Adaptive control of flexible joint manipulators: comments on two papers
Automatica (Journal of IFAC)
Global tracking controllers for flexible-joint manipulators: a comparative study
Automatica (Journal of IFAC)
A course in fuzzy systems and control
A course in fuzzy systems and control
Singular Perturbation Methods in Control: Analysis and Design
Singular Perturbation Methods in Control: Analysis and Design
Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers
Engineering Applications of Artificial Intelligence
On the stability of interval type-2 TSK fuzzy logic control systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Robust Fuzzy Control of Electrical Manipulators
Journal of Intelligent and Robotic Systems
Fuzzy adaptive control of delayed high order nonlinear systems
International Journal of Automation and Computing
The hierarchical expert tuning of PID controllers using tools ofsoft computing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interval type-2 fuzzy logic systems: theory and design
IEEE Transactions on Fuzzy Systems
A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots
IEEE Transactions on Fuzzy Systems
A precise robust fuzzy control of robots using voltage control strategy
International Journal of Automation and Computing
Real-time compliance control of an assistive joint using QNX operating system
International Journal of Automation and Computing
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Type-1 fuzzy sets cannot fully handle the uncertainties. To overcome the problem, type-2 fuzzy sets have been proposed. The novelty of this paper is using interval type-2 fuzzy logic controller (IT2FLC) to control a flexible-joint robot with voltage control strategy. In order to take into account the whole robotic system including the dynamics of actuators and the robot manipulator, the voltages of motors are used as inputs of the system. To highlight the capabilities of the control system, a flexible joint robot which is highly nonlinear, heavily coupled and uncertain is used. In addition, to improve the control performance, the parameters of the primary membership functions of IT2FLC are optimized using particle swarm optimization (PSO). A comparative study between the proposed IT2FLC and type-1 fuzzy logic controller (T1FLC) is presented to better assess their respective performance in presence of external disturbance and unmodelled dynamics. Stability analysis is presented and the effectiveness of the proposed control approach is demonstrated by simulations using a two-link flexible-joint robot driven by permanent magnet direct current motors. Simulation results show the superiority of the IT2FLC over the T1FLC in terms of accuracy, robustness and interpretability.