Generalized Predictive Control Algorithm And Applied Research

Since the mathematical models of a lot of involved industrial systems in the control practices are difficult to be established, and that the structures'and parameters of industrial plants always have some uncertainties, it is hard to achieve the anticipated control indexes by using control theory and modern control theory. Generalized predictive control is one of the typical predictive control methods, and it is widely used in industry. Based on the research of the principle of generalized predictive control, the theory of fuzzy neural networks and radial basis function neural networks, and according to the complicated on-line calculation of generalized predictive control and that it is not suitable for nonlinear system, this paper proposes fuzzy neural networks generalized predictive control using a fuzzy radial basis function neural networks model. By simulating to the linear and the nonlinear system, the results certify that the proposed control method is in effect. In addition, the paper makes relatively in-depth analyses on the function approximation theory of radial basis function neural networks and the stability of the adaptive controller based on radial basis function neural networks.