Zhouhua Peng

Dr. Zhouhua Peng

School of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 June 2020 in IEEE Transactions on Industrial Informatics
Verified
Journal Article
Closed access
Zhouhua PengZhouhua Peng
Zhouhua Peng
JWJun Wang
Jun Wang
DWDan Wang
Dan Wang
QHQing-Long Han
Qing-Long Han
Autonomous surface vehicles (ASVs) are marine vessels capable of performing various marine operations without a crew in a variety of cluttered and hostile water/ocean environments. Coordinated control of multiple ASVs has received considerable attention in the last decade. This paper provides an overview of recent advances in coordinated control of multiple ASVs. This paper provides an overview of recent advances in coordinated control of multiple ASVs. First, some challenging issues and scenarios in motion control of ASVs are presented. Next, coordinated control architecture and methods of multiple ASVs are briefly discussed. Then, recent results on trajectory-guided, path-guided, and target-guided coordinated control of multiple ASVs are reviewed in detail. {\color{blue}Finally, several theoretical and technical issues are suggested to direct future investigations including network-based coordination, event-triggered coordination, collision-free coordination, optimization-based coordination, data-driven coordination of ASVs, and task-region-oriented coordination of multiple ASVs and autonomous underwater vehicles.}

31 January 2012 in IEEE Transactions on Control Systems Technology
Verified
Journal Article
Closed access
Zhouhua PengZhouhua Peng
Zhouhua Peng
DWDan Wang
Dan Wang
ZCZhiyong Chen
Zhiyong Chen
XHXiaojing Hu
Xiaojing Hu
WLWeiyao Lan
Weiyao Lan
In this brief, we consider the formation control problem of underactuated autonomous surface vehicles (ASVs) moving in a leader-follower formation, in the presence of uncertainties and ocean disturbances. A robust adaptive formation controller is developed by employing neural network and dynamic surface control technique. The stability of the design is proven via Lyapunov analysis where semiglobal uniform ultimate boundedness of the closed-loop signals is guaranteed. The advantages of the proposed formation controller are that: first, the proposed method only uses the measurements of line-of-sight range and angle by local sensors, no other information about the leader is required for control implementation; second, the developed neural formation controller is able to capture the vehicle dynamics without exact information of coriolis and centripetal force, hydrodynamic damping and disturbances from the environment. Comparative analysis with a model-based approach is given to demonstrate the effectiveness of the proposed method.

5 June 2019 in IEEE Transactions on Cybernetics
Verified
Journal Article
Closed access
Zhouhua PengZhouhua Peng
Zhouhua Peng
DWDan Wang
Dan Wang
Tieshan LiTieshan Li
Tieshan Li
MHMin Han
Min Han
In this paper, a cooperative time-varying formation maneuvering problem with connectivity preservation and collision avoidance is investigated for a fleet of autonomous surface vehicles (ASVs) with position-heading measurements. Each vehicle is subject to unknown kinetics induced by internal model uncertainty and external disturbances. At first, a nonlinear state observer is used to recover the unmeasured linear velocity and yaw rate as well as unknown uncertainty and disturbances. Then, observer-based cooperative time-varying formation maneuvering control laws are designed based on artificial potential functions, nonlinear tracking differentiators, and a backstepping technique. The stability of closed-loop distributed formation control system is analyzed based on input-to-state stability and cascade stability. The salient features of the proposed method are as follows. First, cooperative time-varying formation maneuvering with the capability of connectivity preservation and collision avoidance can be achieved in the absence of velocity measurements. Second, the complexity of the cooperative time-varying formation maneuvering control laws is reduced without resorting to dynamic surface control. Third, the uncertainty and disturbance are actively rejected in the presence of position-heading measurements. Simulation results are given to substantiate the proposed output feedback control method for cooperative time-varying formation maneuvering of ASVs with connectivity preservation and collision avoidance.

6 April 2022 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
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Journal Article
Closed access
NGNan Gu
Nan Gu
DWDan Wang
Dan Wang
Zhouhua PengZhouhua Peng
Zhouhua Peng
JWJun Wang
Jun Wang
QHQing-Long Han
Qing-Long Han
Autonomous marine vehicles (AMVs), including autonomous surface and underwater vehicles, are versatile means to explore, exploit, monitor, and protect marine resources and environments. Motion control is a fundamental enabling technique for state-of-the-art AMV development. Especially, guidance is a critical component in AMV motion control. In recent years, line-of-sight (LOS) guidance, as an efficient guidance method, has attracted tremendous interest from both theoretical and practical perspectives. In this paper, an overview of recent advances in LOS guidance for AMV path following is provided. First, a control objective for the path following of an AMV with a kinematic model is specified. Next, major LOS guidance laws for path following are reviewed in detail. Then, LOS guidance laws applicable to coordinated path following of multiple AMVs are elaborated. Finally, six challenging issues for future research are addressed.

20 December 2013 in IEEE Transactions on Neural Networks and Learning Systems
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Journal Article
Closed access
Zhouhua PengZhouhua Peng
Zhouhua Peng
DWDan Wang
Dan Wang
HZHongwei Zhang
Hongwei Zhang
GSGang Sun
Gang Sun
This paper addresses the leader–follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.

11 March 2020 in IEEE Transactions on Industrial Electronics
Verified
Journal Article
Closed access
Zhouhua PengZhouhua Peng
Zhouhua Peng
YJYue Jiang
Yue Jiang
JWJun Wang
Jun Wang
This paper addresses the event-triggered dynamic surface control of an under-actuated autonomous surface vehicle with unknown kinetics for circumnavigating a dynamic target with unknown velocity. A modular design approach to the event-triggered dynamic surface control is proposed. In the estimator module, an extended state observer is employed for estimating the relative dynamics between the target and the autonomous surface vehicle. A fuzzy system is used for on-line modeling of the unknown vehicle kinetics. In the controller module, an event-triggered dynamic surface control law is developed by using the estimates of relative dynamics and vehicle kinetics. In the control law, a triggered mechanism is introduced to reduce the transmission load and the execution rate of actuators. Besides, the control inputs are bounded by using a projection operator and a saturated function. The input-to-state stability of the closed-loop target enclosing system is proven via cascade analysis. Simulation results substantiate the effectiveness of the event-triggered dynamic surface control of the autonomous surface vehicle for circumnavigating a dynamic target.