2022/10/20 by Miguel Castroviejo Fernandez, Fernandez, Miguel Castroviejo, Jordan Leung +3
Computer Science · Engineering · #Adaptive Control of Nonlinear Systems #Advanced Control Systems Optimization #FOS: Electrical engineering #Fault Detection and Control Systems #Systems and Control (eess.SY) #cs.SY #eess.SY #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2210.10995
arxiv created 2022/10/20 · openalex publication_date 2022/10/20 · arxiv updated 2022/10/21 · openalex created_date 2022/10/24 · openalex updated_date 2026/07/28
In this paper, a control scheme is developed based on an input constrained Model Predictive Controller (MPC) and the idea of modifying the reference command to enforce constraints, usual of Reference Governors (RG). The proposed scheme, referred to as the RGMPC, requires optimization for MPC with input constraints for which fast algorithms exist, and can handle (possibly nonlinear) state and input constraints. Conditions are given that ensure recursive feasibility of the RGMPC scheme and finite-time convergence of the modified command to the the desired reference command. Simulation results for a spacecraft rendezvous maneuver with linear and nonlinear constraints demonstrate that the RGMPC scheme has lower average computational time as compared to state and input constrained MPC with similar performance.