Comparative Analysis of Neural-Network and Fuzzy Auto-Tuning Sliding Mode Controls for Overhead Cranes under Payload and Cable Variations

<table class="fixed-width table-group" id="tab2"><tr><td><table class="table"><colgroup><col style="width:4.42em"/><col style="width:2.61em"/><col style="width:2.92em"/><col style="width:2.65em"/><col style="width:2.71em"/><col style="width:2.32em"/><col style="width:2.73em"/></colgroup><tr><td class="thead-hr" colspan="7"><hr/></td></tr><tr><td class="align_left">Input:</td><td class="align_center">VS</td><td class="align_center">S</td><td class="align_center">MS</td><td class="align_center">ML</td><td class="align_center">L</td><td class="align_center">VL</td></tr><tr><td class="align_left" colspan="7"><hr/></td></tr><tr><td class="align_left">Output:</td><td class="align_center">NB</td><td class="align_center">NM</td><td class="align_center">NS</td><td class="align_center">ZE</td><td class="align_center">PS</td><td class="align_center">PM</td></tr><tr class="table-tr"><td colspan="7"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>One-dimensional rule table for fuzzy tuning algorithm.</div>

Journal of Control Science and Engineering

tab2

Table 2

Table 2: Comparative Analysis of Neural-Network and Fuzzy Auto-Tuning Sliding Mode Controls for Overhead Cranes under Payload and Cable Variations 