Self-tuning Fuzzy Logic Controller Based on Takagi-Sugeno Applied to Induction Motor Drives

Abstract

<span>Fuzzy logic controller has been the main focus for many researchers and industries in motor drives. The popularity of Fuzzy Logic Controller (FLC) is due to its reliability and ability to handle parameters changes during load or disturbance. Fuzzy logic design can be visualized in two categories, mamdani design or Takagi-Sugeno (TS). Mamdani type can facilitate the design process, however it require high computational burden especially with big number of rules and experimental testing. This paper, develop Self-Tuning (ST) mechanism based on Takagi-Sugeno (TS) fuzzy type. The mechanism tunes the input scaling factor of speed fuzzy control of Induction Motor (IM) drives Based on the speed error and changes of error. A comparison study is done between the standard TS and the ST-TS based on simulations approaches considering different speed operations. Speed response characteristics such as rise time, overshoot, and settling time are compared for ST-TS and TS. It was shown that ST-TS has optimum results compared to the standard TS. The significance of the proposed method is that, optimum computational burden reduction is achieved.</span>

A New design of fuzzy logic controller optimized By PSO-SCSO applied To SFO-DTC induction motor drive

“…The membership functions are assigned with seven fuzzy sets which are NB (negative big), NM (negative medium), NS (negative small), AZ (approximate zero), PS (positive small), PM (positive medium) and PB (positive big), in ascending order as shown in Figures 2(a), 2(b) and 2(c). Table 1 represents the basic linguistic rules which describe an FLC [9,11,14].…”

“…The fuzzy discourse universe is subdivided into seven zones involving 49 control rules [9]. The fuzzy rules are presented in Table 1.…”

“…In recent years, the phenomenal development of digital electronics has demonstrated the merit of using fuzzy logic algorithms to control many complex systems. Nowadays, fuzzy logic controllers (FLCs) [5][6][7] have been widely used successfully in industrial control system applications, such as: Electrical engineering [8,9], Medical field [10], Renewable energy [11][12][13][14], Robotics [15][16][17]. These complex applications are nonlinear and do not require good knowledge of their exact mathematical models.…”

Analysis and investigation of different advanced control strategies for high-performance induction motor drives

“…On the other hand, DTC strategy works by selecting the most [14]. DTC achieves a very quick transient response, but it experiences high torque ripples during steady-state and degraded performance at lower speed operations [15][16][17]. For decades, FOC and DTC have been the prominent control methods for high-performance induction motor drives [18][19][20][21].…”

Type-2 fuzzy logic controller optimized by wavelet networks for mobile robot navigation

“…This logic allows the representation and processing of inaccurate or approximate knowledge. It is expressed by a set of linguistic rules called fuzzy rules, which are used to control complex systems or scarcely modeled [2][3][4]. The number of applications based on fuzzy logic theory in the field of mobile robotics has increased significantly in recent years [5][6][7][8][9][10][11][12].…”