Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems |
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Authors: | Huynh Tuan-Tu Lin Chih-Min Le Nguyen-Quoc-Khanh Vu Mai The Nguyen Ngoc Phi Chao Fei |
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Affiliation: | 1.Department of Electrical Engineering, Yuan Ze University, No. 135, Yuandong Road, Zhongli, 320, Taoyuan, Taiwan, Republic of China ;2.Faculty of Mechatronics and Electronics, Lac Hong University, No. 10, Huynh Van Nghe Road, Bien Hoa, Dong Nai, 810000, Vietnam ;3.Professional Master Program in Artificial Intelligence in Medicine, Taipei Medical University, Taipei, 106, Taiwan ;4.Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei City, 106, Taiwan ;5.School of Intelligent Mechatronics Engineering, Sejong University, 98 Gunja-dong, Gwangjin-gu, Seoul, 143-747, South Korea ;6.Faculty of Mechanical and Aerospace Engineering, Sejong University, 98 Gunja-dong, Gwangjin-gu, Seoul, 143-747, South Korea ;7.Department of Cognitive Science, Xiamen University, Xiamen, China ; |
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Abstract: | This study aims to propose a more efficient hybrid algorithm to achieve favorable control performance for uncertain nonlinear systems. The proposed algorithm comprises a dual function-link network-based multilayer wavelet fuzzy brain emotional controller and a sign(.) functional compensator. The proposed algorithm estimates the judgment and emotion of a brain that includes two fuzzy inference systems for the amygdala network and the prefrontal cortex network via using a dual-function-link network and three sub-structures. Three sub-structures are a dual-function-link network, an amygdala network, and a prefrontal cortex network. Particularly, the dual-function-link network is used to adjust the amygdala and orbitofrontal weights separately so that the proposed algorithm can efficiently reduce the tracking error, follow the reference signal well, and achieve good performance. A Lyapunov stability function is used to determine the adaptive laws, which are used to efficiently tune the system parameters online. Simulation and experimental studies for an antilock braking system and a magnetic levitation system are presented to verify the effectiveness and advantage of the proposed algorithm. |
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