Therefore, the presence of the plant model is a necessary condition for the development of the predictive control. The success of MPC depends on the degree of precision of the plant model. In practice, modelling real plants inherently includes uncertainties that have to be considered in control design, that is control design procedure has to guarantee robustness properties such as stability and...

This thesis extends Model Predictive Control (MPC) for constrained linear systems subject to uncertainty, including persistent disturbances, estimation error and the effects of delay. Previous work has shown that feasibility and constraint satisfaction can be guaranteed by tightening the constraints in a suitable, monotonic sequence. This thesis extends that work in several ways, including more...

Here the idea of data driven is introduced in model predictive control to establish our proposed data-driven control. Considering one first-order discrete time nonlinear dynamical ...

the control of fluidized-bed operations processes is still one of the major areas of research due to the complexity of the process and the inherent nonlinearity and varying dynamics involved in its operation. there are varieties of problems in chemical engineering that can be formulated as nonlinear programming (nlps). the quality of the developed solution significantly affects the performance ...

A critical engineering challenge in quantum technology is the accurate control of dynamics. Model-based methods for optimal have been shown to be highly effective when theory and experiment closely match. Consequently, realizing high-fidelity processes with model-based requires careful device characterization. In processors based on cold atoms, Hamiltonian can well-characterized. For supercondu...