期刊
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
卷 27, 期 6, 页码 2749-2756出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2018.2858203
关键词
Adaptation models; Actuators; Robustness; Trajectory; Artificial neural networks; Adaptive systems; Robots; Boundedness; model reference adaptive control (MRAC); neural networks (NNs); quadcopter; quaternion; tracking; unmanned aerial vehicle (UAV)
资金
- HKU [CRCG 104005021]
The new trajectory regulating model reference adaptive controller (TRMRAC) has been proposed in this brief. The intermediate reference model in the TRMRAC is self-regulated to enhance the stability and robustness of adaptation, with the trajectories of the controlled system proven to be ultimately uniformly bounded. The developed controller is implemented and simulated in a multivariable robotic arm system with its system dynamics approximated by a neural network, showing superior stability characteristics even under unmodeled actuator dynamics and input saturation. To demonstrate its practicality, a nested version of the controller was tested on a quadcopter for quaternion attitude tracking, showing enhanced robustness over the conventional model reference adaptive control strategy.
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