|
Vol: 51(65) No: 2 / June 2006 Fuzzy Control of Micro Hydro Power Plant Dimitar Lakov Department of Intelligent Computer Technologies, Institute of Computer and Communication Systems – Bulgarian Academy of Sciences, Acad. Bonchev street, Bl. 2, Sofia 1113, Bulgaria, phone: +3592 8737 601, e-mail: lakov@iccs.bas.bg Stanislav Vasilev Department of Intelligent Computer Technologies, Institute of Computer and Communication Systems – Bulgarian Academy of Sciences, Acad. Bonchev street, Bl. 2, Sofia 1113, Bulgaria, phone: +3592 8737 601, e-mail: stnani@abv.bg Keywords: MHPP, control modes, intelligent fuzzy logic control, hybrid control system. Abstract The paper presents a fuzzy intelligent approach for control of Micro Hydro Power Plant MHPP. The main idea of fuzzy intelligent approach is to combine expert knowledge with advanced control using fuzzy logic model. The aim of Intelligent The paper presents a fuzzy intelligent approach for control of Micro Hydro Power Plant MHPP. The main idea of fuzzy intelligent approach is to combine expert knowledge with advanced control using fuzzy logic model. The aim of Intelligent Control of MHPP application is twofold: firstly, to show improving of human machine interactions by system learning from operator’s expertise and secondly, to express an advanced technique associated with plant initialization and functioning in specific working conditions: initial tuning of system parameters, emerging situations, programable energy power production, ets. Two basic tasks are realized by fuzzy control: launching energy power generation and automatic goal tracing in uncertain, ambiguous defined conditions. Real sysytem implementation is based on advanced Beckhoff TwinCAT software system. References [1] http://www.fuzzytech.com/. [2] http://www.stowa-nn.ihe.nl/Applications_ANN_Fuzzy_Logic.htm. [3] R. BabuÅ¡ka and H.B. Verbruggen, “An overview of fuzzy modeling for controlâ€, Control Engineering Practice 1996; 4: 1593-1606. [4] IEEE Working Group, “Hydraulic turbine and turbine control models for system dynamic studiesâ€, IEEE Trans. Power Syst. Apparatus 1992; 7: 167-179. [5] S. Hagihara, H. Yokota, K. Gode and K. Isobe, “Stability of a hydraulic turbine-generating unit controlled by PID governorâ€, IEEE Trans. Power Syst. Apparatus 1979; 98: 2294-2298. [6] L.N. Hannett and B. Fardanesh, “Field test to validate hydro turbine governor model structure and parametersâ€, IEEE Trans. Power Syst. Apparatus 1994; 9: 1744-1751. [7] L.N. Hannet, J. W. Feltes, B. Fardanesh and W. Crean, “Modeling and control tuning of a hydro station with units sharing a common penstock sectionâ€, IEEE Trans Power Syst 1999; 14: 1407-1414. [8] J.-S.R. Jang, “ANFIS: Adaptive-network based fuzzy inference systemâ€, IEEE Trans. Systems, Man and Cybernetics 1993; 23: 665-685, 1993. [9] T. Takagi and M. Sugeno, “Fuzzy identification of systems and its applications to modeling and controlâ€, IEEE Trans System Man and Cybernetic 1985; 15:116-132 [10] D. Lakov and G. Kirov, “Soft computing agents in custom dependent productionâ€, MED 2002, the 10th Mediterranean Conference on Control and Automation, July 9-12, 2002 Lisbon, Portugal, 443-452. |