2019/05/07 by Dominic Liao-McPherson, Liao-McPherson, Dominic, Marco M. Nicotra +3
Engineering · #Advanced Control Systems Optimization #FOS: Electrical engineering #FOS: Mathematics #Fault Detection and Control Systems #Fuel Cells and Related Materials #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1905.02684
openalex publication_date 2019/05/07 · openalex created_date 2022/07/23 · openalex updated_date 2026/07/28
Suboptimal model predictive control is a technique that can reduce the\ncomputational cost of model predictive control (MPC) by exploiting its\nrobustness to incomplete optimization. Instead of solving the optimal control\nproblem exactly, this method maintains an estimate of the optimal solution and\nupdates it at each sampling instance. The resulting controller can be viewed as\na dynamic compensator which runs in parallel with the plant. This paper\nexplores the use of the semismooth predictor-corrector method to implement\nsuboptimal MPC. The dynamic interconnection of the combined plant-optimizer\nsystem is studied using the input-to-state stability framework and sufficient\nconditions for closed-loop asymptotic stability and constraint enforcement are\nderived using small gain arguments. Numerical simulations demonstrate the\nefficacy of the scheme.\n