The paper presents a robust adaptive MPC framework, termed UC-MPC, for linear systems with both matched and unmatched nonlinear uncertainties subject to state and input constraints. The key aspects are:
The framework uses an L1 adaptive controller (L1AC) to compensate for the matched uncertainties and provide uniform bounds on the error between the states and inputs of the actual system and a nominal system.
These uniform bounds are used to tighten the state and control constraints of the actual system, and an MPC is designed for the nominal system with the tightened constraints.
The proposed UC-MPC guarantees constraint satisfaction and achieves improved performance compared to existing robust or tube MPC methods.
Simulation results on a flight control example demonstrate the benefits of the proposed framework, showing that UC-MPC can achieve better tracking performance than MPC and tube MPC while enforcing the constraints.
The key advantages of UC-MPC are: 1) it can handle a broad class of uncertainties that are time-varying and state-dependent without a parametric structure, 2) it can handle unmatched disturbances, and 3) it improves tracking performance compared to existing robust or tube MPC solutions.
다른 언어로
소스 콘텐츠 기반
arxiv.org
더 깊은 질문