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The increasing demand for target tracking, environmental surveys,surveillance and mapping requires multi-axis gimbal systems with high trackingand stabilization performance. In this paper, first, computed torque model isgenerated to estimate the complex disturbances acting on the system. Then, twodifferent control strategies based on active disturbance rejection control(ADRC) and computed torque model are implemented on a two-axis gimbal system.The purpose is to improve the robustness, environmental adaptability andtracking accuracy of the system and reduce the tuning effort of ADRC byintegrating a neural network (NN) based disturbance compensator (NN assistedADRC). In the second control strategy, NN is replaced with a computed torquemodel (CTM assisted ADRC), whose inputs come from plant outputs. The simulationresults show that, NN and CTM assisted ADRC structures can decrease meantracking errors up to 85.4% and 40.8%, respectively.

NN Based Active Disturbance Rejection Controller for a Multi-Axis Gimbal System