Cascade predictive control for nonlinear fully-actuated systems with input saturation
WANG Xiu-bo
DUAN Guang-ren
Abstract：Predictive control based on fully actuated system(FAS)approaches employs nonlinear input transformations to map the original inputs into the desired linear closed-loop system inputs.This enables the construction of distributed linear predictive models,effectively reducing the complexity of solving the optimization problem.However,when the system owns input saturation,such input transformations introduce highly nonlinear constraint issues to the desired predic-tive model.To address this,this paper proposes a cascaded predictive control method and designs a cascaded predictive controller with a two-layer optimization structure.In the first layer of optimization,the predictive input sequence from the previous instant is used to optimize the linear boundaries of the transformed inputs within the predictive horizon.In the sec-ond layer of optimization,based on the newly defined linear constraints,a series of distributed linear optimization problems with slack factors are solved.This cascaded predictive method effectively avoids the nonlinear constraint issues caused by input transformations,reduces optimization complexity,improves the solvability of nonlinear optimization problems,and ensures the stability of the closed-loop system.Finally,the effectiveness of the proposed algorithm is verified through simulations on fully-actuated spacecraft attitude system and the under-actuated rotational translational actuator system.
Keywords：nonlinear systemspredictive controlfully actuated system approachescascade optimizationinput satu-ration
Publication Date：2025-12-30
Online Publishing Date：2026-03-05(First online date of this platform, not the publication date of the document)
Pages：10( 2419-2428 )