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One DOF robot manipulator control through type-2 fuzzy robust adaptive controller

Naderolasli Amir, Chatraei Abbas

Journal of Automation Mobile Robotics and Intelligent Systems

2019

Vol. 13, No. 1

65--70

In this article, the one DOF robot manipulator control is assessed through second type robust fuzzy-adaptive controller. The objective is to obtain a tracking path with appropriate accuracy. The stability of the closed loop system is verified through Lyapunov stability theory and the efficiency of tracking is analyzed subject to the constraints and uncertainty. In order to design the fuzzy controller a set of if-then fuzzy rules are considered which describe the system input-output behavior. Simulation and the results of the experiments on the one DOF robots indicate the effectiveness of the proposed methods.

Flatness-based adaptive fuzzy control of spark-ignited engines

Rigatos G.G., Siano P.

Journal of Artificial Intelligence and Soft Computing Research

2014

Vol. 4, No. 4

231--242

An adaptive fuzzy controller is designed for spark-ignited (SI) engines, under the constraint that the system’s model is unknown. The control algorithm aims at satisfying the H∞ tracking performance criterion, which means that the influence of the modeling errors and the external disturbances on the tracking error is attenuated to an arbitrary desirable level. After transforming the SI-engine model into the canonical form, the resulting control inputs are shown to contain nonlinear elements which depend on the system’s parameters. The nonlinear terms which appear in the control inputs are approximated with the use of neuro-fuzzy networks. It is shown that a suitable learning law can be defined for the aforementioned neuro-fuzzy approximators so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed adaptive fuzzy control scheme results in H∞ tracking performance. The efficiency of the proposed adaptive fuzzy control scheme is checked through simulation experiments.

Design of a robust adaptive fuzzy controller globally stabilizing the multi-input nonlinear system with state-dependent uncertainty

Park Y., Park G.

Control and Cybernetics

1998

Vol. 27, no 4

613-629

In this paper a novel robust adaptive fuzzy controller is proposed for the nonlinear system with state-dependent uncertainty. Compared with the conventional adaptive fuzzy controller that determines the function which bounds the uncertainty in the system dynamics by off-line calculation on the local state space, the proposed method determines that function by the fuzzy inference so that guarantees the stability of the closed loop system globally on the whole state space. In addition the method is applied to the multi-input system. We applied the proposed method to the Burn Control of the Tokamak fusion reactor whose dynamical equations contain the state-dependent uncertainty and proved the effectiveness of the scheme by the simulation results.