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According to the nonlinearity of the industrial process, it is difficult for traditional predictive control algorithm to establish an accurate mathematical model. In the paper, a two-step predictive control algorithm based on the least square support vector machine (LS-SVM) is proposed. In this algorithm, the nonlinear system is turned into linear system by adding the appropriate intermediate variables...
Often in face of deciding schemes with many factors in production and life, relational analysis of the factors is an important basis of decision. The decision method is analyzed and studied to avoid strong subjectivity and improve weighting rationality. Optimization and entropy of information are used to adjust the weighting values of each factor and BP neural network to learn how to train assignment...
In this paper, a square root extended set membership (SRESM) state estimation algorithm is proposed to further improve the numerical accuracy and stability of the nonlinear system estimation. In comparison with the existing extended set membership (ESM), the proposed square root ESM using the efficient and stable updating recursions provides much more accurate estimation results. It has improved numerical...
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