scholarly journals Adaptive Neural Network Based Fuzzy Sliding Mode Control of Robot Manipulator

10.5772/6205 ◽  
2008 ◽  
Author(s):  
Ayca Gokhan ◽  
Galip Cansever
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Adaptive Neural Network ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Fuzzy Sliding Mode

Fuzzy sliding mode control for a robot manipulator

2008 ◽  
Vol 13 (1) ◽  
pp. 124-128 ◽  
Author(s):  
Ha Quang Thinh Ngo ◽  
Jin-Ho Shin ◽  
Won-Ho Kim
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Fuzzy Sliding Mode

scholarly journals Advanced Interval Type-2 Fuzzy Sliding Mode Control for Robot Manipulator

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Ji-Hwan Hwang ◽  
Young-Chang Kang ◽  
Jong-Wook Park ◽  
Dong W. Kim
Keyword(s):  
Sliding Mode Control ◽  
Fuzzy System ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Control Law ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Fuzzy Sliding Mode ◽  
Interval Type

In this paper, advanced interval type-2 fuzzy sliding mode control (AIT2FSMC) for robot manipulator is proposed. The proposed AIT2FSMC is a combination of interval type-2 fuzzy system and sliding mode control. For resembling a feedback linearization (FL) control law, interval type-2 fuzzy system is designed. For compensating the approximation error between the FL control law and interval type-2 fuzzy system, sliding mode controller is designed, respectively. The tuning algorithms are derived in the sense of Lyapunov stability theorem. Two-link rigid robot manipulator with nonlinearity is used to test and the simulation results are presented to show the effectiveness of the proposed method that can control unknown system well.

Robust fuzzy sliding mode control for tracking the robot manipulator in joint space and in presence of uncertainties

Robotica ◽  
2013 ◽  
Vol 32 (3) ◽  
pp. 433-446 ◽  
Author(s):  
Mohammad Reza Soltanpour ◽  
Mohammad Hassan Khooban ◽  
Mahmoodreza Soltani
Keyword(s):  
Sliding Mode Control ◽  
Feedback Linearization ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Rule Base ◽  
Sliding Mode Controller ◽  
Fuzzy Sliding Mode Control ◽  
Ts Fuzzy Model ◽  
Mode Control ◽  
Fuzzy Sliding Mode

SUMMARYThis paper proposes a simple fuzzy sliding mode control to achieve the best trajectory tracking for the robot manipulator. In the core of the proposed method, by applying the feedback linearization technique, the known dynamics of the robot's manipulator is removed; then, in order to overcome the remaining uncertainties, a classic sliding mode control is designed. Afterward, by applying the TS fuzzy model, the classic sliding mode controller is converted to fuzzy sliding mode controller with very simple rule base. The mathematical analysis shows that the robot manipulator with the new proposed control in tracking the robot manipulator in presence of uncertainties has the globally asymptotic stability. Finally, to show the performance of the proposed method, the controller is simulated on a robot manipulator with two degrees of freedom as case study of the research. Simulation results demonstrate the superiority of the proposed control scheme in presence of the structured and unstructured uncertainties.

Optimization of hysteretic chaotic neural network based on fuzzy sliding mode control

2016 ◽  
Vol 189 ◽  
pp. 72-79 ◽  
Author(s):  
Guowei Xu ◽  
Fengnan Liu ◽  
Chunbo Xiu ◽  
Liankun Sun ◽  
Chang Liu
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Chaotic Neural Network ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Fuzzy Sliding Mode
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