Fuzzy issues in multivariable predictive control

Model predictive control (MPC) is a well-known control technique, which has been applied to complex and nonlinear processes. This paper integrates different fuzzy issues in multivariable predictive control. Fuzzy predictive control incorporates fuzzy goals and constraints in model predictive control, in a fuzzy decision making framework. Several issues are proposed in this paper for multivariable fuzzy predictive control, namely, the use of weighted fuzzy decision functions and fuzzy predictive filters. Simultaneous weighted satisfaction of various criteria is modeled by using the qualitative extensions of (Archimedean) fuzzy t-norms. The use of fuzzy predictive filters are represented as an adaptive set of control actions multiplied by gain factors. The integration of the several fuzzy issues proposed in this paper is applied to the control of a container gantry crane. Simulation results show the advantages of the proposed methods.