Adaptive Dynamic Surface Control for Formations of Autonomous Surface Vehicles With Uncertain Dynamics

doi:10.1109/TCST.2011.2181513

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Adaptive Dynamic Surface Control for Formations of Autonomous Surface Vehicles With Uncertain Dynamics

Journal Article•DOI•

Adaptive Dynamic Surface Control for Formations of Autonomous Surface Vehicles With Uncertain Dynamics

Zhouhua Peng¹, Dan Wang¹, Zhiyong Chen², Xiaojing Hu, Weiyao Lan³ - Show less +1 more•Institutions (3)

Dalian Maritime University¹, University of Newcastle², Xiamen University³

01 Mar 2013-IEEE Transactions on Control Systems and Technology (IEEE)-Vol. 21, Iss: 2, pp 513-520

TL;DR: A robust adaptive formation controller is developed by employing neural network and dynamic surface control technique and is able to capture the vehicle dynamics without exact information of coriolis and centripetal force, hydrodynamic damping and disturbances from the environment.

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Abstract: 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.

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Journal Article•DOI•

Unmanned surface vehicles: An overview of developments and challenges

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Zhixiang Liu¹, Youmin Zhang¹, Xiang Yu¹, Chi Yuan¹•Institutions (1)

Concordia University¹

01 Jan 2016-Annual Reviews in Control

TL;DR: An overview of both historical and recent USVs development is provided, along with some fundamental definitions, and existing USVs GNC approaches are outlined and classified according to various criteria, such as their applications, methodologies, and challenges.

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709 citations

Journal Article•DOI•

Adaptive Neural Network Control of AUVs With Control Input Nonlinearities Using Reinforcement Learning

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Rongxin Cui¹, Chenguang Yang², Yang Li¹, Sanjay Sharma³•Institutions (3)

Northwestern Polytechnical University¹, Swansea University², University of Plymouth³

10 Jan 2017-IEEE Transactions on Systems, Man, and Cybernetics

TL;DR: The trajectory tracking problem for a fully actuated autonomous underwater vehicle (AUV) that moves in the horizontal plane is investigated and two neural networks, including a critic and an action NN, are integrated into the adaptive control design.

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Abstract: In this paper, we investigate the trajectory tracking problem for a fully actuated autonomous underwater vehicle (AUV) that moves in the horizontal plane. External disturbances, control input nonlinearities and model uncertainties are considered in our control design. Based on the dynamics model derived in the discrete-time domain, two neural networks (NNs), including a critic and an action NN, are integrated into our adaptive control design. The critic NN is introduced to evaluate the long-time performance of the designed control in the current time step, and the action NN is used to compensate for the unknown dynamics. To eliminate the AUV’s control input nonlinearities, a compensation item is also designed in the adaptive control. Rigorous theoretical analysis is performed to prove the stability and performance of the proposed control law. Moreover, the robustness and effectiveness of the proposed control method are tested and validated through extensive numerical simulation results.

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370 citations

Cites methods from "Adaptive Dynamic Surface Control fo..."

...NN adaptive control was presented for multiple unmanned surface vessels in [43], and the unmeasured states were estimated by a local...
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Journal Article•DOI•

Fault tolerant finite-time leader-follower formation control for autonomous surface vessels with LOS range and angle constraints

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Xu Jin¹•Institutions (1)

Georgia Institute of Technology¹

01 Jun 2016-Automatica

TL;DR: It is shown that under the proposed control method, despite the presence of actuator faults and system uncertainties, the formation tracking errors can converge into arbitrarily small neighborhoods around zero in finite time, while the constraint requirements on the LOS range and angle will not be violated.

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344 citations

Cites background or methods from "Adaptive Dynamic Surface Control fo..."

...In this section we present a simulation study based on the model presented in Do and Pan (2006) and Peng et al. (2013), where the vessel dynamics are in the form of (1), with the kinetics Miν̇i + Ci(νi)νi + Di(νi)νi + Fi(νi) = τ Fi , (45) where i = 1, 2 meaning that there are two followers that we…...
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...The assumption of passive-boundedness for the sway velocity is a mild one and has been adopted in the literature on the topic of underactuated ships (Li et al., 2008; Peng et al., 2013)....
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...Take m23,i = 0 by properly choosing the body-frame origin (Peng et al., 2013), the kinetics model can be further represented as...
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...The formulation of the ship kinematics presented in the works such as Do and Pan (2006), Ghommam and Mnif (2009), Peng et al. (2013, 2011) can also be converted into the form of (1)....
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...As the leader moves in the sea and is subject to the hydrodynamic damping force, the surge speed cannot be infinite in practice (Peng et al., 2013)....
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Journal Article•DOI•

