By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm and a partially coupled generalised extended stochastic gradient algorithm to estimate the parameters of a multivariable output‐error‐like system with autoregressive moving average noise from input–output data. The key is to divide the identification model into several submodels based on the hierarchical identification principle and to establish the parameter estimation algorithm by using the coupled relationship between these submodels. The simulation test results indicate that the proposed algorithms are effective.

In this article, a sliding mode dual-channel disturbance rejection control based on an extended state observer is proposed for the attitude control of a quadrotor under unknown disturbances. There exist an inner disturbance rejection channel (IDRC) and an outer disturbance rejection channel (ODRC) in this control scheme. In the IDRC, a low-frequency disturbance compensator is proposed to obtain the disturbance compensation value and to compensate the low-frequency component of the lumped disturbance. In the ODRC, a novel sliding mode controller with a variable-gain switching term and a constant-gain switching term is designed, and the switching terms are used to compensate the virtual disturbance estimation error and the high-frequency component of the lumped disturbance. The low-frequency and high-frequency components of the lumped disturbance can be estimated and the influence of the virtual disturbance estimation error is reduced by using the proposed control scheme. The stability of the system is proved by using the Lyapunov theory. Finally, the effectiveness of the proposed scheme is tested by numerical simulations and platform experiments.