Model predictive control (MPC) is a very popular controller design method in the process industry. A key advantage of MPC is that it can accommodate constraints on the inputs and outputs. Usually MPC uses linear or nonlinear discrete-time models. In this paper we give an overview of some results in connection with model predictive control (MPC) approaches for some tractable classes of discrete-...

Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or nonlinear discrete-time models. Previously, we have extended MPC to a class of discrete event systems that can be described by a model that is “linear” in the max-plus algebra. In this paper we consider the stability of MPC for these max-plus linear (MPL) systems, and...

Model predictive control (MPC) in building HVAC systems incorporates predictions of weather and occupancy to determine the optimal operating setpoints. However, application of MPC strategies to large buildings might not be feasible in real time due to the large number of degrees of freedom in the underlying optimization problem. Decomposing the problem into several smaller sub-problems to be so...

Most academic control schemes for MIMO systems assume all the control variables are updated simultaneously. MPC outperforms other control strategies through its ability to deal with constraints. This requires on-line optimization, hence computational complexity can become an issue when applying MPC to complex systems with fast response times. The multiplexed MPC scheme described in this paper s...

In this paper we address the Model Predictive Control (MPC)-based path planning problem for Unmanned Aerial Vehicles (UAVs). Our goal is to find trajectories that are safe with respect to grounding and collision, fuel efficient and satisfy criteria for communication such that the UAVs form a chain with a given radio communication capacity. A centralized MPC and a distributed MPC approach to sol...

Model predictive control (MPC) is a very popular controller design method in the process industry. One of the main advantages of MPC is that it can handle constraints on the inputs and outputs. Usually MPC uses linear discrete-time models. Recently we have extended this framework to max-plus-linear discrete event systems. In this paper we further explore this topic. More specifically, we focus ...

Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be imple...

Myopericytoma (MPC) is a rare kind of benign neoplasm, showing derivation from perivascular myoid cells. About 115 cases have been reported in the English literature; however, most of the literature focuses on the description and classification of pathology. The case presented here is that of a 42-year-old woman with a surgical management experience of multicentric MPC in the maxillofacial regi...