The Design of Robotic Arm Adaptive Fuzzy Controller Based on Oscillator and Differentiator

<p class="AbstractText">State variables are acquired when tracking the trace of the robotic arm with adaptive fuzzy controller. Since some variables are difficult to or cannot be measured directly, we introduced the second order oscillator and the second order differentiator that converges in finite time to obtain the value of each state variable. In this paper, a model based on the dynamics analysis of robotic arm was build to design the second order oscillator and the second order differentiator that converges in finite time to obtain the value of each state variable. The designed adaptive fuzzy controller for robotic arm achieved high accuracy in trace tracking. Simulation results of two-link robotic arm show the adaptive fuzzy controller for robotic arm based on differentiators is adaptable, flexible. This controller is simple to design, easy to implement, and has a good value for the application of robotic arm system.</p>

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Research of Robust Adaptive Fuzzy Control in Manipulator

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.317-319.713 ◽

2011 ◽

Vol 317-319 ◽

pp. 713-717

Author(s):

Hong Lin Li ◽

Peng Bing Zhao

Keyword(s):

Fuzzy Control ◽

Influencing Factors ◽

Fuzzy Controller ◽

Adaptive Fuzzy Control ◽

Random Disturbance ◽

State Variables ◽

Adaptive Fuzzy Controller ◽

Adaptive Fuzzy ◽

Load Variation ◽

Robust Adaptive

There are friction characteristics, random disturbance, load variation and other nonlinear influencing factors in the multi-joint manipulator system generally. According to the problem that the traditional PID and fuzzy control are difficult to achieve rapid and high-precision control for this kind of system, a kind of robust adaptive fuzzy controller was designed based on fuzzy compensation under the circumstances that the fuzzy information can be known and all the state variables can be measured. Simultaneously, in order to reduce the computational load of fuzzy approximation and improve the efficiency of mathematical operation, a method that distinguishing different disturbance compensatory terms and approximating each of them respectively was adopted. The simulation results show that the robust adaptive fuzzy controller based on fuzzy compensation can restrain friction, disturbance, load variation and other nonlinear influencing factors.

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Robust adaptive fuzzy controller with supervisory compensator for MEMS gyroscope sensor

Robotica ◽

10.1017/s026357471400294x ◽

2015 ◽

Vol 34 (10) ◽

pp. 2330-2343 ◽

Cited By ~ 1

Author(s):

Yunmei Fang ◽

Jian Zhou ◽

Juntao Fei

Keyword(s):

Fuzzy Inference ◽

Fuzzy Controller ◽

Adaptive Controller ◽

State Variables ◽

Inference System ◽

Mems Gyroscope ◽

Adaptive Fuzzy Controller ◽

Adaptive Fuzzy ◽

Robust Adaptive ◽

Gyroscope Sensor

SUMMARYIn this paper, a robust adaptive fuzzy controller is proposed to improve the robustness and position tracking of a MEMS gyroscope sensor. The proposed controller is designed as an indirect adaptive fuzzy controller with a supervisory compensator. It incorporates a fuzzy inference system with an adaptive controller in a unified Lyapunov framework, which can approximate and compensate for the unknown system dynamics and nonlinearities in the MEMS gyroscope. The parameters of the membership functions in the fuzzy controller can be adjusted online based on the Lyapunov method. Moreover, a supervisory controller is employed to guarantee the asymptotic stability of the closed-loop system and boundedness of the state variables in the MEMS gyroscope model. Numerical simulations demonstrate the proposed robust adaptive fuzzy controller has satisfactory tracking performance and robustness in the presence of external disturbances.

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