terminal invariant set based on LMI is designed to ensure that the constrained system remains stable under M consecutive attacks. Finally, numerical simulations are conducted to validate the proposed MPC framework, showing its effectiveness in practical applications.

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UAV Formation Control Under Communication Constraints Based on Distributed Model Predictive Control

Cited by 12 publications

References 25 publications

Modeling the Solution of the Pursuit–Evasion Problem Based on the Intelligent–Geometric Control Theory

Modeling the Solution of the Pursuit–Evasion Problem Based on the Intelligent–Geometric Control Theory

Distributed Cooperative Tracking Control Strategy for Virtual Coupling Trains: An Event-Triggered Model Predictive Control Approach

Resilient dual-mode model predictive control for constrained linear networked control systems with random DoS attacks

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