Model predictive control

Model predictive control

Model predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. In recent years it has also been used in power system balancing models and in power electronics. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system identification. The main advantage of MPC is the fact that it allows the current timeslot to be optimized, while keeping future timeslots in account. This is achieved by optimizing a finite time-horizon, but only implementing the current timeslot and then optimizing again, repeatedly, thus differing from a linear–quadratic regulator (

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enModel predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. In recent years it has also been used in power system balancing models and in power electronics. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system identification. The main advantage of MPC is the fact that it allows the current timeslot to be optimized, while keeping future timeslots in account. This is achieved by optimizing a finite time-horizon, but only implementing the current timeslot and then optimizing again, repeatedly, thus differing from a linear–quadratic regulator (
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MPC scheme basic.svg
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enModel predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. In recent years it has also been used in power system balancing models and in power electronics. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system identification. The main advantage of MPC is the fact that it allows the current timeslot to be optimized, while keeping future timeslots in account. This is achieved by optimizing a finite time-horizon, but only implementing the current timeslot and then optimizing again, repeatedly, thus differing from a linear–quadratic regulator (LQR). Also MPC has the ability to anticipate future events and can take control actions accordingly. PID controllers do not have this predictive ability. MPC is nearly universally implemented as a digital control, although there is research into achieving faster response times with specially designed analog circuitry. (GPC) and (DMC) are classical examples of MPC.
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Model predictive control
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enModel predictive control
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www.mathworks.com/matlabcentral/fileexchange/35825-model-predictive-control
apmonitor.com/wiki/index.php/Main/Control
sourceforge.net/projects/grampc
ifatwww.et.uni-magdeburg.de/syst/muAO-MPC/
predictive-control.com/
www.mathworks.com/products/mpc/
gekko.readthedocs.io/en/latest/
web.archive.org/web/20111008140805/http:/viewer.zmags.co.uk/publication/c87cd4eb%3Fpage=48%23/c87cd4eb/48/
www.i2c2.aut.ac.nz/Resources/Software/jMPCToolbox.html
www.scribd.com/doc/16955545/MPC-CEP-Qin-Badgwell
www.pidlab.com/en/psmpc-demo
apmonitor.com/wiki/index.php/Main/PythonApp
www.acadotoolkit.org
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Category:Control theory
Chemical plant
Collocation method
Control engineering
Control theory
Convex optimization
Convex polytope
Dependent variable
Direct multiple shooting method
Distributed parameter system
Dynamical system
Dynamic matrix control
Empirical
Euler–Lagrange equation
Exponential growth
Feed forward (control)
File:MPC scheme basic.svg
Generalized predictive control
Independent variable
Industrial process
Kalman filter
Linear algebra
Linear–quadratic regulator
MathWorks
MATLAB
Model identification
Oil refineries
Parametric programming
PID controller
Piecewise linear function
Power electronics
Power system
Preconditioning
Process control
Quantization (signal processing)
Shooting method
Simulink
Superposition principle
System identification
SameAs
Commande prédictive
Control predictivo por modelo
j9Xt
m.04604p
Modelo de controle preditivo
Model Predictive Control
Q1782962
Sterowanie predykcyjne
Управление с прогнозирующими моделями
Управління з прогнозуючими моделями
تحكم استشرافي
کنترل پیش‌بینانه مدل
मॉडल द्वारा अनुमानित नियंत्रण
模型預測控制
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Category:Control theory
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