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Design and Validation of a Wave-Inversion-Compensated Path-Following Controller for Unmanned Surface Vehicle: Simulation and Experiment
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DOI：10.1109/joe.2026.3697327.png)
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Abstract
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To compensate for wave disturbances encountered by an uncrewed surface vehicle (USV) during navigation, the application of feedforward compensation using the wave information estimated from waves is a good strategy. However, the computational complexity of wave estimation does not meet the real-time requirements of the control system. To reduce the complexity of ship motion response-based wave estimation, and effectively integrate wave estimation into the USV control system while balancing real-time performance and estimation accuracy, a wave inversion strategy based on USV motion time-series data is proposed in this article. The strategy combines the particle swarm optimization (PSO) algorithm with the sequential quadratic programming (SQP) method to achieve a favorable tradeoff between the real-time performance and accuracy of wave estimation, and is further embedded into the design of the USV path-following controller. The method compensates for most of the wave disturbance at the physical level and improves the control effect of the USV. First, using the time-history data of the pitch under low-sea conditions, a hybrid PSO-SQP algorithm is constructed to estimate wave parameters and response amplitude operators, leading to the establishment of an estimated wave spectrum. The effectiveness of the estimation method is validated through simulations with synthetic data. Second, an estimated wave disturbance model is developed and integrated into the control system, where the extended state observer-line of sight guidance law and the backstepping method are used for controller design. To address external disturbances beyond wave disturbance, an radial basis function neural network is adopted to approximate and compensate for errors. Finally, the proposed approach is further validated through simulation analysis and field experiments. In the experimental phase, real pitch data from the USV are used to estimate ocean waves, and a virtual navigator strategy is implemented. Path-following control tests are conducted on two different USV experimental platforms, achieving favorable control results and demonstrating that the method is both applicable and feasible across different platforms under sea states of level 2 and 3.
Keywords:
Field experiment
numerical simulation
particle swarm optimization (PSO)-sequential quadratic programming (SQP)
path-following control
wave spectrum estimation
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