scholarly journals Disturbance rejection control of yaw channel of a small-scale unmanned helicopter via Takagi–Sugeno disturbance modeling approach

2016 ◽  
Vol 13 (5) ◽  
pp. 172988141667111
Author(s):  
Xiangxiang Fan ◽  
Yang Yi ◽  
Tianping Zhang
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Rui Ma ◽  
Li Ding ◽  
Hongtao Wu

This article presents design and optimization results from an implementation of a novel disturbance decoupling control strategy for a small-scale unmanned helicopter. Such a strategy is based on the active disturbance rejection control (ADRC) method. It offers an appealing alternative to existing control approaches for helicopters by combining decoupling and disturbance rejection without a detailed plant dynamics. The tuning of the control system is formulated as a function optimization problem to capture various design considerations. In comparison with several different iterative search algorithms, an artificial bee colony (ABC) algorithm is selected to obtain the optimal control parameters. For a fair comparison of control performance, a well-designed LQG controller is also optimized by the proposed method. Comparison results from an attitude tracking simulation against wind disturbance show the significant advantages of the proposed optimization control for this control application.


Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1548 ◽  
Author(s):  
Raul-Cristian Roman ◽  
Radu-Emil Precup ◽  
Emil M. Petriu ◽  
Florin Dragan

In this paper a second-order data-driven Active Disturbance Rejection Control (ADRC) is merged with a proportional-derivative Takagi-Sugeno Fuzzy (PDTSF) logic controller, resulting in two new control structures referred to as second-order data-driven Active Disturbance Rejection Control combined with Proportional-Derivative Takagi-Sugeno Fuzzy Control (ADRC–PDTSFC). The data-driven ADRC–PDTSFC structure was compared with a data-driven ADRC structure and the control system structures were validated by real-time experiments on a nonlinear Multi Input-Multi Output tower crane system (TCS) laboratory equipment, where the cart position and the arm angular position of TCS were controlled using two Single Input-Single Output control system structures running in parallel. The parameters of the data-driven algorithms were tuned in a model-based way using a metaheuristic algorithm in order to improve the efficiency of energy consumption.


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