Satisfactory optimization control algorithm based on infinite-norm performance index

This paper investigates the use of fuzzy decision making in predictive control, the use of fuzzy goals and fuzzy constraints in predictive control allows for a more flexible aggregation of the control objectives than the usual weighting sum of squared errors. By defining the membership degree of the control objective and system constraint, and using the fuzzy interference, the optimal control problem with constraint, multi-objective multi-degree of freedom can be transferred as a convex optimal problem, so as to utilize the efficient optimal algorithm and guarantee the global optimal solution. More importantly, we can increase the freedom degree of control by adjusting the relevant membership degree parameters of control objective and system constraints. The designer's experience of control objective and system constraint can be utilized through the fuzzy inference of language variables, thus can get better understanding of effect for control performance.