A New Robust Adaptive Decentralized Tube Model Predictive Control of Continuous Time Uncertain Nonlinear Large-Scale Systems

In this paper, a new decentralized model predictive control has been proposed for continuous-time nonlinear large-scale systems made of multiple interconnected subsystems and uncertain systems with disturbances. This approach is characterized by: (I) consideration of input and state constraints, (II) no requirement for information transmission between local control rules, (III) robustness of local controllers to uncertainty in model and disturbances.; (IV) bounded disturbances in subsystems, but their upper bound is not specified; (V) a robust invariant set for each controller; (VI) proven closed-loop system overall stability and convergence. In order to show the key features and the performance of the proposed algorithm, a simulation model has been provided.