Adaptive Control of Neuro Fuzzy PID for Fixed Wing UAV Flight Stability
Abstract
Unmanned Aerial Vehicle (UAV), especially fixed wing, are widely used to carry out various missions, namely civil and military missions. To support the implementation of this mission, it is necessary to develop an intelligent automatic control system (autopilot). In this paper, an autopilot system with adaptive neuro fuzzy PID control is developed to control lateral (pitch) and longitudinal (roll) motion, by taking advantage of PID, fuzzy, and neural network control. Therefore, robust controls which can handle non-linear conditions can be formed. This paper aims to determine the performance of adaptive control of neuro fuzzy PID controllers for longitudinal and lateral motion on UAV. The result shows that adaptive control of neuro fuzzy PID are able to control the lateral and longitudinal motion of the aircraft and able to compensate for interferences from environmental disturbances in flying condition, such as changes in direction and wind speed that causes changes in aircraft attitude. The control characteristics of neuro fuzzy PID adaptive control in lateral and longitudinal motion are relatively similar. Adaptive control of neuro fuzzy PID has better performance than fuzzy PID control, i.e., faster settling time and lower percentage of maximum overshoot.
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