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Sliding Mode Control Based on Genetic Algorithm Optimization Applied to Manipulator Robot

Author(s): Ahmad Riyad Firdaus

ISSN 1693-6930

Volume: 10;
Issue: 4;
Start page: 645;
Date: 2012;
Original page

Keywords: Sliding Mode Controller (SMC) | manipulator robot | nonlinear system | tracking error | genetic algorithm.

The dynamical model of manipulator robot is represented by equations systems which are nonlinear and strongly coupled. Furthermore, the inertial parameters of manipulator depend on the payload which is often unknown and variable. So, to avoid these problems we studied sliding mode controller which is well suited to manipulator robot application. The sliding mode controller provides an effective and robust means of controlling nonlinear plants. The performance of sliding mode controller depends on parameter selection of gain switching and sliding surface constant. In this paper, a parameter selection algorithm is proposed by genetic algorithm to select the gain switching and sliding surface constant parameter s so that the controlled system can achieve a good overall performance in the sliding mode controller design. The searching of these parameter values is done by evaluating the fitness function of chromosome which is defined in this algorithm. A better overall performance is presented by smaller time response and tracking error of the output state.
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