Ship rudder anti-pitching nonlinear predictive control base on information fusion optional estimate

This article presents a method to build a T-S fuzzy model based on Generalized Dynamic Fuzzy Neural Network (GD-FNN) of Elliptical Basis Function in order to solve the problem of slanting ship´s model uncertainty and nonlinear. The proposed method needs neither prior fuzzy neural networks structure knowledge nor prior training phase,it can be used to build the nonlinear and uncertain part through online adaptive learning algorithm. The fuzzy rules could be generated and pruned on-line by learning, and then get ship slanting rudder vertical (heaving and pitching) dynamic linear adaptive CARMA model. An iterative prediction control algorithm based on optimal estimation with information fusion is established according to the self-adaptive linearized model of the obtained system. The optimal estimation of costate sequences and control sequences are achieved by combining the soft constraint information of prospective referenced track and control energy, included in the quadratic form performance index function, and the hard constraint information of the system equation. The efficiency of the algorithm is shown by simulation experiment of system, which control effect of pitching achieved by 76%.