Design of self-learning multivariable fuzzy controller based on fuzzy sliding-mode

2002 ◽  
Author(s):  
Yong Qin ◽  
Limin Jia
Keyword(s):  
Fuzzy Controller ◽  
Sliding Mode ◽  
Fuzzy Sliding Mode ◽  
Self Learning

Sensorless Control for PMLSM Based on Fuzzy Sliding Mode Observer

2014 ◽  
Vol 556-562 ◽  
pp. 2270-2273
Author(s):  
Hua Cai Lu ◽  
Juan Ti ◽  
Yi Ming Yuan ◽  
Li Sheng Wei
Keyword(s):  
Boundary Layer ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Sensorless Control ◽  
Sliding Mode Observer ◽  
Mode Function ◽  
Fuzzy Sliding Mode ◽  
The Difference ◽  
Current Error

In this paper, a new sensorless control method is proposed for a permanent magnet linear synchronous motor based on Fuzzy sliding mode observer, which combines the advantages of sliding mode observer and Fuzzy controller respectively. The difference between the current estimated value and the actual current value is regarded as sliding mode function; sliding mode function (current error) and variation of the error are used as the input of fuzzy controller, and the width of the boundary layer as the output, adjusting the width of the boundary layer dynamically in real time. The simulation results show that Fuzzy sliding mode observer is able to find a balance between soft chattering and steady-state error, keep the system robustness and control precision.

Chaotic Gyros Synchronization

2011 ◽  
pp. 183-209
Author(s):  
M. Roopaei ◽  
M. J. Zolghadri ◽  
B. S. Ranjbar ◽  
S. H. Mousavi ◽  
H. Adloo ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Dead Zone ◽  
Control Input ◽  
Mode Control ◽  
Fuzzy Sliding Mode ◽  
Robust Adaptive ◽  
Fuzzy Parameter

In this chapter, three methods for synchronizing of two chaotic gyros in the presence of uncertainties, external disturbances and dead-zone nonlinearity are studied. In the first method, there is dead-zone nonlinearity in the control input, which limits the performance of accurate control methods. The effects of this nonlinearity will be attenuated using a fuzzy parameter approximator integrated with sliding mode control method. In order to overcome the synchronization problem for a class of unknown nonlinear chaotic gyros a robust adaptive fuzzy sliding mode control scheme is proposed in the second method. In the last method, two different gyro systems have been considered and a fuzzy controller is proposed to eliminate chattering phenomena during the reaching phase of sliding mode control. Simulation results are also provided to illustrate the effectiveness of the proposed methods.

Gain Scheduling Fuzzy Sliding Mode Strategy for Robotic Motion Control

2010 ◽  
Author(s):  
Shiuh-Jer Huang ◽  
Shian-Shin Wu ◽  
You-Min Huang
Keyword(s):  
Motion Control ◽  
Pulse Width Modulation ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Gain Scheduling ◽  
Industrial Applications ◽  
System Control ◽  
Model Free ◽  
Robotic Motion ◽  
Fuzzy Sliding Mode

A Mitsubishi Movemaster RV-M2 robotic system control system is retrofitted into system-on-programmable-chip (SOPC) control structure. The software embedded in Altera Nios II field programmable gate array (FPGA) micro processor has the functions of using UART to communicate with PC, robotic inverse kinematics calculation, and robotic motion control. The digital hardware circuits with encoder decoding, limit switch detecting, pulse width modulation (PWM) generating functions are designed by using Verilog language. Since the robotic dynamics has complicate nonlinear behavior, it is impossible to design a MIMO model-based controller on micro-processor. Here a novel model-free fuzzy sliding mode control with gain scheduling strategy is developed to design the robotic joint controller. This fuzzy controller is easy to implement with 1D fuzzy control rule and less trial-and-error parameters searching work. The experimental results show that this intelligent controller can achieve quick transient response and precise steady state accuracy for industrial applications.

Attitude Control of Flapping Wing Micro Aerial Vehicle Based on Double Fuzzy Sliding Mode Control

2012 ◽  
Vol 468-471 ◽  
pp. 704-707
Author(s):  
Sheng Bin Hu ◽  
Wen Hua Lu ◽  
Zhi Yi Chen ◽  
Lei Lei ◽  
Yi Xuan Zhang
Keyword(s):  
Sliding Mode Control ◽  
Attitude Control ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Micro Aerial Vehicle ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Control Scheme ◽  
Aerial Vehicle ◽  
Fuzzy Sliding Mode

An adaptive Double Fuzzy Sliding Mode Control scheme for attitude control of Flapping Wing Micro Aerial Vehicle is proposed in this paper. Based on the feedback linearization technique, a sliding mode controller is designed. To faster response speed, a fuzzy controller is designed to adaptively tune the slope of sliding mode surface. To reduce the chattering, another fuzzy controller is designed to adaptively tune the switch part of sliding mode control. The system stability is proved by Lyapunov principle. Simulation results show that the proposed control scheme is effective.

Fuzzy Sliding Mode Control for a Three-Links Spatial Robot Based on RBF Neural Network

2011 ◽  
Vol 141 ◽  
pp. 303-307 ◽  
Author(s):  
Sheng Bin Hu ◽  
Min Xun Lu
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Basis Function ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Sliding Mode Controller ◽  
System A ◽  
Radial Basis ◽  
Fuzzy Sliding Mode

To achieve the tracing control of a three-links spatial robot, a adaptive fuzzy sliding mode controller based on radial basis function neural network is proposed in this paper. The exponential sliding mode controller is divided into two parts: equivalent part and exponential corrective part. To realize the control without the model information of the system, a radial basis function neural network is designed to estimate the equivalent part. To diminish the chattering, a fuzzy controller is designed to adjust the corrective part according to sliding surface. The simulation studies have been carried out to show the tracking performance of a three-links spatial robot. Simulation results show the validity of the control scheme.

scholarly journals Adaptive Backstepping Fractional Fuzzy Sliding Mode Control of Active Power Filter

2019 ◽  
Vol 9 (16) ◽  
pp. 3383 ◽  
Author(s):  
Fei ◽  
Wang ◽  
Cao
Keyword(s):  
Fractional Order ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Harmonic Distortion ◽  
Active Power Filter ◽  
Active Power ◽  
Power Filter ◽  
Fuzzy Sliding Mode ◽  
Fractional Order Controller

An adaptive fractional-order fuzzy control method for a three-phase active power filter (APF) using a backstepping and sliding mode controller is developed for the purpose of compensating harmonic current and stabilizing the DC voltage quickly. The dynamic model of APF is changed to an analogical cascade system for the convenience of the backstepping strategy. Then a fractional-order sliding mode surface is designed and a fuzzy controller is proposed to approximate the unknown term in the controller, where parameters can be adjusted online. The simulation experiments are conducted and investigated using MATLAB/SIMULINK software package to verify the advantage of the proposed controller. Furthermore, the comparison study between the fractional-order controller and integer-order one is also conducted in order to demonstrate the better performance of the proposed controller in total harmonic distortion (THD), a significant index to evaluate the current quality in the smart grid.

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