Attitude control of an unmanned patrol helicopter based on an optimised spiking neural membrane system for use in coal mines

Abstract

For the attitude control of unmanned helicopters used in the intelligent patrolling of coal mines, a spiking neural membrane system is introduced for attitude optimisation control. First, a geometry-based attitude dynamics model suitable for coal mine scenarios is constructed. Second, in accordance with the attitude dynamics model, an extended spiking neural membrane system (ESNMS) is constructed, and an optimised spiking neural membrane system (OSNMS) and accompanying algorithm are designed to optimise the ESNMS. Then, the attitude control performance of the developed system is theoretically analysed. Finally, through the simulation of a semiphysical experimental platform, trajectory tracking is effectively realised. Under normal and wind disturbance conditions, comparisons with the traditional synovium controller (TSC) and linear feedback controller (LFC) show that the performance of the designed OSNMS is greatly improved, and the experimental results show that the OSNMS has good stability and effectiveness.