PID controllers do not have this predictive ability. Also MPC has the ability to anticipate future events and can take control actions accordingly. 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). The main advantage of MPC is the fact that it allows the current timeslot to be optimized, while keeping future timeslots in account. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system identification. In recent years it has also been used in power system balancing models and in power electronics. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. Model predictive control ( MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints.
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