A course in fuzzy systems and control
A course in fuzzy systems and control
Control system design guide: using your computer to understand and diagnose feedback controllers
Control system design guide: using your computer to understand and diagnose feedback controllers
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Self-constructing fuzzy neural network speed controller for permanent-magnet synchronous motor drive
IEEE Transactions on Fuzzy Systems
Two-Mode Adaptive Fuzzy Control With Approximation Error Estimator
IEEE Transactions on Fuzzy Systems
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This paper proposes a stable adaptive fuzzy controller applied to a servomotor for velocity tracking of time-varying references. The control law is composed of two parts. The first part comprises a Proportional controller plus feedforward compensation. An adaptive fuzzy compensator corresponds to the second part and counteracts the effects of nonlinear loads. The only a priori information about the servomotor parameters is a nominal value of the voltage input gain. A depart from current adaptive adaptive controllers is the fact that the proposed control law does not rely on a switching supervisor controller then avoiding chattering. Moreover, the desired time varying reference feeds the membership functions instead of using the measured velocity, which is contaminated by noise. In this way, less measurement noise is injected to the closed loop system. The Lyapunov stability method allows concluding uniform ultimate boundedness of the closed loop system solutions. Experiments performed on a laboratory prototype allow comparing the proposed approach against a Proportional Integral controller endowed with feedforward compensation.