Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
A course in fuzzy systems and control
A course in fuzzy systems and control
Parallel fuzzy P+fuzzy I+fuzzy D controller: Design and performance evaluation
International Journal of Automation and Computing
Robust Fuzzy Control of Electrical Manipulators
Journal of Intelligent and Robotic Systems
Adaptive control of robot manipulator using fuzzy compensator
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Robust tracking control of an electrically driven robot: adaptive fuzzy logic approach
IEEE Transactions on Fuzzy Systems
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A robotic system including the robot manipulator and motors is highly nonlinear, heavily coupled and multivariable in a non-companion form. To guarantee stability of the tracking control, a multivariable fuzzy controller may be designed; however the controller becomes computationally extensive. In contrast, a PD fuzzy controller is computationally simple in a decentralized structure; however a precise performance may not be provided. To remove the shortcoming, this paper presents a novel fine-tuning fuzzy control of robots which is computationally simple with a guaranteed stability. Its performance is better than the PD fuzzy controller due to having the fine-tuning ability. Unlike the adaptive fuzzy control which adapts all fuzzy rules, the fine-tuning fuzzy control adapts only one fuzzy rule. The convergence analysis is efficiently used to obtain a simple design with high-accuracy response, robust tracking performance and guaranteed stability. Simulation results using an articulated electrically driven robot manipulator shows superiority of the fine-tuning fuzzy control over the PD fuzzy control in the set point and tracking control.