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This paper presents fuzzy tracking control design for nonlinear systems. The design methodology is a synthesis of the tracking control theory of linear multivariable control and the Takagi-Sugeno fuzzy model. The observer-based stabilizing compensator type from multivariable tracking control theory is used, because not all states of the nonlinear system are fully available or measured while Takagi-Sugeno...
In this paper, an adaptive fuzzy sliding-mode formation controller (AFSFC) is designed to accomplish the formation tracking control of multi-robot systems. The multi-agent system with the proposed AFSFC can reach the desired formation asymptotically. Based on an adaptive tuning scheme, the external disturbances are dealt with and the analysis of the control stability is given. The simulation results...
An interval type-2 fuzzy neural network (IT2FNN) is developed for the position control of ball-and-beam systems to confront the noise. A T2FNN consists of a type-2 fuzzy linguistic process as the antecedent part and multi-layer neural network as the consequent part. The developed IT2FNN combines the merits of an interval type-2 fuzzy logic system and a neural network. Furthermore, the parameter-learning...
This paper proposes the design of fuzzy logic controllers to revolve a wheeled mobile robot (WMR) through digital images, and the design of WMR anti-collision system. After the image processing, the authors utilize the center of object image to design the fuzzy logic controllers that incorporate expert knowledge in terms of 9 linguistic rules to drive the WMR to revolve. By the way, the WMR can execute...
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