Heuristic on-line tuning for nonlinear model predictive controllers using fuzzy logic

In this paper a systematic mechanism for on-line tuning of the non-linear model predictive controllers is presented. The proposed method automatically adjusts the prediction horizon P, the diagonal elements of the input weight matrix Λ, and the diagonal elements of the output weight matrix Γ for the sake of good performance. The desired good performance is cast as a time-domain specification. The control horizon (M) is left constant because of the importance of its relative value with respect to P. The concepts from fuzzy logic are used in designing the tuning algorithm. In the mechanism considered here, predefined fuzzy rules represent available tuning guidelines and the performance violation measure in the form of fuzzy sets determine the new tuning parameter values Therefore, the tuning algorithm is formulated as a simple and straightforward mechanism, which makes it more appealing for on-line implementation. The effectiveness of the proposed tuning method is tested through simulated implementation on three non-linear process examples. Two of these examples possess open-loop unstable dynamics. The result of the simulations shows that this method is successful and promising.