Distributed Maneuvering of Autonomous Surface Vehicles Based on Neurodynamic Optimization and Fuzzy Approximation

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Zhouhua Peng¹, Jun Wang², Dan Wang¹•Institutions (2)

Dalian Maritime University¹, City University of Hong Kong²

01 May 2018-IEEE Transactions on Control Systems and Technology

TL;DR: It is proven that distributed maneuvering errors converge to a residual set by virtue of cascade stability analysis, and an optimization-based command governor is employed to generate an optimal guidance signal for vehicle kinetics.

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Abstract: This brief is concerned with the distributed maneuvering of multiple autonomous surface vehicles guided by a virtual leader moving along a parameterized path. In the guidance loop, a distributed guidance law is developed by incorporating a constant bearing strategy into a path-maneuvering design such that a prescribed formation pattern can be reached. To optimize the guidance signal under velocity constraint as well as minimize control torque during transient phase, an optimization-based command governor is employed to generate an optimal guidance signal for vehicle kinetics. The optimization problem is formulated as a bound-constrained quadratic programming problem, which is solved using a recurrent neural network. In the control loop, an estimator is developed where a fuzzy system is used to approximate unknown kinetics based on input and output data. Next, a kinetic control law is constructed based on the optimal command signal and the fuzzy-system-based estimator. By virtue of cascade stability analysis, it is proven that distributed maneuvering errors converge to a residual set. The simulation results illustrate the efficacy of the proposed method.

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284 citations

Cites methods from "Adaptive Dynamic Surface Control fo..."

...Remark 1: Compared with the backstepping and DSC design methods in [1]–[4], [8]–[11], [21], and [31], the advantage of the RNN-based reference governor is twofold....
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Journal Article•DOI•

Output-Feedback Path-Following Control of Autonomous Underwater Vehicles Based on an Extended State Observer and Projection Neural Networks

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Zhouhua Peng¹, Jun Wang²•Institutions (2)

Dalian Maritime University¹, City University of Hong Kong²

01 Apr 2018-IEEE Transactions on Systems, Man, and Cybernetics

TL;DR: Simulation results substantiate the efficacy of the proposed method for output-feedback path-following of under-actuated autonomous underwater vehicles and prove that all error signals in the closed-loop system are uniformly and ultimately bounded.

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Abstract: This paper presents a design method for output-feedback path-following control of under-actuated autonomous underwater vehicles moving in a vertical plane without using surge, heave, and pitch velocities. Specifically, an extended state observer (ESO) is developed to recover the unmeasured velocities as well as to estimate total uncertainty induced by internal model uncertainty and external disturbance. At the kinematic level, a commanded guidance law is developed based on a vertical line-of-sight guidance scheme and the observed velocities. To optimize guidance signals, optimization-based reference governors are formulated as bound-constrained quadratic programming problems for computing optimal reference signals. Two globally convergent recurrent neural networks called projection neural networks are used to solve the optimization problems in real-time. Based on the optimal reference signals and ESO, a kinetic control law with disturbance rejection capability is constructed at the kinetic level. It is proved that all error signals in the closed-loop system are uniformly and ultimately bounded. Simulation results substantiate the efficacy of the proposed method for output-feedback path-following of under-actuated autonomous underwater vehicles.

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281 citations

Cites background or methods from "Adaptive Dynamic Surface Control fo..."

...In addition to handling vehicle uncertainty [3], [5], [6], [12], [18], [22], [36], [37], [43], it is necessary to adhere to strict...
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...If only the output information is available, the methods given in [3], [5], [6], [12], [18], [22], [36], and [37] may not be...
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...A variety of methods are proposed to deal with the uncertainty, ranging from sliding model control [36], neural network control [3], [6], [18], [22], [37]–[39], fuzzy...
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...Motion control scenario for marine vehicles include trajectorytracking [14]–[18], path-following [1], [2], [19]–[21], and formation control [3], [4], [8], [10], [22]–[25]....
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...Remark 4: The proposed design method takes the following advantages over the backstepping and dynamic surface control designs in [1]–[3], [6], [12], [14], [18]–[22], and [37]....
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Kurt Hornik¹•Institutions (1)

