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This paper investigates the fault tolerance control of hypersonic aircrafts with
Zhaoying Li; Shuai Shi. \({\mathcal{L}_1}\) Adaptive Loss Fault Tolerance Control of Unmanned Hypersonic Aircraft with Elasticity. Aerospace 2021, 8, 176 .
AMA StyleZhaoying Li, Shuai Shi. \({\mathcal{L}_1}\) Adaptive Loss Fault Tolerance Control of Unmanned Hypersonic Aircraft with Elasticity. Aerospace. 2021; 8 (7):176.
Chicago/Turabian StyleZhaoying Li; Shuai Shi. 2021. "\({\mathcal{L}_1}\) Adaptive Loss Fault Tolerance Control of Unmanned Hypersonic Aircraft with Elasticity." Aerospace 8, no. 7: 176.
This article considers the practical fixed-time self-triggered consensus tracking problem of delayed multiagent networks (MANs) subject to external disturbances under undirected topology and directed topology. The fixed-time consensus implies that the consensus is reached in a finite time and the convergence time is independent of initial conditions under the nonlinear consensus protocols. A self-triggered control (STC) strategy is developed based on the event-triggered control (ETC) strategy. For the ETC strategy, the nonlinear controllers and the measurement errors are designed based on the hyperbolic tangent function to avoid a nondifferential problem and Zeno behavior. To avoid continuous monitoring, the STC strategy is presented. Furthermore, the minimal interevent interval is strictly positive, which implies that no Zeno behavior occurs in the STC strategy. Finally, a numerical example is presented to verify the availability of the algorithms.
Jian Liu; Yanling Zhang; Yao Yu; Hao Liu; Changyin Sun. A Zeno-Free Self-Triggered Approach to Practical Fixed-Time Consensus Tracking With Input Delay. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2021, PP, 1 -11.
AMA StyleJian Liu, Yanling Zhang, Yao Yu, Hao Liu, Changyin Sun. A Zeno-Free Self-Triggered Approach to Practical Fixed-Time Consensus Tracking With Input Delay. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2021; PP (99):1-11.
Chicago/Turabian StyleJian Liu; Yanling Zhang; Yao Yu; Hao Liu; Changyin Sun. 2021. "A Zeno-Free Self-Triggered Approach to Practical Fixed-Time Consensus Tracking With Input Delay." IEEE Transactions on Systems, Man, and Cybernetics: Systems PP, no. 99: 1-11.
In this paper, a model‐free optimal synchronization controller is designed to achieve the aggressive attitude synchronization for multiple heterogeneous quadrotor systems with highly nonlinear and coupled dynamics by using a reinforcement learning (RL) approach. A distributed observer is first designed for each following quadrotor to estimate the states of a virtual leader. A performance function is then utilized for each quadrotor to penalize the observed synchronization error and the control effort. An RL approach is finally employed to learn the optimal control law without any knowledge of the dynamic model information of the followers. The control law depends on the quadrotor states and the observer states, and guarantees that the attitude synchronization error converges to zero for all quadrotors, under aggressive maneuvers. Simulation results are provided to verify the effectiveness of the proposed controller.
Wanbing Zhao; Hao Liu; Bohui Wang. Model‐free attitude synchronization for multiple heterogeneous quadrotors via reinforcement learning. International Journal of Intelligent Systems 2021, 36, 2528 -2547.
AMA StyleWanbing Zhao, Hao Liu, Bohui Wang. Model‐free attitude synchronization for multiple heterogeneous quadrotors via reinforcement learning. International Journal of Intelligent Systems. 2021; 36 (6):2528-2547.
Chicago/Turabian StyleWanbing Zhao; Hao Liu; Bohui Wang. 2021. "Model‐free attitude synchronization for multiple heterogeneous quadrotors via reinforcement learning." International Journal of Intelligent Systems 36, no. 6: 2528-2547.
In this article, the data-driven optimal formation control problem is addressed for a heterogeneous quadrotor team with a virtual leader. Each quadrotor is considered as a highly nonlinear system with six degrees of freedom and the accurate dynamic information of the quadrotor is difficult to obtain in practical applications. An optimal cascade formation controller, including a position controller and an attitude controller, is proposed to track a virtual leader and form a predesigned formation. By using the reinforcement learning (RL) approach, the optimal formation controller is learned from the quadrotor system data without any knowledge of dynamic information of the quadrotors. Simulation results of a heterogeneous multiquadrotor system in a formation flight are given to show the effectiveness of the proposed controllers.
