An optimal sliding mode control based on immune-wavelet algorithm for underwater robotic manipulator

In this paper, a robust optimal Sliding Mode Controller (SMC) based on new algorithm of Artificial Immune System (AIS) is proposed for trajectory tracking of underwater manipulators. A new AIS algorithm is used to derive optimal values of surface parameters and boundary layer thickness in SMC with considering minimum torques and error. Surface parameters and boundary layer thickness are considered as antibody in AIS and Morlet wavelet is used for mutation of them. The simulation results show that the new algorithm is an effective method to optimal control of underwater manipulator and decreases the cost function at least 34% in comparison with conventional SMC method.

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