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"Adaptive Dynamic Surface Control fo..." refers background in this paper

...Since neural networks (NNs) have an inherent ability of learning nonlinear dynamics [24]–[26], it is attractive to apply them to the control of surface vehicles....
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Journal Article•DOI•

Information flow and cooperative control of vehicle formations

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J.A. Fax¹, Richard M. Murray²•Institutions (2)

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13 Sep 2004-IEEE Transactions on Automatic Control

TL;DR: A Nyquist criterion is proved that uses the eigenvalues of the graph Laplacian matrix to determine the effect of the communication topology on formation stability, and a method for decentralized information exchange between vehicles is proposed.

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Abstract: We consider the problem of cooperation among a collection of vehicles performing a shared task using intervehicle communication to coordinate their actions. Tools from algebraic graph theory prove useful in modeling the communication network and relating its topology to formation stability. We prove a Nyquist criterion that uses the eigenvalues of the graph Laplacian matrix to determine the effect of the communication topology on formation stability. We also propose a method for decentralized information exchange between vehicles. This approach realizes a dynamical system that supplies each vehicle with a common reference to be used for cooperative motion. We prove a separation principle that decomposes formation stability into two components: Stability of this is achieved information flow for the given graph and stability of an individual vehicle for the given controller. The information flow can thus be rendered highly robust to changes in the graph, enabling tight formation control despite limitations in intervehicle communication capability.

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Behavior-based formation control for multirobot teams

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Tucker Balch¹, Ronald C. Arkin²•Institutions (2)

Carnegie Mellon University¹, Georgia Institute of Technology College of Computing²

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TL;DR: New reactive behaviors that implement formations in multirobot teams are presented and evaluated and demonstrate the value of various types of formations in autonomous, human-led and communications-restricted applications, and their appropriateness in different types of task environments.

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Abstract: New reactive behaviors that implement formations in multirobot teams are presented and evaluated. The formation behaviors are integrated with other navigational behaviors to enable a robotic team to reach navigational goals, avoid hazards and simultaneously remain in formation. The behaviors are implemented in simulation, on robots in the laboratory and aboard DARPA's HMMWV-based unmanned ground vehicles. The technique has been integrated with the autonomous robot architecture (AuRA) and the UGV Demo II architecture. The results demonstrate the value of various types of formations in autonomous, human-led and communications-restricted applications, and their appropriateness in different types of task environments.

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Journal Article•DOI•

Dynamic surface control for a class of nonlinear systems

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D. Swaroop¹, J.K. Hedrick, P.P. Yip, J.C. Gerdes•Institutions (1)

Texas A&M University¹

01 Oct 2000-IEEE Transactions on Automatic Control

TL;DR: A method is proposed for designing controllers with arbitrarily small tracking error for uncertain, mismatched nonlinear systems in the strict feedback form and it is shown that these low pass filters allow a design where the model is not differentiated, thus ending the complexity arising due to the "explosion of terms" that has made other methods difficult to implement in practice.

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Abstract: A method is proposed for designing controllers with arbitrarily small tracking error for uncertain, mismatched nonlinear systems in the strict feedback form. This method is another "synthetic input technique," similar to backstepping and multiple surface control methods, but with an important addition, /spl tau/-1 low pass filters are included in the design where /spl tau/ is the relative degree of the output to be controlled. It is shown that these low pass filters allow a design where the model is not differentiated, thus ending the complexity arising due to the "explosion of terms" that has made other methods difficult to implement in practice. The backstepping approach, while suffering from the problem of "explosion of terms" guarantees boundedness of tracking errors globally; however, the proposed approach, while being simpler to implement, can only guarantee boundedness of tracking error semiglobally, when the nonlinearities in the system are non-Lipschitz.

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"Adaptive Dynamic Surface Control fo..." refers methods in this paper

...In this section, we present the leader-follower formation control algorithm based on NN-based DSC technique [27], [29]....
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Journal Article•DOI•

Information flow and cooperative control of vehicle formations

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J. Alexander Fax¹, Richard M. Murray²•Institutions (2)

Northrop Grumman Corporation¹, California Institute of Technology²

01 Jan 2002-IFAC Proceedings Volumes

TL;DR: It is demonstrated how exchange of minimal amounts of information between vehicles can be designed to realize a dynamical system which supplies each vehicle with a shared reference trajectory.

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1,724 citations