2017
DOI: 10.1007/s13369-017-2747-0
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Decoupled Adaptive Neuro-Interval Type-2 Fuzzy Sliding Mode Control Applied in a 3DCrane System

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Cited by 7 publications
(2 citation statements)
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“…Therefore, intelligent control systems appeared that used fuzzy logic [15], [16], or neural networks [17], [18] as well as genetic algorithms [19]. Selma et al [14] and Benhellal et al [20] have used a combination of fuzzy logic and neural networks, or a combination of neural networks and genetic algorithms [21], [22] to improve the performance of the control system. Moreover, soft-computing tools, such as fuzzy logic, were also used to online tuning of the PID controller parameters without the need for a lever mathematical model [23], [24].…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, intelligent control systems appeared that used fuzzy logic [15], [16], or neural networks [17], [18] as well as genetic algorithms [19]. Selma et al [14] and Benhellal et al [20] have used a combination of fuzzy logic and neural networks, or a combination of neural networks and genetic algorithms [21], [22] to improve the performance of the control system. Moreover, soft-computing tools, such as fuzzy logic, were also used to online tuning of the PID controller parameters without the need for a lever mathematical model [23], [24].…”
Section: Introductionmentioning
confidence: 99%
“…Hai bộ điều khiển này thiết kế độc lập với nhau. Phương án thứ hai, đó là sử dụng cấu trúc phản hồifeedback[3][4][5][6][7][8][9] với các thuật toán điển hình như PD mở rộng, các thuật toán thông minh như fuzzy, mạng nơ ron, thuật toán trượt và kết hợp một số thuật toán. Các phương pháp này có ưu điểm là xem xét cầu trục dưới dạng cấu trúc phi tuyến gần với thực tế.…”
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