Wanbing Zhao; Hao Liu; Frank L. Lewis; Xinlong Wang. Data-Driven Optimal Formation Control for Quadrotor Team With Unknown Dynamics. IEEE Transactions on Cybernetics 2021, PP, 1 -10.
AMA StyleWanbing Zhao, Hao Liu, Frank L. Lewis, Xinlong Wang. Data-Driven Optimal Formation Control for Quadrotor Team With Unknown Dynamics. IEEE Transactions on Cybernetics. 2021; PP (99):1-10.
Chicago/Turabian StyleWanbing Zhao; Hao Liu; Frank L. Lewis; Xinlong Wang. 2021. "Data-Driven Optimal Formation Control for Quadrotor Team With Unknown Dynamics." IEEE Transactions on Cybernetics PP, no. 99: 1-10.
In this paper, a distributed model-free solution based on reinforcement learning is proposed for the leader–follower formation control problem of heterogeneous multi-agent systems. The multi-agent system consists of multiple rotorcrafts involving a virtual leader and multiple followers, where the dynamics of leaders and followers is unknown. The formation control problem is firstly formulated as an optimal output regulation problem. A discounted performance function is then introduced to guarantee that the tracking error asymptotically converges to zero, and an online off-policy reinforcement learning algorithm is proposed to solve the optimal output problem online using the data generated along the trajectories of the agents. A simulation example is provided to validate the effectiveness of the proposed control method.
Hao Liu; Fachun Peng; Hamidreza Modares; Bahare Kiumarsi. Heterogeneous formation control of multiple rotorcrafts with unknown dynamics by reinforcement learning. Information Sciences 2021, 558, 194 -207.
AMA StyleHao Liu, Fachun Peng, Hamidreza Modares, Bahare Kiumarsi. Heterogeneous formation control of multiple rotorcrafts with unknown dynamics by reinforcement learning. Information Sciences. 2021; 558 ():194-207.
Chicago/Turabian StyleHao Liu; Fachun Peng; Hamidreza Modares; Bahare Kiumarsi. 2021. "Heterogeneous formation control of multiple rotorcrafts with unknown dynamics by reinforcement learning." Information Sciences 558, no. : 194-207.
In this note, the data-driven fault-tolerant synchronization control problem is investigated for unknown cooperative quadrotors subject to nonlinearities and multiple actuator faults in the quadrotor dynamics. A distributed observer is provided to estimate the state of the virtual leader. Based on the reinforcement learning theory, the optimal control policy is learned for each quadrotor without any knowledge of the quadrotor dynamic information. Then, the learned control policy is used to construct a data-based fault-tolerant controller to restrain the effects of quadrotor actuator faults. Stability of the constructed controller is proven and the simulation results illustrate the effectiveness of the proposed controller.
Wanbing Zhao; Hao Liu; Frank L. Lewis. Data-Driven Fault-Tolerant Control for Attitude Synchronization of Nonlinear Quadrotors. IEEE Transactions on Automatic Control 2021, PP, 1 -1.
AMA StyleWanbing Zhao, Hao Liu, Frank L. Lewis. Data-Driven Fault-Tolerant Control for Attitude Synchronization of Nonlinear Quadrotors. IEEE Transactions on Automatic Control. 2021; PP (99):1-1.
Chicago/Turabian StyleWanbing Zhao; Hao Liu; Frank L. Lewis. 2021. "Data-Driven Fault-Tolerant Control for Attitude Synchronization of Nonlinear Quadrotors." IEEE Transactions on Automatic Control PP, no. 99: 1-1.
In this paper, a robust visual servoing control approach is proposed to address the landing problem for quadrotors on a moving platform. A vision system is implemented to estimate the position and velocity of the quadrotor. A robust cascade controller is proposed by following backstepping-like fundamentals and robust compensating theory. The effects of time-varying uncertainties, including parameter uncertainties and external disturbances, and time-varying delays resulted from image acquisition, image processing, and sensor measurement delays can be restrained. Experimental results using a quadrotor to land on a ground moving target illustrate the effectiveness of the proposed approach.
Wanbing Zhao; Hao Liu; Xinlong Wang. Robust visual servoing control for quadrotors landing on a moving target. Journal of the Franklin Institute 2021, 358, 2301 -2319.
AMA StyleWanbing Zhao, Hao Liu, Xinlong Wang. Robust visual servoing control for quadrotors landing on a moving target. Journal of the Franklin Institute. 2021; 358 (4):2301-2319.
