Predictive directional compensator for systems with input constraints

Nonlinearity caused by actuator constraint plays a destructive role in the overall performance of a control system. A model predictive controller can handle the problem by implementing a constrained optimization algorithm. Due to the iterative nature of the solution, however, this requires high computation power. In the present work we propose a new method to approach the problem by separating the constraint handling from the predictive control job. The input constraint effects are dealt with in a newly defined component called a predictive directional compensator, which works based on the directionality and predictive concepts. Through implementation of the proposed method, the computational requirement is greatly reduced with the least degradation of the closed-loop performance. Meanwhile, a new characteristic matrix has been defined by which directionality of SISO as well as nonminimum phase systems can be determined.