Economic Predictive Control of a Pasteurization Plant using a Linear Parameter Varying Model

A two-layer control architecture for operational management and hydroelectricity production maximization in inland waterways using model predictive control

“…One of the most prominent advanced control strategies, and which has found much success in water systems management, is model predictive control (MPC). Broadly speaking, the sequence of control actions is determined as the solution of an optimization-based control problem that allows to achieve the operational objectives and complies with the set of restrictions, linked to physical/operational conditions and the system model [3]. Consequently, MPC offers an appropriate framework to fulfill operational management of water systems, because it enables calculation of optimal control actions ahead of time.…”

Health-Aware Economic MPC for Operational Management of Flow-Based Networks Using Bayesian Networks

“…For this purpose, there exists a systematic method to optimize the cost of a system management: the Economic MPC (EMPC) [2]. However, there is a well-known problem related with this strategy, which is the aim of obtaining a family of optimal setpoints considering economic efficiency rather than aiming the controlled system to reach a certain setpoint [2].…”

“…For this purpose, there exists a systematic method to optimize the cost of a system management: the Economic MPC (EMPC) [2]. However, there is a well-known problem related with this strategy, which is the aim of obtaining a family of optimal setpoints considering economic efficiency rather than aiming the controlled system to reach a certain setpoint [2]. Nevertheless, different approaches were suggested to enhance this concept, such as in Karimi Pour et al [3], where they implemented an LPV-MPC controller based on a single-layer economic optimization problem with dynamic constraints, including predetermined safety levels to deal with the demand uncertainty.…”

Health-aware control design based on remaining useful life estimation for autonomous racing vehicle

“…The idea of controlling nonlinear systems such as autonomous driving system considering LPV models has been widely investigated in the literature [13,14]. The main advantage of LPV models is that allows solving nonlinear problems in a quasi-linear mode by embedding the model non-linearities inside model parameters that depend on some scheduling variables [15]. In [16], authors propose a model predictive path tracking controller according to the vehicle dynamics and actuators conditions in its path tracking.…”