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This paper presents a robust model predictive control method for discrete nonlinear systems. Instead of conventional T-S fuzzy system where linear local models are used, T-S fuzzy system with nonlinear local models is adopted that the number of fuzzy rules is decreased and the computational burden is reduced. Meanwhile, persistent external disturbances are also considered in the T-S fuzzy systems...
This study presents an improved method for first-order plus dead-time (FOPDT) model identification from less step response data. Firstly, B-spline series expansions are used to approximate step responses, providing effective interpolation values for modeling computation. Then, to enhance modeling accuracy, a least-squares method with a regressive compensation scheme is proposed, which adaptively adjusts...
This paper presents an improved method of model parameters identification in frequency-domain for closed-loop multivariable processes. Based on reference input and process output data during the closed-loop sequence step tests, the process frequency-responses are estimated with signal frequency analysis. Using a min-max critical frequency search algorithm, only a least possible number of frequency...
In this paper, 5 key geometrical factors: the area ratio between the nozzle and constant-area section, nozzle exit position, diverging angle of nozzle, converging angle of mixing section and the length of constant-area section and different back pressures are considered to investigate the ejector performance under 209 working conditions with CFD model which is calibrated by experimental data. It is...
A control-oriented dynamic model for a ball mill coal-pulverizing system (BMCPS) has been developed by using mechanism analysis and experiment identification. The nonlinear equations are obtained based on simplified physical model and previous efforts in BMCPS modeling. Through computation of known physical values, identification of grouped coefficients, and heuristic adjustments, the model parameters...
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