Chicago/Turabian StyleWanbing Zhao; Hao Liu; Xinlong Wang. 2021. "Robust visual servoing control for quadrotors landing on a moving target." Journal of the Franklin Institute 358, no. 4: 2301-2319.
The paper addresses the fully distributed timevarying formation control problem for multiple missiles involving uncertainties. An adaptive control protocol is developed for the missiles, which includes uncertainties in the flight dynamics, while the adaptive control protocol does not require global information of the network missile system. Global formation flight stability is proven via the Lyapunov theory. Simulation tests are performed to validate the effectiveness of the developed protocol as applied to the network system
Deyuan Liu; Hao Liu; Kimon P. Valavanis. Fully Distributed Time-Varying Formation Control for Multiple Uncertain Missiles. IEEE Transactions on Aerospace and Electronic Systems 2020, 57, 1646 -1656.
AMA StyleDeyuan Liu, Hao Liu, Kimon P. Valavanis. Fully Distributed Time-Varying Formation Control for Multiple Uncertain Missiles. IEEE Transactions on Aerospace and Electronic Systems. 2020; 57 (3):1646-1656.
Chicago/Turabian StyleDeyuan Liu; Hao Liu; Kimon P. Valavanis. 2020. "Fully Distributed Time-Varying Formation Control for Multiple Uncertain Missiles." IEEE Transactions on Aerospace and Electronic Systems 57, no. 3: 1646-1656.
This paper investigates a completely distributed adaptive formation control protocol for networked quadrotors under switching communication topologies, where the dynamics of each quadrotor involves seriously nonlinearity and uncertainty simultaneously. For the switching communication topologies case, the adaptive formation control protocol is proposed to guarantee that the translational and rotational tracking errors of the global closed-loop system can converge into a priori set neighborhood of the origin ultimately. Furthermore, the proposed formation control protocol is completely distributed, which means that the controller of each quadrotor only needs the information from itself and its neighbors. Numerical simulation results on the quadrotor team are provided to confirm the effectiveness and advantages of the proposed adaptive formation control protocol.
Hao Liu; Yanhu Wang; Jianxiang Xi. Completely distributed formation control for networked quadrotors under switching communication topologies. Systems & Control Letters 2020, 147, 104841 .
AMA StyleHao Liu, Yanhu Wang, Jianxiang Xi. Completely distributed formation control for networked quadrotors under switching communication topologies. Systems & Control Letters. 2020; 147 ():104841.
Chicago/Turabian StyleHao Liu; Yanhu Wang; Jianxiang Xi. 2020. "Completely distributed formation control for networked quadrotors under switching communication topologies." Systems & Control Letters 147, no. : 104841.
In this paper, a distributed robust optimal formation control problem is studied based on reinforcement learning for the heterogeneous multi-agent system with partial unknown system parameters. The formation system is subjected to equivalent disturbances containing parameter uncertainties and external disturbances. The proposed robust optimal controller consists of a nominal controller and a robust compensator. For the nominal controller, the reinforcement learning algorithm is proposed to obtain the optimal control input. For the robust compensator, the reinforcement learning algorithm is firstly used to identify the unknown dynamic parameters and then the robust compensator is designed to restrain the equivalent disturbances in the formation system. The robustness properties of the global multi-agent system are proven. A simulation of heterogeneous rotorcrafts is provided to verify the effectiveness of the proposed method.
Wei Lin; Wanbing Zhao; Hao Liu. Robust Optimal Formation Control of Heterogeneous Multi-Agent System via Reinforcement Learning. IEEE Access 2020, 8, 218424 -218432.
AMA StyleWei Lin, Wanbing Zhao, Hao Liu. Robust Optimal Formation Control of Heterogeneous Multi-Agent System via Reinforcement Learning. IEEE Access. 2020; 8 (99):218424-218432.
Chicago/Turabian StyleWei Lin; Wanbing Zhao; Hao Liu. 2020. "Robust Optimal Formation Control of Heterogeneous Multi-Agent System via Reinforcement Learning." IEEE Access 8, no. 99: 218424-218432.
In this paper, the fault-tolerant formation control for multiple octorotor unmanned aerial vehicles is investigated. A fully distributed adaptive fault-tolerant formation control scheme is presented to achieve a desired formation flight under multiple uncertainties and actuator faults. The developed controller does not require the global information of the constructed communication network and the knowledge of faults. The robust formation system stability under multiple uncertainties and actuator faults is proven by Lyapunov analysis. Simulation results for octorotor formation flying are provided to demonstrate the effectiveness.
