Liu, G., Chen, L., Zhao, W., Jiang, Y. and Qu, L. (2013) Internal Model Control of Permanent Magnet Synchronous Motor Using Support Vector Machine Generalized Inverse. IEEE Transactions on Industrial Informatics, 9, 890-898.
https://doi.org/10.1109/TII.2012.2222652

has been cited by the following article:

• TITLE: A Data-Driven Adaptive Method for Attitude Control of Fixed-Wing Unmanned Aerial Vehicles

  AUTHORS: Meili Chen, Yuan Wang

  KEYWORDS: Data-Driven, Adaptive Method, Attitude Control, Unmanned Aerial Vehicles (UAV), Internal Model Control

  JOURNAL NAME: Advances in Aerospace Science and Technology, Vol.4 No.1, March 1, 2019

  ABSTRACT: In this paper, a real-time online data-driven adaptive method is developed to deal with uncertainties such as high nonlinearity, strong coupling, parameter perturbation and external disturbances in attitude control of fixed-wing unmanned aerial vehicles (UAVs). Firstly, a model-free adaptive control (MFAC) method requiring only input/output (I/O) data and no model information is adopted for control scheme design of angular velocity subsystem which contains all model information and up-mentioned uncertainties. Secondly, the internal model control (IMC) method featured with less tuning parameters and convenient tuning process is adopted for control scheme design of the certain Euler angle subsystem. Simulation results show that, the method developed is obviously superior to the cascade PID (CPID) method and the nonlinear dynamic inversion (NDI) method.