Neuroadaptive Distributed Output Feedback Tracking Control for Multiple Marine Surface Vessels With Input and Output Constraints

Xia, Guoqing; Sun, Chuang; Zhao, Bo; Xia, Xiaoming; Sun, Xianxin

doi:10.1109/access.2019.2938067

Cited by 33 publications

(32 citation statements)

References 37 publications

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“…Substituting (27), (28), (29) into (26), the path following error dynamics can be rewritten as: Choose the Lyapunov function candidate as follows:…”

Section: Guidance Systemmentioning

confidence: 99%

“…However, the structure of MLPNN is complicated, so that the design parameters are difficult to choose and the learning speed is slow. In [26], the radial basis function neural network (RBFNN) was applied to estimate the unknown model dynamics of fullactuated vessels for dynamic position. For path following problem of USVs, the RBFNN was used to compensate the model uncertainties and environment disturbances in [27] and [28].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Neural Path Following Control of Underactuated Surface Vessels With Input Saturation

et al. 2020

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In this paper, considering the input saturation, off-diagonal mass matrix, model uncertainties and time-varying environment disturbances, an adaptive neural path following control strategy, which is based on the surge-heading line-of-sight guidance law, is presented for underactuated surface vessels. In view of the practical situation, we consider that the mass and damping matrices are off-diagonal. For the sake of better path following performance, a surge-heading line-of-sight guidance law is established, where the surge-heading line-of-sight guidance law not only generates the desired heading angle, but also designs the desired surge speed for the control system. Then, adaptive neural path following controllers are designed to track the referenced signals, where the input saturation nonlinearity is handled by a hyperbolic tangent function, and the lumped disturbances including external environment disturbances, approximation errors and model uncertainties are approximated by adaptive radial basis function neural network. On the basis of the proposed control scheme, all error signals of the whole system are proven to be uniformly ultimately bounded, so that the target of path following problem is realized. At last, simulation results are applied to indicate that the presented approach is effective. INDEX TERMS Input saturation, neural networks, path following, surge-heading line-of-sight.

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“…Substituting (27), (28), (29) into (26), the path following error dynamics can be rewritten as: Choose the Lyapunov function candidate as follows:…”

Section: Guidance Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Neural Path Following Control of Underactuated Surface Vessels With Input Saturation

et al. 2020

Self Cite

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“…e research of nonlinear control theory has been playing an increasingly important role for MASs [9,25,[30][31][32] and has also become necessary in the design of the consensus control for the multi-UUVs, including the back stepping-based [33], adaptive-based [34,35], slide mode-2 Complexity based [36], and neutral networks-based [37][38][39] consensus control.…”

Section: Introductionmentioning

confidence: 99%

Leader-Following Multiple Unmanned Underwater Vehicles Consensus Control under the Fixed and Switching Topologies with Unmeasurable Disturbances

Yan

Liu³

et al. 2020

Complexity

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We propose a consensus control strategy for multiple unmanned underwater vehicles (multi-UUVs) with unmeasurable disturbances under the fixed and switching topologies. The current methods presented in the literature mainly solve tracking consensus problems with the disturbances under the time-invariant and time-varying topologies, respectively. In the paper, considering the complex nonlinear and couple model of the UUV, the technique of the feedback linearization is employed to transform the nonlinear UUV model into a second-order integral UUV model. For unmeasurable disturbances consisting of unknown model uncertainties and external disturbance for each UUV, we design the distributed extended state observer (DESO) to estimate the disturbances using the UUV position information relative to its neighbours. Moreover, leader-following multi-UUVs consensus control algorithm that enables all following UUVs to track the leader UUV state information based on the estimation state information from the DESO is proposed for two types of topologies, the fixed and switching topologies. Finally, simulation results are shown to demonstrate the effectiveness of the algorithm proposed in the paper.

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“…Unfortunately, no previous research has comprehensively considered the problems in the practical application of the moving mass actuator, including aerodynamic model error, the dynamic effect of movement, stroke limitation, and slow convergence. Such a system can be summarized as a system subject to complex disturbances and actuator constraints, and some advanced control algorithms have been studied in previous research (Akella et al, 2005; Xia et al, 2019; Yu and Xie, 2019). The constrained backstepping technique was applied to derive a robust control law for spacecraft under input magnitude and rate saturations (Zou et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Speed-adaptive dynamic surface attitude control for a satellite with moving masses under input constraints

Liao

2020

Transactions of the Institute of Measurement and Control

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This paper investigates an attitude control technique for a low Earth orbit nanosatellite with moving masses based on the active use of aerodynamic forces. A speed-adaptive dynamic surface control scheme is designed to comprehensively solve the practical problems of aerodynamic model error, the dynamic effect of movement, stroke limitation, and slow convergence. Multiple constraints are imposed on the inputs to reduce the fast-varying dynamic effect of the masses to be negligible. Other slow-varying disturbances are precisely estimated by a nonlinear observer. In particular, to resolve the contradiction between the overshoot and the attitude convergence speed, a novel adaptive law is designed based on the smooth hyperbolic tangent function to adjust the convergence parameter within the given boundary. Moreover, considering the actual physical limitation, hard constraints are imposed on two actuators. Finally, by using the Lyapunov approach, it is proven that, despite uncertain dynamics, unknown disturbances and input constraints, the attitude error can be adjusted to be arbitrarily small by choosing the proper parameters. A semi-physical simulation platform is built to verify the feasibility of the moving mass actuator and the effectiveness and robustness of the proposed control scheme.

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Neuroadaptive Distributed Output Feedback Tracking Control for Multiple Marine Surface Vessels With Input and Output Constraints

Cited by 33 publications

References 37 publications

Adaptive Neural Path Following Control of Underactuated Surface Vessels With Input Saturation

Adaptive Neural Path Following Control of Underactuated Surface Vessels With Input Saturation

Leader-Following Multiple Unmanned Underwater Vehicles Consensus Control under the Fixed and Switching Topologies with Unmeasurable Disturbances

Speed-adaptive dynamic surface attitude control for a satellite with moving masses under input constraints

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