This example shows how the Model Predictive Control Toolbox™ can use time-varying prediction models to achieve better performance when controlling a time-varying plant. The following …

Variations on optimal control problem • time varying costs, dynamics, constraints – discounted cost – convergence to nonzero desired state – tracking time-varying desired trajectory • …

Mar 1, 2019 · It is shown that the population-interaction structure can be modified dynamically along the time by adding conditions over the optimization problem constraints depending on …

20 hours ago · Regularized Model Predictive Control Komeil Nosrati, Senior Member, IEEE, Juri Belikov, Senior Member, ... effective solution for control problems with time-varying dy-namics. …

Abstract—In the article, we study the distributed model predic-tive control (DMPC) problem for a network of linear discrete-time systems, where the system dynamics are decoupled, the …

distributed model predictive control (DMPC) strategies with a system partitioning and by using density-dependent population games (DDPG) is presented. Key words: Predictive control, …

Jul 18, 2022 · When an RTO/scheduling layer is employed to generate feasible time-varying setpoints, it is naturally befitting to adopt an optimal controller, such as the widely popular …

The time-varying nature of the plant is captured by assuming known bounds on the rate of change of the model parameters in time. In the second step, a robust finite-horizon optimal control …

Nov 18, 2021 · In this paper, a stochastic model predictive control (MPC) is proposed for the wheeled mobile robot to track a reference trajectory within a finite task horizon. The wheeled …

In this paper, we propose a cooperative Kalman filter between two networks. The proposed Kalman filter alternately estimates signals in time between the two networks. We formulate a …