Operating in the near-vicinity of marine energy devices poses significant challenges to the control of underwater vehicles, predominantly due to the presence of large magnitude wave disturbances causing hazardous state perturbations. Approaches to tackle this problem have varied, but one promising solution is to adopt predictive control methods. Given the predictable nature of ocean waves, the potential exists to incorporate disturbance estimations directly within the plant model; this requires inclusion of a wave predictor to provide online preview information. To this end, this paper presents a Nonlinear Model Predictive Controller with an integrated Deterministic Sea Wave Predictor for trajectory tracking of underwater vehicles. State information is obtained through an Extended Kalman Filter, forming a complete closed-loop strategy and facilitating online wave load estimations. The strategy is compared to a similar feed-forward disturbance mitigation scheme, showing mean performance improvements of 51% in positional error and 44.5% in attitude error. The preliminary results presented here provide strong evidence of the proposed method's high potential to effectively mitigate disturbances, facilitating accurate tracking performance even in the presence of high wave loading.

翻译：在海洋能源设备附近区域作业对水下航行器的控制提出了重大挑战，这主要是由于大幅值波浪扰动导致危险的状态扰动。解决该问题的方法多种多样，但一种有前景的方案是采用预测控制方法。鉴于海浪的可预测性，存在将扰动估计直接纳入被控对象模型的潜力；这需要包含一个波浪预测器以提供在线预览信息。为此，本文提出了一种集成确定性海浪预测器的非线性模型预测控制器，用于水下航行器的轨迹跟踪。通过扩展卡尔曼滤波器获取状态信息，形成完整的闭环策略，并实现在线波浪载荷估计。将该策略与类似的前馈扰动抑制方案进行比较，结果显示位置误差和姿态误差的平均性能分别提升了51%和44.5%。本文展示的初步结果为所提方法在有效抑制扰动方面的高潜力提供了有力证据，即使在高波浪载荷下也能实现精确的跟踪性能。