Event-triggered discrete extended state observer–based model-free controller for quadrotor position and attitude trajectory tracking

Author(s):  
Dingxin He ◽  
Haoping Wang ◽  
Yang Tian ◽  
Konstantin Zimenko

In this article, an event-triggered discrete extended state observer–based model-free controller is developed for the position and attitude trajectory tracking of a quadrotor with uncertainties and external disturbances. The referred event-triggered discrete extended state observer–based model-free controller is composed of two event-triggered mechanisms, ultra-local model-based discrete extended state observer and proportional-derivative sub-controller. To reduce system output signal transmission, the event-triggered mechanism of output signal which owns dynamic and static threshold is designed. Based on event-triggered output signals, the discrete extended state observer is constructed to obtain the estimations of state values which are utilized as controller’s variables and to compensate for the lumped disturbances. The proportional-derivative sub-controller is adopted to guarantee the convergence of trajectory tracking error. To decrease control input signal transmission, the event-triggered mechanism of input signal that processes static threshold is constructed. Moreover, the stability analysis of overall quadrotor system with the proposed control strategy is investigated using Lyapunov theorem and the Zeno behavior is avoided. Finally, corresponding control scheme for quadrotor system is structured and the numerical comparative simulation and co-simulation experiment are given to demonstrate the effectiveness and performance of the proposed approach.

2021 ◽  
Author(s):  
Xianming Wang ◽  
Mouquan Shen ◽  
Ju H. Park

Abstract This paper is dedicated to extended state observer-based event-triggered model free iterative learning control (ET-MFILC) for nonlinear systems with disturbances. A modified MFILC scheme is proposed by using the estimated uncertainties for the disturbed system. With the help of the estimated errors, an iterative extended state observer (IESO) is constructed to estimate the unknown uncertainties. New triggering mechanism integrated true tracking errors, the estimated errors and the estimated uncertainties is designed for multiple inputs and multiple outputs (MIMO) systems. Sufficient conditions are proposed to make the resultant ET-MFILC tracking error systems be uniformly ultimately bounded. An illustrative example is presented to demonstrate the effectiveness of the proposed scheme.


2020 ◽  
Vol 386 ◽  
pp. 191-197 ◽  
Author(s):  
Xiang Wu ◽  
Kexin Liu ◽  
Yuqi Bai ◽  
Jinzhi Wang

Author(s):  
Wenming Nie ◽  
Huifeng Li ◽  
Ran Zhang ◽  
Bo Liu

The ascent trajectory tracking problem of a launch vehicle is investigated in this paper. To improve the conventional trajectory linearization method which usually omits the linearization errors, the extended state observer (ESO) is employed in this paper to timely estimate the total disturbance which consists of the external disturbances and the modeling uncertainties resulting from linearization error. It is proven that the proposed trajectory tracking controller can guarantee the desired performance despite both external disturbances and the modeling uncertainties. Moreover, compared with the conventional linearization control method, the proposed controller is shown to have much better performance of uncertainty rejection. Finally, the feasibility and performance of this controller are illuminated via simulation studies.


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