Optimal preview control design of pneumatic servo system: a comparative analysis

2020 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Randeep Kaur ◽  
Jyoti Ohri
Author(s):  
Ahmed Khalil ◽  
Nicolas Fezans

AbstractGust load alleviation functions are mainly designed for two objectives: first, alleviating the structural loads resulting from turbulence or gust encounter, and hence reducing the structural fatigue and/or weight; and second, enhancing the ride qualities, and hence the passengers’ comfort. Whilst load alleviation functions can improve both aspects, the designer will still need to make design trade-offs between these two objectives and also between various types and locations of the structural loads. The possible emergence of affordable and reliable remote wind sensor techniques (e.g., Doppler LIDAR) in the future leads to considering new types of load alleviation functions as these sensors would permit anticipating the near future gusts and other types of turbulence. In this paper, we propose a preview control design methodology for the design of a load alleviation function with such anticipation capabilities, based on recent advancements on discrete-time reduced-order multi-channel $$H_\infty $$ H ∞ techniques. The methodology is illustrated on the DLR Discus-2c flexible sailplane model.


2013 ◽  
Vol 753-755 ◽  
pp. 2674-2678
Author(s):  
Kun Yang ◽  
Cai Jun Liu ◽  
Shu Min Liu

Based on the situation that the hydraulic position servo system is easily influenced by the external interference and the parameters of which are different with time-varying, the fuzzy control can soften the buffeting and the sliding algorithm has no the same problems as the hydraulic position servo system, a brandly-new fuzzy sliding control algorithm is designed. In the simulation process, within the parameters of simulated time-varying and outside strong interference, the results show that the hydraulic servo system based on fuzzy sliding mode control algorithm has a greater resistance to internal and external interference and time-varying parameters.


1996 ◽  
Vol 27 (1) ◽  
pp. 159-164 ◽  
Author(s):  
Witrisnanto. S. N. ◽  
T. Futami ◽  
T. Arai ◽  
M. Kimura

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