Robotics: control, sensing, vision, and intelligence
Robotics: control, sensing, vision, and intelligence
Fuzzy self-organizing controller and its application for dynamic processes
Fuzzy Sets and Systems - Fuzzy Control
Introduction to Grey system theory
The Journal of Grey System
An introduction to fuzzy control
An introduction to fuzzy control
Control of Robot Manipulators
EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots
Information Sciences: an International Journal
Information Sciences: an International Journal
Dynamic structure adaptive neural fuzzy control for MIMO uncertain nonlinear systems
Information Sciences: an International Journal
A nonsmooth Levenberg-Marquardt method for solving semi-infinite programming problems
Journal of Computational and Applied Mathematics
Grey system theory-based models in time series prediction
Expert Systems with Applications: An International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Stability indices for a self-organizing fuzzy controlled robot: A case study
Engineering Applications of Artificial Intelligence
MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators
Information Sciences: an International Journal
Global Synchronization in an Array of Delayed Neural Networks With Hybrid Coupling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Paper: A linguistic self-organizing process controller
Automatica (Journal of IFAC)
Information Sciences: an International Journal
Menger's theorem for fuzzy graphs
Information Sciences: an International Journal
Enhanced adaptive grey-prediction self-organizing fuzzy sliding-mode controller for robotic systems
Information Sciences: an International Journal
Design of a grey-prediction self-organizing fuzzy controller for active suspension systems
Applied Soft Computing
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A self-organizing fuzzy controller (SOFC) under system control has online learning capabilities; nevertheless, the SOFC may excessively modify its fuzzy rules when its learning rate and weighting distribution are inappropriately selected. This results in oscillatory phenomena in the system during the control process. Moreover, the SOFC is mainly used to manipulate single-input single-output systems. When it is used to handle robotic systems, which are multiple-input multiple-output systems, the dynamic coupling effects between degrees of freedom (DOF) in the robotic systems are difficult to eliminate. To eliminate these problems, this study developed a grey-prediction self-organizing fuzzy controller (GPSOFC) for robotic systems. The GPSOFC introduces a grey-prediction algorithm into the SOFC to pre-correct fuzzy rules to reasonable ones for the control of robotic systems. This solves the problem caused by the inappropriate selection of parameters in the SOFC and compensates for the dynamic coupling effects between the DOFs in the robotic systems. To evaluate the feasibility of the proposed method, this study used the GPSOFC to manipulate a 6-DOF robot to determine its control performance. The GPSOFC yielded better control performance than the SOFC for robotic motion control, as shown in experimental results.