Seaweed biomass offers significant potential for climate mitigation, but
large-scale, autonomous open-ocean farms are required to fully exploit it. Such
farms typically have low propulsion and are heavily influenced by ocean
currents. We want to design a controller that maximizes seaweed growth over
months by taking advantage of the non-linear time-varying ocean currents for
reaching high-growth regions. The complex dynamics and underactuation make this
challenging even when the currents are known. This is even harder when only
short-term imperfect forecasts with increasing uncertainty are available. We
propose a dynamic programming-based method to efficiently solve for the optimal
growth value function when true currents are known. We additionally present
three extensions when as in reality only forecasts are known: (1) our methods
resulting value function can be used as feedback policy to obtain the
growth-optimal control for all states and times, allowing closed-loop control
equivalent to re-planning at every time step hence mitigating forecast errors,
(2) a feedback policy for long-term optimal growth beyond forecast horizons
using seasonal average current data as terminal reward, and (3) a discounted
finite-time Dynamic Programming (DP) formulation to account for increasing
ocean current estimate uncertainty. We evaluate our approach through 30-day
simulations of floating seaweed farms in realistic Pacific Ocean current
scenarios. Our method demonstrates an achievement of 95.8% of the best possible
growth using only 5-day forecasts. This confirms the feasibility of using
low-power propulsion and optimal control for enhanced seaweed growth on
floating farms under real-world conditions.

利用动态规划优化控制来利用海流控制海藻生长，可实现在真实世界条件下通过低功率推进和优化控制实现漂浮海藻场的增强生长。