Third International Conference on Industrial Fuzzy Control and Intelligent Systems
Fuzzy control of machining process is undoubtedly a very promissory approach, taking on account m... more Fuzzy control of machining process is undoubtedly a very promissory approach, taking on account machinetool complexity and the need of increasing its efficiency. Creation of the knowledge basis for this fuzzy controller requires something more than operators experience: an objective support. Such objective support is to be obtained from experiments, during which the machinetool actually performs the cutting process and corresponding input and output data must begathered. A rather efficient approach, fuzzy chstering, was chosen for elaborating this data in order to obtain the wanted knowledge basis for the fuzzy model. The paper describes algorithms, experiments and fuzzy models of the cutting process in a milling machine. Models so obtained are to be the basis for designing model-based fuzzy supervisory controllers for this machine.
A fuzzy model of the cutting process has been obtained for a vertical milling-machine, adopting a... more A fuzzy model of the cutting process has been obtained for a vertical milling-machine, adopting a previously used technique (Sugeno-Yasukawa, 1991). The inputs are cutting speed, feed rate, depth of cut, tool diameter, and workpiece hardness, and the output is the result of the three-axis force sensing signal, working directly on the machine tool. The identification approach is a blackbox type, where only a file of I/O data is necessary to construct the model. The fuzzy model consists of a number of IF...THEN rules with fuzzy antecedents and consequents. Five fuzzy models have been generated according to the material type used. The output error and the relative output error have been used as performance indices of the fuzzy models.
Third International Conference on Industrial Fuzzy Control and Intelligent Systems
Fuzzy control of machining process is undoubtedly a very promissory approach, taking on account m... more Fuzzy control of machining process is undoubtedly a very promissory approach, taking on account machinetool complexity and the need of increasing its efficiency. Creation of the knowledge basis for this fuzzy controller requires something more than operators experience: an objective support. Such objective support is to be obtained from experiments, during which the machinetool actually performs the cutting process and corresponding input and output data must begathered. A rather efficient approach, fuzzy chstering, was chosen for elaborating this data in order to obtain the wanted knowledge basis for the fuzzy model. The paper describes algorithms, experiments and fuzzy models of the cutting process in a milling machine. Models so obtained are to be the basis for designing model-based fuzzy supervisory controllers for this machine.
A fuzzy model of the cutting process has been obtained for a vertical milling-machine, adopting a... more A fuzzy model of the cutting process has been obtained for a vertical milling-machine, adopting a previously used technique (Sugeno-Yasukawa, 1991). The inputs are cutting speed, feed rate, depth of cut, tool diameter, and workpiece hardness, and the output is the result of the three-axis force sensing signal, working directly on the machine tool. The identification approach is a blackbox type, where only a file of I/O data is necessary to construct the model. The fuzzy model consists of a number of IF...THEN rules with fuzzy antecedents and consequents. Five fuzzy models have been generated according to the material type used. The output error and the relative output error have been used as performance indices of the fuzzy models.
Uploads
Papers by Elena Aguero