Robust model predictive control of the automatic operation boats for aquaculture

- We propose a robust model predictive control approach for the AOB.
- We design a mixed H2/H∞ cost function to improve control robustness.
- We construct a polyhedral predictive model to decrease computational complexity of MPC.

This paper proposes a robust model predictive control (RMPC) approach for the automatic operation boats to cast baits evenly along desired paths. The difficulties in the control design come from the control system model, which is nonlinear, underactuated, input saturated, and disturbed by time-varying signals. The RMPC overcomes these difficulties by the receding horizon optimization explicitly considering the input saturation and using the mixed H2/H∞ cost function. To decrease computational complexity of the RMPC, a polyhedral model is constructed as the predictive model based on dynamics of the path-following error. The feasibility and effectiveness of the proposed path-following control is verified by theoretical analysis and illustrated by simulations and experiments.