Abstract
A fuzzy logic compensator is designed for feedback linearizable nonlinear systems with deadzone nonlinearity. The classification property of fuzzy logic systems makes them a natural candidate for the rejection of errors induced by the deadzone, which has regions in which it behaves differently. A tuning algorithm is given for the fuzzy logic parameters, so that the deadzone compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded parameter estimates. Formal nonlinear stability proofs are given to show that the tracking error is small. The fuzzy logic deadzone compensator is simulated on a one-link robot system to show its efficacy.
Highlights
Very accurate control is required in mechanical devices such as xy positioning tables [1], overhead crane mechanisms [2], robot manipulators [3], etc
We illustrate the effectiveness of fuzzy logic deadzone compensation with feedback linearization by computer simulation
A fuzzy logic deadzone compensator has been proposed for feedback linearizable nonlinear systems
Summary
Very accurate control is required in mechanical devices such as xy positioning tables [1], overhead crane mechanisms [2], robot manipulators [3], etc. For many of these devices, the performance is limited by deadzone, friction, and backlash. A number of control strategies have been developed to overcome the problems caused by the deadzone effects. The most relevant published strategies are: deadzone compensation using neural networks [4] and variable structure control [5]. Control of gear transmission servo system with asymmetric deadzone nonlinearity is proposed in [6] and [7].
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