Robust Control of Vectored-Thrust Cross-Domain Robots via Allocation-Aware Incremental Nonlinear Dynamic Inversion

Abstract

Vectored-thrust cross-domain robots must maintain accurate six-DOF motion under strong nearshore wave disturbances and strict actuator saturation/rate limits. Under such conditions, conventional controller-allocator separation can create a command-execution mismatch: the motion controller evolves based on an ideal generalized force that the constrained allocator cannot fully realize, which may induce windup-like accumulation and degrade 3D stabilization performance. To address this issue, this paper proposes an AllocationAware Incremental Nonlinear Dynamic Inversion (AA-INDI) framework that closes the loop with the realized allocated generalized force returned by the allocator. By updating the commanded generalized force around the previously realized input, the proposed architecture preserves command-execution consistency under saturation and vectoring-rate constraints. A fixed-time extended state observer is used to estimate lumped disturbances, a smoothed INDI law generates the incremental motion-control command, and a model predictive control allocator computes feasible thrust-vector commands. Comparative simulations against ADRC on a mission-oriented nearshore aquaculture-cage inspection trajectory under Sea State 2 show that AA-INDI achieves tighter 3D tracking, improved attitude stabilization, and smooth feasible actuation within thrust and vectoring limits.