A SIMPLE TUNING MODEL-FREE CONTROLLER COMPARED TO PID AND FLC: CASE STUDY

Author(s):  
D. Monjengue
2019 ◽  
Vol 15 (3) ◽  
pp. 1361-1371 ◽  
Author(s):  
Yinliang Xu ◽  
Wei Zhang ◽  
Mo-Yuen Chow ◽  
Hongbin Sun ◽  
Hoay Beng Gooi ◽  
...  

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.


2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
S. Pezeshki ◽  
M. A. Badamchizadeh ◽  
S. Ghaemi ◽  
M. A. Poor

This paper introduces a new approach to design Model-Free Adaptive Controller (MFAC) using adaptive fuzzy procedure as a feedback linearization based on output error. The basic idea is to transfer the control signal to an appropriate surface and then, depending on the output error of system, the control signal changes around this surface. Some examples are provided as well to illustrate the efficiency of the proposed approach. The obtained simulation results have shown good performances of the proposed controller.


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