In the past ten years many Stochastic Model Predictive Control (SMPC) algorithms have
been developed for systems subject to stochastic disturbances and model uncertainties …

It has been witnessed that swarm systems are superior to individual agents in performing
complicated tasks. In recent years, new results in some branches of control for swarm …

Two stochastic model predictive control algorithms, which are referred to as distributionally
robust model predictive control algorithms, are proposed in this article for a class of discrete …

Two robust model predictive control (MPC) schemes are proposed for tracking unicycle
robots with input constraint and bounded disturbances: tube-MPC and nominal robust MPC …

This paper develops a distributed model predictive control algorithm for linear quadratic
optimal consensus of discrete-time multi-agent systems. The consensus state and control …

In the era of Industrial 4.0, the next-generation control system regards the cyber-physical
system (CPS) as the core ingredient thanks to the comprehensive integration of physical …

This paper investigates the problem of designing data-driven stochastic Model Predictive
Control (MPC) for linear time-invariant systems under additive stochastic disturbance, whose …

This technical note develops a new form of distributed stochastic model predictive control
(DSMPC) algorithm for a group of linear stochastic subsystems subject to additive …

As one of the research focuses in the field of intelligent driving, improving the performance of
path tracking has become a goal for many scholars. Among many path tracking control …

We propose a novel robust model agnostic predictive control (RoMAn-MPC) algorithm and
illustrate its application in randomly excited dynamical systems. Unlike conventional model …