This paper proposes a novel economic requirements-oriented online tuning strategy for
MPC, the design of which encompasses the well-known operational particularities of oil …

This paper presents a robust-adaptive nonlinear model predictive control (MPC) technique
that leverages past experiences to achieve tractability on computationally constrained …

This work presents Experience-driven Predictive Control (EPC) as a fast technique for
solving nonlinear model predictive control (NMPC) problems with uncertain system …

The proposed auto-tuning method is a layer of receding horizon optimization problem
whose objective function is able to consider the performance/robustness through the trade …

In this work, a new approach to integrate Model Predictive Control (MPC) and Real-Time
Optimization (RTO) layers within an hierarchic control structure is presented. When …

As autonomous systems are deployed in increasingly complex and uncertain environments,
safe, accurate, and robust feedback control techniques are required to ensure reliable …

This paper proposes an approach for the robust stabilization of systems controlled by MPC
strategies. Uncertain SISO linear systems with box‐bounded parametric uncertainties are …

A new predictive control technique has been proposed in this article. The proposed strategy
is based on the control matrix formulation combined with a tuning technique using model …

The generalized predictive controller (GPC) is an efficient strategy for controlling processes
with time-varying parameters, as long as the GPC tuning parameters are chosen correctly …

Many model predictive control (MPC) algorithms have been proposed in the literature
depending on the conditionality of the system matrix and the tuning control parameters. A …