The Distributed Adaptive Finite-Time Chattering Reduction Containment Control for Multiple Ocean Bottom Flying Nodes

Qin, Hongde; Chen, Hui; Sun, Yanchao; Wu, Zheyuan

doi:10.1007/s40815-018-0592-2

Cited by 50 publications

(7 citation statements)

References 38 publications

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“…In [19,20], fuzzy logic systems were employed to estimate the lumped unknown functions. In [21][22][23][24], adaptive techniques were used to reject the model uncertainties and compensate the effects of external disturbances. Nevertheless, the above systems work with periodic sampling and controlling in these studies , known as periodic-triggered control systems.…”

Section: Introductionmentioning

confidence: 99%

Event-triggered neural network control of autonomous surface vehicles over wireless network

Wang

Peng

et al. 2020

Sci. China Inf. Sci.

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In this paper, an event-triggered neural network control method is proposed for autonomous surface vehicles subject to uncertainties and input constraints over wireless network. An event-triggered mechanism with three logic rules is employed to determine the wireless data transmission of states and control inputs. An event-driven neural network is applied to approximate the uncertainties using aperiodic sampled states. In addition, a predictor is employed to update the weights of neural network. An event-based bounded kinetic control law is applied to address the actuator constraints. The advantage of the proposed event-triggered neural network control approach is that the network traffic can be reduced while guaranteeing system stability and speed following performance. The closed-loop control system is proved to be input-tostate stable via cascade theory. The Zeno behavior can be avoided via the proposed event-triggered neural network control approach. A simulation example is provided to demonstrate the effectiveness of the proposed event-triggered neural network control approach for autonomous surface vehicles.

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Section: Introductionmentioning

confidence: 99%

Event-triggered neural network control of autonomous surface vehicles over wireless network

Wang

Peng

et al. 2020

Sci. China Inf. Sci.

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“…Nonlinear dynamical systems suffer from the performance degradation caused by uncertainties and external disturbances. 1 Various nonlinear control methods, such as adaptive method, 2 fuzzy control method, 3 –7 and sliding-mode control (SMC) method, 8,9 have been successively applied to guarantee the nonlinear system stability. Among all of these methods, SMC has wide acceptance in practical implementations and achieves many research results because of its relatively simple design, rapid response, and robustness to unknown interference and model uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Adaptive chattering-free terminal sliding-mode control for full-order nonlinear system with unknown disturbances and model uncertainties

Wan

Chen

Sheng

et al. 2020

International Journal of Advanced Robotic Systems

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This study investigates an adaptive chattering-free sliding-mode control method for n-order nonlinear systems with unknown external disturbances and uncertain models. The proposed method takes the advantage of finite-time fast convergence to avoid singularity problem and ensure its robustness against system uncertainty and unknown disturbance. To achieve fast convergence from any initial condition to system origin, a full-order terminal sliding-mode controller containing differential terms is proposed based on the property of n-order nonlinear systems. Then the continuous and smooth actual control law is obtained by integrating the differential control law containing the discontinuous sign function to realize chattering free. Meanwhile, instead of evaluating the fixed upper bound of system uncertainty and interference in practical implementations, an adaptive method is utilized for its unknown upper bound estimation. The convergence of the adaptive terminal sliding-mode controller in finite time is verified based on Lyapunov stability theory. Finally, two simulation results demonstrate the effectiveness of the proposed control method.

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“…The objective of containment control is to guarantee that all the followers will asymptotically converge into the convex hull formed by the leaders through information interaction and coordinated control. The containment control problem received significant research interest due to its various applications, such as mobile robots [ 13 ] , unmanned aerial vehicles(UAVs) [ 14 ] , underwater vehicles [ 15 ] and satellite formation systems [16,17] , etc.…”

Section: Introductionmentioning

confidence: 99%

“…In view of information topology, fixed network topology [16,20,23,24] and switching network topology [19] , undirected graph [21] and directed graph [18,24] are considered. In many researches, containment control is combined with other novel control algorithms, such as finite-time control [15,16,23] , adaptive control [15,17] , neural network [17] , event-triggered control [ 27 ] , etc. In addition, other problems such as time delay [12,22] , model uncertainties [16,17,24] , external disturbances [16,17] are also discussed.…”

Section: Introductionmentioning

confidence: 99%

Orbital Containment Control Algorithm and Complex Information Topology Design for Large-Scale Cluster of Spacecraft

et al. 2020

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In order to investigate coordinated orbit control problem for large-scale cluster flight spacecraft, a distributed orbital containment control algorithm is proposed for spacecraft cluster flight system with multiple leaders. At first, a general distributed orbital containment control strategy for largescale cluster spacecraft system is given, so that all followers are driven to the convex hull formed by leaders. Then the constraints of convergence and convergence rate of cluster spacecraft system on control gains and information topology are investigated. Specifically, the control gains which achieve maximal convergence rate are analyzed. Furthermore, two kinds of cell partitions from graph theory are employed to investigate the influence of information topology on steady states of followers, which provides theoretical basis for collision avoidance design. Finally, simulation results show that the designed information topology could meet the requirements of large-scale cluster system, and followers belonging to the same cell have the same steady states. INDEX TERMS Large-scale cluster, orbital control, multiple leaders, containment control, graph theory, topology design.

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The Distributed Adaptive Finite-Time Chattering Reduction Containment Control for Multiple Ocean Bottom Flying Nodes

Cited by 50 publications

References 38 publications

Event-triggered neural network control of autonomous surface vehicles over wireless network

Event-triggered neural network control of autonomous surface vehicles over wireless network

Adaptive chattering-free terminal sliding-mode control for full-order nonlinear system with unknown disturbances and model uncertainties

Orbital Containment Control Algorithm and Complex Information Topology Design for Large-Scale Cluster of Spacecraft

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