tailieunhanh - Control of electric motor machine tools using self organizing fuzzy logic controller

This paper addresses the application of a self-organizing fuzzy logic controller (SOFLC) to actively deal with the real-time variation of the plant’s characteristics. SOFLC is a heuristic methodology where the control rules are generated and improved automatically according to the evaluation of the system’s behavior, and to modify the control rule based on the system performance evaluation. | Journal of Automation and Control Engineering Vol. 3, No. 6, December 2015 Control of Electric Motor Machine Tools Using Self-Organizing Fuzzy Logic Controller Kyeong Mi Lee, Donggil Kim, and Dongik Lee School of Electronics Engineering, Kyungpook National University, Daegu, South Korea Email: rudal2419@, {eastroad, dilee}@ Abstract—For the control of electric motor which drives machine tools, it is important to achieve a high precision and accuracy. In general, PID-type controllers, which are widely used for industrial machine tools, exploit a ZieglerNichols based tuning method. However, it is difficult to perform real-time parameter tuning to obtain good performances under various operating modes. This paper addresses the application of a self-organizing fuzzy logic controller (SOFLC) to actively deal with the real-time variation of the plant’s characteristics. SOFLC is a heuristic methodology where the control rules are generated and improved automatically according to the evaluation of the system’s behavior, and to modify the control rule based on the system performance evaluation. The simulation is performed using Matlab/Simulink and the results of a comparison study between the proposed SOFLC controller and a PID type controller are presented to explore the performance and effectiveness of the proposed algorithm. methods. As described before, the resulting PID controller needs to adaptive in the presence of the change in operating environment. Typical auto-tuning methods for PID include Ziegler-Nichols, Astrom & Hagglund algorithm, and Cohen & Coonrule [4]. However, these approaches still suffer from difficulties in dealing with the rapid change of system characteristics [1]-[3] [5], so that the control system results in performance degradation. This paper presents a self-organizing fuzzy logic controller (SOFLC) to actively address the time-varying plant characteristics including randomly varying network delays and actuator .