Long-prediction-horizon nonlinear model predictive control (Q2776235)

One of the advantages of long-prediction-horizon model predictive control is its applicability to processes with nonminimum-phase behavior. Motivated by this attractive feature of the model predictive control, a long-prediction-horizon model predictive control formulation is used to derive an approximate input-output-linearising nonlinear control law for hyperbolically stable, single-input single-output processes, whether nonminimum-phase or minimum phase. Indeed, the problem of nonlinear control of a class of nonminimum-phase processes is solved by exploiting further the connections between model predictive control and input-output linearization. The derived control law has one single tunable parameter, and thus is very easy to tune. It is applied to linear processes, and the resulting linear control law is presented.NEWLINENEWLINEFor the entire collection see [Zbl 0976.00019].