Model predictive control (MPC) is an advanced method of process control that 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. Model predictive controllers rely on dynamic models of the process (can be technological, biological or biomedical ...), 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. MPC has the ability to anticipate future events and can take control actions accordingly. PID and LQR 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.
Here are links and attached files in subject.
-Generalized Predictive Control And Bioengineering
https://books.google.dz/books?isbn=0748405976
-Biomedical Engineering Handbook 2
https://books.google.dz/books?isbn=354066808X
-World Congress of Medical Physics and Biomedical Engineering 2006: ...
https://books.google.dz/books?isbn=3540368418
-Generalised Predictive Control and Bioengineering - Professor M ...
www.sheffield.ac.uk › ... › Professor M.Mahfouf
-Computationally Efficient Model Predictive Control Algorithms: A ...
https://books.google.dz/books?isbn=3319042297
-Recent Advances in Optimization and its Applications in Engineering
La aplicación del control predictivo en biomedicina, es la de anteponerse a las perturbaciones propias de las variables del cuerpo humana que se este sensando, por ejemplo, azúcar en la sangre, hematositos en la orina, haciendo que el control predictivo haga los ajustes antes de que se presenten la perturbación o un instante después de que se hallan presentado..