کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
382329 660757 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Robust adaptive control of a bio-inspired robot manipulator using bat algorithm
ترجمه فارسی عنوان
کنترل تطبیقی مقاوم بازوهای ربات زیستی الهام گرفته با استفاده از الگوریتم خفاش
کلمات کلیدی
ربات کاترپیلار؛ کنترل کننده PID جزء به جزء. کنترل مقاوم؛ کنترل تطبیقی، الگوریتم خفاش
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A new combined control law (AFOPIDSMC) proposed for chattering reduction.
• We apply an adaptive controller for updating FOPID parameters.
• A bio-inspired bat algorithm used for tuning the proposed controller parameters.
• The stability of the proposed controller is proved by Lyapunov theory.
• The simulation results show the effectiveness of the proposed control.

This paper proposes a novel adaptive fractional order PID sliding mode controller (AFOPIDSMC) using a Bat algorithm to control of a Caterpillar robot manipulator. A fractional order PID (FOPID) control is applied to improve both trajectory tracking and robustness. Sliding mode controller (SMC) is one of the control methods which provides high robustness and low tracking error. Using hybridization, a new combined control law is proposed for chattering reduction by means of FOPID controller and high trajectory tracking through using SMC. Then, an adaptive controller design motivated from the SMC is applied for updating FOPID parameters. A metaheuristic approach, the Bat search algorithm based on the echolocation behavior of bats is applied for optimal design of the Caterpillar robot in order to tune the parameter AFOPIDSMC controllers (BA-AFOPIDSMC). To study the effectiveness of Bat algorithm, its performance is compared with five other controllers such as PID, FOPID, SMC, AFOPIDSMC and PSO-AFOPIDSMC. The stability of the AFOPIDSMC controller is proved by Lyapunov theory. Numerical simulation results completely indicate the advantage of BA-AFOPIDSMC for trajectory tracking and chattering reduction.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 56, 1 September 2016, Pages 164–176
نویسندگان
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