The conventional Generic Model Control (GMC) has no ability to handle the constraints explicitly

which limits the industrial application of this nonlinear control approach. In this paper

after introducing an approximate model based predictor

we present an optimization algorithm which is based on quadratic programming

with the ability to handle the linear constraints of manipulated and controlled variables and their moving velocities. After that

by combining the proposed optimization algorithm with the control law of GMC

a novel approach to the constrained Generic Model Control based on quadratic programming is developed. The proposed approach was compared with the nonlinear programming based constrained nonlinear control approach and with the nonlinear quadratic programming based dynamic matrix control approach via computer simulations

which demonstrated the effectiveness of the proposed approach.The proposed approach can be used in real time

and has the potential in industrial application.