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A state estimation NLQDMC (nonlinear LQ dynamic matrix control) algorithm is presented for use with nonlinear input-output models. The proposed algorithm extends the state estimation NLQDMC presented previously by the authros (1992) to nonlinear models identified using input-output information. The algorithm preserves the computational advantages of the previous approach when compared to the other algorithms based on nonlinear programming techniques. The illustrating example given demonstrates the usage of tuning parameters and points out the benefits and shortcomings of the algorithm.