A Novel Design of a Neural Network-Based Fractional PID Controller for Mobile Robots Using Hybridized Fruit Fly and Particle Swarm Optimization

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left" rowspan="2">Controller type</td><td class="align_center" colspan="3">MSE</td></tr><tr class="thead"><td class="align_center">Case 1</td><td class="align_center">Case 2</td><td class="align_center">Case 3</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">NNPID</td><td class="align_center">0.00079</td><td class="align_center">0.0012</td><td class="align_center">0.00028</td></tr><tr><td class="align_left">NNFOPID</td><td class="align_center">0.000059</td><td class="align_center">0.00073</td><td class="align_center">0.00009</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The MSE for NNPID and NNFOPID controllers with MAPSO-EFFO.</div>

Complexity

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Table 2

Table 2: A Novel Design of a Neural Network-Based Fractional PID Controller for Mobile Robots Using Hybridized Fruit Fly and Particle Swarm Optimization 

Table 2 | A Novel Design of a Neural Network-Based Fractional PID Controller for Mobile Robots Using Hybridized Fruit Fly and Particle Swarm Optimization 