Hybrid adaptive fuzzy controllers with application to robotic systems

Lin, Chih-Min; Mon, Yi-Jen

doi:10.1016/s0165-0114(02)00504-3

Cited by 19 publications

(11 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They used fuzzy controller to attenuate the chattering phenomenon in sliding mode control and invented the method of fuzzy sliding mode control. By using the algorithm of adaptive fuzzy sliding mode control, the control signal was softened and the chattering phenomenon was alleviated in a conventional sliding mode control system [6][7][8][9][10]. Fuzzy sliding mode control has heuristic characteristics because of its structure and the operation are simple.…”

Section: Introductionmentioning

confidence: 99%

Bionic fuzzy sliding mode control and robustness analysis

Hua

2015

Applied Mathematical Modelling

View full text Add to dashboard Cite

Please cite this article as: J. Hua, L-X. An, Y-M. Li, Bionic fuzzy sliding mode control and robustness analysis, Appl. Math. Modelling (2014), doi: http://dx.Abstract: A bionic fuzzy sliding mode control based on switching control item fuzzification is proposed for a class of uncertain nonlinear systems. This article introduces the biological adaptation strategies into sliding mode control under uncertain boundary circumstance and disturbances. The trait of this new method is the design of switching-type control item in the sliding mode controller by utilizing the biological active adaptation strategies..Moreover, we analyze the robustness of bionic fuzzy sliding mode control system and prove the stability of the closed-loop system in the sense of Lyapunov. Finally, the simulation result for the circle of inverted-pendulum system is effective and feasible. it shows that the bionic fuzzy sliding mode control is superior to the conventional fuzzy sliding mode control. This way makes the chattering phenomenon in the sliding mode control was been alleviated and ensures that the tracking error steady be zero.

show abstract

Section: Introductionmentioning

confidence: 99%

Bionic fuzzy sliding mode control and robustness analysis

Hua

2015

Applied Mathematical Modelling

View full text Add to dashboard Cite

show abstract

“…There has been much research involving designs for fuzz y logic based on sliding mode control, which is referred to as fuzzy sliding mode control [10].…”

Section: Introductionmentioning

confidence: 99%

Neural network based fuzzy sliding mode direct torque control for PMSM

Zhu

Mao

2010

2010 3rd International Conference on Computer Science and Information Technology

View full text Add to dashboard Cite

A fuzzy sliding mode controller based on radial basis function neural network (RBFNN) for permanent magnet synchronous machine (PMSM) is investigated in this paper, in which direct torque control (DTC) concept, variable structure control and space vector modulation (SVM) are integrated to achieve high performance. Fuzzy logic is used to adjust the gain of the corrective control of the sliding mode controller. A RBFNN is used to compute the equivalent control.The weights of the RBFNN are changed according to adaptive algorithm for the system state to hit the sliding surface and slide along it. The simulation results verify the validity of the adaptive neural network based fuzzy sliding mode controller in the presence of uncertainties.

show abstract

“…In the the fuzzy-tuning sliding mode controllers [1]- [4], the fuzzy rules are set up to tune the control gains and the slope of sliding surfaces to attenuate chattering according to the position of the representative point. The authors in [5] apply fuzzy tuning to moving the sliding surface (rotating and shifting) for fast and robust tracking control for a class of nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy sliding mode control for robotic manipulators

Gao

Sun

Wang

2010

2010 8th World Congress on Intelligent Control and Automation

View full text Add to dashboard Cite

An adaptive fuzzy sliding mode control scheme is designed for robotic manipulators. By transforming the sliding surface and using the hyperbolic tangent function, a fuzzy logic system is constructed to approximate the conventional sliding mode control. The continuous hyperbolic tangent function and the group of pseudo-sliding surfaces can eliminate the chattering effectively, and meanwhile, a satisfactory tracking accuracy can be achieved. Stability analysis shows that this approach can guarantee the boundedness of all the signals in the closed loop. Tracking performance is illustrated by simulation results.

show abstract

Hybrid adaptive fuzzy controllers with application to robotic systems

Cited by 19 publications

References 20 publications

Bionic fuzzy sliding mode control and robustness analysis

Bionic fuzzy sliding mode control and robustness analysis

Neural network based fuzzy sliding mode direct torque control for PMSM

Adaptive fuzzy sliding mode control for robotic manipulators

Contact Info

Product

Resources

About