Leveling control of an inertial platform based on single neuron self tuning PID

DOI:	10.11809/bqzbgcxb2023.01.027
Keywords:	inertial platform; leveling loop; single neuron; self tuning PID control algorithm
Abstract:	The leveling loop of an inertial platform is mostly controlled by PID, but this algorithm has the problem of a low anti interference performance. A single neuron self tuning PID control algorithm is designed based on the advantages of neural network which has self study, self organization, associative memory and concurrent processing. The control algorithm is not only simple in structure, but also has strong acclimatization and robustness. An improved Hebb learning algorithm is applied to the design of controlling the leveling loop of the inertial platform. Finally, as the simulation results indicate, the single neuron self tuning PID control algorithm is better than the traditional PID control algorithm in many indicators, especially in dynamic ones like overshoot, capacity of anti interference and transition time. Thus, it is an ideal control algorithm and can be applied to all kinds of inertial platform systems.
Issue:	Vol. 44 No. 1 (2023)
Published:	2023-01-28
PDF HTML