Deyuan Liu; Hao Liu; Jianxiang Xi. Fully distributed adaptive fault-tolerant formation control for octorotors subject to multiple actuator faults. Aerospace Science and Technology 2020, 108, 106366 .
AMA StyleDeyuan Liu, Hao Liu, Jianxiang Xi. Fully distributed adaptive fault-tolerant formation control for octorotors subject to multiple actuator faults. Aerospace Science and Technology. 2020; 108 ():106366.
Chicago/Turabian StyleDeyuan Liu; Hao Liu; Jianxiang Xi. 2020. "Fully distributed adaptive fault-tolerant formation control for octorotors subject to multiple actuator faults." Aerospace Science and Technology 108, no. : 106366.
With the wide application of lithium‐ion battery in various fields, the security and reliability of lithium‐ion battery have attracted great attention. Under the mode of continuous development of Internet of vehicles technology, vehicles will be connected with each other in the future, and the hackers will attack the energy system of the vehicle. However, health assessment of lithium‐ion battery can timely grasp the running state and health of the power battery system, so as to realize active defense against hacker security attacks. This paper proposes a health assessment method for lithium‐ion batteries using incremental capacity analysis and weighted Kalman filter algorithm. In view of the problem that ordinary Kalman filtering algorithm produces poor filtering results when the actual measurement noise error is large, this paper proposes a weighted Kalman filtering algorithm based on ordinary Kalman filtering. Incremental capacity analysis was performed on the charge and discharge data of lithium‐ion batteries, and health characteristics were extracted to construct a Gaussian nonlinear feature association mapping model for the health characteristics of lithium‐ion batteries. Combined with the battery SOH double‐exponential decay model, the weighted Kalman filter algorithm was used to evaluate the health of lithium‐ion batteries. Four lithium‐ion battery data sets provided by NASA were used to simulate and verify the health assessment method proposed in this paper. The verification results show that the health assessment method based on weighted Kalman filter proposed in this paper has better assessment accuracy than the common Kalman filter method with an average percentage error of 0.61%. The average percentage error of the assessment results for different types of batteries was less than 0.9%. The health assessment method has high accuracy and is suitable for different types of batteries.
Sheng Hong; Tianyu Yue; Hao Liu. Vehicle energy system active defense: A health assessment of lithium‐ion batteries. International Journal of Intelligent Systems 2020, 1 .
AMA StyleSheng Hong, Tianyu Yue, Hao Liu. Vehicle energy system active defense: A health assessment of lithium‐ion batteries. International Journal of Intelligent Systems. 2020; ():1.
Chicago/Turabian StyleSheng Hong; Tianyu Yue; Hao Liu. 2020. "Vehicle energy system active defense: A health assessment of lithium‐ion batteries." International Journal of Intelligent Systems , no. : 1.
In this article, the model-free robust formation control problem is addressed for cooperative underactuated quadrotors involving unknown nonlinear dynamics and disturbances. Based on the hierarchical control scheme and the reinforcement learning theory, a robust controller is proposed without knowledge of each quadrotor dynamics, consisting of a distributed observer to estimate the position state of the leader, a position controller to achieve the desired formation, and an attitude controller to control the rotational motion. Simulation results on the multiquadrotor system confirm the effectiveness of the proposed model-free robust formation control method.
Wanbing Zhao; Hao Liu; Frank L. Lewis. Robust Formation Control for Cooperative Underactuated Quadrotors via Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems 2020, PP, 1 -11.
AMA StyleWanbing Zhao, Hao Liu, Frank L. Lewis. Robust Formation Control for Cooperative Underactuated Quadrotors via Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems. 2020; PP (99):1-11.
Chicago/Turabian StyleWanbing Zhao; Hao Liu; Frank L. Lewis. 2020. "Robust Formation Control for Cooperative Underactuated Quadrotors via Reinforcement Learning." IEEE Transactions on Neural Networks and Learning Systems PP, no. 99: 1-11.
A robust control method is proposed to address the satellite formation flying problem subject to communication delays. Each satellite dynamics involves nonlinear dynamics, parametric uncertainties, and external disturbances. Communications between neighboring satellites are affected by time delays. For each satellite, the resulted controller includes a translational controller to maintain the desired formation pattern, and a rotational controller to align the attitude. Theoretical analysis and simulation results are provided to verify the advantages of the proposed formation flying controller.
