A new sliding-mode control with fuzzy boundary layer

2001 ◽  
Vol 120 (1) ◽  
pp. 135-143 ◽  
Author(s):  
Heejin Lee ◽  
Euntai Kim ◽  
Hyung-Jin Kang ◽  
Mignon Park
Keyword(s):  
Boundary Layer ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Mode Control ◽  
Fuzzy Boundary

Sliding Mode-Like Fuzzy Logic Control With Adaptive Boundary Layer for Multiple-Variable Discrete Nonlinear Systems

2016 ◽  
Vol 25 (2) ◽  
pp. 209-220 ◽  
Author(s):  
Xiaoyu Zhang
Keyword(s):  
Boundary Layer ◽  
Fuzzy Logic ◽  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Fuzzy Logic Control ◽  
Sliding Mode ◽  
Mode Control ◽  
Logic Control ◽  
Chattering Free ◽  
Discrete Nonlinear Systems

AbstractMore serious chattering emerges in discrete systems of sliding mode control. The paper presents a sliding mode-like fuzzy logic control design, which eliminates the chattering, for a class of discrete nonlinear systems with multiple variables. First, the boundary layer is self-tuned on-line, and then, the chattering free is obtained. Consequently, the fuzzy logic control (FLC) is designed to approximate the sliding mode control (SMC) with boundary layer self-tuning. Finally, the performance of the robustness, chattering free, and adaption are verified by the simulation results.

Pneumatic position servo control of magnetic resonance compatible needle insertion robot

2012 ◽  
Vol 227 (7) ◽  
pp. 1469-1480 ◽  
Author(s):  
Shan Jiang ◽  
Wenhao Feng ◽  
Peng Zheng ◽  
Jun Liu ◽  
Jun Yang
Keyword(s):  
Boundary Layer ◽  
Steady State ◽  
Magnetic Resonance ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Needle Insertion ◽  
Servo Control ◽  
Mode Control ◽  
Position Servo Control ◽  
Position Servo

This paper presents a control methodology that enables nonlinear model-base control of pulse width modulated (PWM) pneumatic position servo control system of a magnetic resonance (MR) compatible needle insertion robot used for MRI-guided prostate brachytherapy. Sliding mode control with a boundary layer is investigated based on the equivalent continuous-time dynamic model. Considering chattering in sliding mode control applications, especially in motion control of the robot, a fuzzy method is developed to tune the boundary layer of the sliding mode controller. Simulation and experimental results indicate that the controller is effective in both position control and trajectory tracking. With the boundary layer increasing, the steady state error of the response is becoming larger; however the maximum error is less than 0.2 mm. This steady state performance meets the accuracy requirement.

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