Model Predictive Control, Constrained Optimization, Quadratic Programming, Modified Optimization

A significantly important part of model predictive control (MPC) with constraints is a solution of an optimization task. The result of the optimization is a vector of future increments of a manipulated variable. The first element of this vector is applied in the next sampling period of MPC in the framework of a receding horizon strategy. In practical realization of a multivariable MPC, the optimization is characterized by higher computational complexity. Therefore, reduction of the computational complexity of the optimization methods has been widely researched. One suitable principle of precomputing operations was proposed by Wang, L. This general optimization strategy is further modified in this paper. Decreasing of the computational complexity of the optimization by using of the proposed modification is discussed.