Yue Gao; Hao Liu; Yu Tian. Robust Satellite Formation Flying Controller Design Subject to Communication Delays. IEEE Access 2020, 8, 170830 -170842.
AMA StyleYue Gao, Hao Liu, Yu Tian. Robust Satellite Formation Flying Controller Design Subject to Communication Delays. IEEE Access. 2020; 8 (99):170830-170842.
Chicago/Turabian StyleYue Gao; Hao Liu; Yu Tian. 2020. "Robust Satellite Formation Flying Controller Design Subject to Communication Delays." IEEE Access 8, no. 99: 170830-170842.
This paper is concerned with the robust visual servoing formation tracking problem for a team of quadrotor unmanned aerial vehicles (UAVs). The quadrotor UAV firstly capturing the target in its camera scope is considered as the current leader to perform the target tracking task and the other quadrotor UAVs follow the current leader with a prescribed formation pattern. When the leader changes, which means the current leader loses the target and the target is captured by another quadrotor UAV, a switching-topology strategy is used to change the leader and guarantee the cooperative work of the quadrotor team. A robust visual servoing switching-topology formation control approach is developed for the quadrotor team, whose model possesses six degrees of freedom subject to the underactuation feature, nonlinear dynamics, parameter uncertainties, and external disturbance. The effectiveness of the theoretical result is validated by theoretical analysis and numerical simulation studies.
Hao Liu; Yafei Lyu; Wanbing Zhao. Robust visual servoing formation tracking control for quadrotor UAV team. Aerospace Science and Technology 2020, 106, 106061 .
AMA StyleHao Liu, Yafei Lyu, Wanbing Zhao. Robust visual servoing formation tracking control for quadrotor UAV team. Aerospace Science and Technology. 2020; 106 ():106061.
Chicago/Turabian StyleHao Liu; Yafei Lyu; Wanbing Zhao. 2020. "Robust visual servoing formation tracking control for quadrotor UAV team." Aerospace Science and Technology 106, no. : 106061.
In this brief, a distributed optimal control method via reinforcement learning is proposed to address the heterogeneous unmanned aerial vehicle (UAV) formation trajectory tracking problem. The UAV formation is composed of a virtual leader with limited nonzero input and several follower vehicles with different unknown dynamics. The proposed control law contains a distributed observer and a model-free off-policy reinforcement learning (RL) protocol. The distributed optimal trajectory tracking problem is formulated for the heterogeneous formation system. A RL algorithm is designed to obtain the optimal control input online without any knowledge of the followers’ dynamics. Simulation example illustrates the effectiveness of the proposed method.
Hao Liu; Qingyao Meng; Fachun Peng; Frank L. Lewis. Heterogeneous formation control of multiple UAVs with limited-input leader via reinforcement learning. Neurocomputing 2020, 412, 63 -71.
AMA StyleHao Liu, Qingyao Meng, Fachun Peng, Frank L. Lewis. Heterogeneous formation control of multiple UAVs with limited-input leader via reinforcement learning. Neurocomputing. 2020; 412 ():63-71.
Chicago/Turabian StyleHao Liu; Qingyao Meng; Fachun Peng; Frank L. Lewis. 2020. "Heterogeneous formation control of multiple UAVs with limited-input leader via reinforcement learning." Neurocomputing 412, no. : 63-71.
This paper focuses on designing a robust time-varying formation controller for a set of micro quad-copters with switching interaction communication topology. Each micro quad-copter within the formation is represented by an under-actuated nonlinear model with the dynamics of each quad-copter being subjected to parameter perturbations and external disturbances. A robust formation control protocol is proposed that consists of a position controller and an attitude controller. The theoretical analysis is detailed to prove robust stability and tracking performance of the multi-vehicle control system, subject to uncertainties and switching interaction communication topology. Experimental and simulation results for a set of micro quad-copters validate the advantages of the proposed control protocol in time-varying formation flights.
Hao Liu; Teng Ma; Frank L. Lewis; Kimon P. Valavanis. Robust Time-Varying Formation Control for a Set of Quad-Copters With Switching Interaction Communication Topology. IEEE Transactions on Vehicular Technology 2020, 69, 6880 -6890.
AMA StyleHao Liu, Teng Ma, Frank L. Lewis, Kimon P. Valavanis. Robust Time-Varying Formation Control for a Set of Quad-Copters With Switching Interaction Communication Topology. IEEE Transactions on Vehicular Technology. 2020; 69 (7):6880-6890.
