Enhanced two-loop model predictive control design for linear uncertain systems

A Linear Matrix Inequality (LMI) Approach to Robust Model Predictive Control (RMPC) Design in Nonlinear Uncertain Systems Subjected to Control Input Constraint

In this paper, a robust model predictive control (MPC) algorithm is addressed for nonlinear uncertain systems in presence of the control input constraint. For achieving this goal, firstly, the additive and polytopic uncertainties are formulated in the nonlinear uncertain systems. Then, the control policy can be demonstrated as a state feedback control law in order to minimize a given cost funct...

Model Based Predictive Control for Linear Systems

Model predictive control for uncertain max-min-plus-scaling systems

In this paper we extend the classical min-max model predictive control framework to a class of uncertain discrete event systems that can be modeled using the operations maximization, minimization, addition and scalar multiplication, and that we call max-min-plus-scaling (MMPS) systems. Provided that the stage cost is an MMPS expression and considering only linear input constraints then the open...

Distributed Stochastic Model Predictive Control Synthesis for Large-Scale Uncertain Linear Systems

This paper presents an approach to distributed stochastic model predictive control (SMPC) of large-scale linear systems with additive disturbances and multiplicative uncertainties in a plug-and-play (PnP) framework. Typical SMPC approaches for such problems involve formulating a large-scale finite-horizon chance-constrained optimization problem at each sampling time, which is in general non-con...

Design and Analysis of Nonlinear Control for Uncertain Linear Systems

By using the input–output information, the problem of robust output tracking control is addressed for linear dynamical systems with arbitrary relative degrees. The considered systems are confined to minimum phase systems with unknown parameters, and unmatched disturbances composed of a bounded part and a class of unmodeled dynamics. The a priori knowledge concerning the disturbance bounds is un...