Fuzzy Modeling of a Medium-Speed Pulverizer Using Improved Genetic Algorithms
Based on the analysis of its operational mechanism, an improved nonlinear model is developed for a medium-speed pulverizer. This is achieved by identifying a group of constant coefficients for a set of nonlinear differential equations with the aid of an improved genetic algorithm. The main objective of this research is to convert the nonlinear model into a T-S fuzzy model composed of several linear models, enabling easy design of the control system for the pulverizer. The simulation results show a satisfactory agreement between the T-S fuzzy model response and the measured data, confirming the effectiveness of the proposed method. Moreover, the proposed modeling method can be easily applied to other nonlinear systems, given that their nonlinear differential equations are known “a priori”.
KeywordsFuzzy Model Nonlinear Differential Equation Static Output Feedback Improve Genetic Algorithm Nonlinear Dynamic Characteristic
Unable to display preview. Download preview PDF.
- 3.Tanaka, S., Kurosaki, Y., Teramoto, T., Murakami, S.: Dynamic simulation analysis of MPS mill for coal fired boiler and application of its results to boiler control system. In: IFAC Symposium of Power Plant and Control, Beijing, China (1997)Google Scholar
- 4.Takagi, T., Sugeno, M.: Fuzzy Identification of Systems and Its Applications to Modeling and Control. IEEE Transactions on System, Man, and Cybernetics 1, 116–132 (1985)Google Scholar
- 5.Wu, H.N., Zhang, H.Y.: Reliable mixed L-2/H-infinity fuzzy static output feedback control for nonlinear systems with sensor faults. Automatica 11, 1925–1932 (2005)Google Scholar
- 8.Liu, H.P., Sun, F.C., Sun, Z.Q.: Stability analysis and synthesis of fuzzy singularly perturbed systems. IEEE Transactions on Fuzzy Systems 2, 273–284 (2005)Google Scholar
- 10.Huang, X.Y.: Operation and combustion regulation of boiler in power plants. Chinese electric power press, Beijing (2003)Google Scholar