Chicago/Turabian StyleHao Liu; Teng Ma; Frank L. Lewis; Kimon P. Valavanis. 2020. "Robust Time-Varying Formation Control for a Set of Quad-Copters With Switching Interaction Communication Topology." IEEE Transactions on Vehicular Technology 69, no. 7: 6880-6890.
Tail-sitter unmanned aerial vehicles have two flight modes: they can fly long distances at high cruising speeds as fixed-wing aircrafts; or hover, take off, and land vertically as rotary-wing aircrafts. The tail-sitter dynamics involves serious nonlinearities and high uncertainties, especially in the two flight mode transitions. In this article, an adaptive control approach is proposed for a class of tail-sitter unmanned aerial vehicles to achieve the robustness properties. The control torque allocation problem is addressed based on the dynamic pressure in the transition flight. The proposed control method does not need to switch the coordinate system, the controller structure, or the controller parameters in different flight modes. It is proven that the attitude tracking errors can converge into a given neighborhood of the origin in finite time. Simulation results are presented to show the advantages of the proposed adaptive control method.
Deyuan Liu; Hao Liu; Jiansong Zhang; Frank L Lewis. Adaptive attitude controller design for tail-sitter unmanned aerial vehicles. Journal of Vibration and Control 2020, 27, 185 -196.
AMA StyleDeyuan Liu, Hao Liu, Jiansong Zhang, Frank L Lewis. Adaptive attitude controller design for tail-sitter unmanned aerial vehicles. Journal of Vibration and Control. 2020; 27 (1-2):185-196.
Chicago/Turabian StyleDeyuan Liu; Hao Liu; Jiansong Zhang; Frank L Lewis. 2020. "Adaptive attitude controller design for tail-sitter unmanned aerial vehicles." Journal of Vibration and Control 27, no. 1-2: 185-196.
This paper focuses on formation control of multi-agent systems composed of a team of quadrotors subject to switching topologies. The quadrotor model is underactuated and includes nonlinear dynamics, parameter uncertainties and external disturbance. A robust control approach is proposed that consists of a position and an attitude controller, both consisting of two sub-systems: the nominal controller that is designed to achieve desired tracking for the nominal system, and the disturbance estimating controller that restrains the influence of uncertainties on the real system. Theoretical foundations, detailed simulation studies, and experimental results validate the effectiveness of the proposed methodology.
Hao Liu; Yanhu Wang; Frank L. Lewis; Kimon P. Valavanis. Robust Formation Tracking Control for Multiple Quadrotors Subject to Switching Topologies. IEEE Transactions on Control of Network Systems 2020, 7, 1319 -1329.
AMA StyleHao Liu, Yanhu Wang, Frank L. Lewis, Kimon P. Valavanis. Robust Formation Tracking Control for Multiple Quadrotors Subject to Switching Topologies. IEEE Transactions on Control of Network Systems. 2020; 7 (3):1319-1329.
Chicago/Turabian StyleHao Liu; Yanhu Wang; Frank L. Lewis; Kimon P. Valavanis. 2020. "Robust Formation Tracking Control for Multiple Quadrotors Subject to Switching Topologies." IEEE Transactions on Control of Network Systems 7, no. 3: 1319-1329.
The robust time-varying formation control problem for a group of satellites is addressed. By the static state feedback control strategy and the disturbance estimation theory, a formation flying controller is proposed for the satellite group to form desired time-varying formation patterns and trajectories, and achieve the satellite attitude consensus. The dynamics of each satellite is subject to nonlinearities, parametric perturbations, and external disturbances. Robustness analysis shows that the trajectory and attitude tracking errors of the global closed-loop control system can converge into a given neighborhood of the origin in a finite time. The numerical simulation results validate the effectiveness and advantages of the proposed formation flying controller.
Hao Liu; Yu Tian; Frank L. Lewis. Robust Trajectory Tracking in Satellite Time-Varying Formation Flying. IEEE Transactions on Cybernetics 2020, 1 -9.
AMA StyleHao Liu, Yu Tian, Frank L. Lewis. Robust Trajectory Tracking in Satellite Time-Varying Formation Flying. IEEE Transactions on Cybernetics. 2020; (99):1-9.
Chicago/Turabian StyleHao Liu; Yu Tian; Frank L. Lewis. 2020. "Robust Trajectory Tracking in Satellite Time-Varying Formation Flying." IEEE Transactions on Cybernetics , no. 99: 1-9.