Real-Time Control Algorithms for a Hybrid Electric Race Car Using a Two-Level Model Predictive Control Scheme

2017 ◽  
Vol 66 (12) ◽  
pp. 10911-10922 ◽  
Author(s):  
Mauro Salazar ◽  
Camillo Balerna ◽  
Philipp Elbert ◽  
Fernando P. Grando ◽  
Christopher H. Onder
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Control Algorithms ◽  
Real Time Control ◽  
Race Car ◽  
Time Control ◽  
Control Scheme ◽  
Level Model ◽  
Two Level Model

scholarly journals A Model Predictive Control Framework for Real-Time Optimisation of Water System Operations

10.29007/fg7g ◽  
2018 ◽  
Author(s):  
Henrik Madsen ◽  
Anne Katrine Falk ◽  
Rasmus Halvgaard
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Case Studies ◽  
Predictive Control ◽  
Large Scale ◽  
Water System ◽  
River System ◽  
Quadratic Program ◽  
Real Time Control ◽  
Time Control

We have developed a versatile Model Predictive Control (MPC) framework, which can handle real-time control of a large variety of water systems. The framework combines a fast-solvable optimisation model (a quadratic program) with evaluation and realignment by a detailed hydrological-hydrodynamic model. The flexibility of the MPC framework is highlighted by two case studies: (1) a large-scale river system with several weeks of travel time, and (2) an urban storm and wastewater system with a concentration time of about half an hour to one hour. Both case studies demonstrate a large potential for improving operations by system-wide real-time optimisation.

scholarly journals Polder Flushing: Model Predictive Control of Flushing Operations to Effective and Real Time Control of Salinity in Polders

2016 ◽  
Vol 154 ◽  
pp. 94-98
Author(s):  
Boran Ekin Aydin ◽  
Martine Rutten ◽  
Gualbert H.P. Oude Essink ◽  
Joost Delsman
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Real Time Control ◽  
Time Control

Survey of Optimal Control and Model Predictive Control with State Estimation and a Real Time Application

2020 ◽  
Vol 13 (1) ◽  
pp. 19-30
Author(s):  
László Dávid ◽  
Katalin György ◽  
László-Alpár Galaczi
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Industrial Applications ◽  
Electron Gun ◽  
Real Time Control ◽  
Practical Applications ◽  
Time Control ◽  
Self Tuning

AbstractThe optimal control and its limited version namely the model predictive control represent one of the most important nonlinear control alternatives nowadays. The success of them are also proven in many practical applications. These can provide for several industrial applications the optimal trajectory calculation as well as calculation of the real-time control signal. One successful version of this is Generalized Predictive Control (GPC). A big advantage of these control algorithms is that they solutions are able to take into account the limitations of the inputs, and the states. In some cases, it is important to know the mathematical model chosen and the complete state information. Otherwise, the model can be estimated during the operation. Our study shows through the control of the cathode heating of a high-power electron beam device the self-tuning adaptive control thus constructed. Using a suitable dynamic model and an extended Kalman estimator, we determine the estimated temperature of the two cathodes during operation and the saturation electron current, which ensures the maximum cathode life. The practical application was tested on a CTW 5/60 type electron gun.

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