Multi‐objective optimal motion control of a laboratory helicopter based on parallel simple cell mapping method

2019 ◽  
Vol 22 (4) ◽  
pp. 1565-1578 ◽  
Author(s):  
Zhi‐Chang Qin ◽  
Ying Xin ◽  
Jian‐Qiao Sun
2016 ◽  
Vol 23 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Zhi-Chang Qin ◽  
Fu-Rui Xiong ◽  
Qian Ding ◽  
Carlos Hernández ◽  
Jesús Fernandez ◽  
...  

This paper presents a study of the multi-objective optimal design of a sliding mode control for an under-actuated nonlinear system with the parallel simple cell mapping method. The multi-objective optimal design of the sliding mode control involves six design parameters and five objective functions. The parallel simple cell mapping method finds the Pareto set and Pareto front efficiently. The parallel computing is done on a graphics processing unit. Numerical simulations and experiments are done on a rotary flexible arm system. The results show that the proposed multi-objective designs are quite effective.


2013 ◽  
Vol 1 (3) ◽  
pp. 231-238 ◽  
Author(s):  
Carlos Hernández ◽  
Yousef Naranjani ◽  
Yousef Sardahi ◽  
Wei Liang ◽  
Oliver Schütze ◽  
...  

Author(s):  
Zhi-Chang Qin ◽  
Fu-Rui Xiong ◽  
Qian Ding ◽  
Carlos Hernández ◽  
Jesús Fernandez ◽  
...  

This paper presents a study of multi-objective optimal design of a slide mode control for an under-actuated nonlinear system with the parallel simple cell mapping method. The multi-objective optimal design of the slide mode control involves 6 design parameters and 5 objective functions. The parallel simple cell mapping method finds the Pareto set and Pareto front efficiently. The parallel computing is done on a graphic processing unit (GPU). Numerical simulations and experiments are done on a rotary flexible arm system. The results show that the proposed multi-objective designs are quite effective.


2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yu Wang ◽  
Heng Cao ◽  
JinLin Jiang

An indicator of a passive biped walker’s global stability is its domain of attraction, which is usually estimated by the simple cell mapping method. It needs to calculate a large number of cells’ Poincare mapping result in the estimating process. However, the Poincare mapping is usually computationally expensive and time-consuming due to the complex dynamical equation of the passive biped walker. How to estimate the domain of attraction efficiently and reliably is a problem to be solved. Based on the simple cell mapping method, an improved method is proposed to solve it. The proposed method uses the multiple iteration algorithm to calculate a stable domain of attraction and effectively decreases the total number of Poincare mappings. Through the simulation of the simplest passive biped walker, the improved method can obtain the same domain of attraction as that calculated using the simple cell mapping method and reduce calculation time significantly. Furthermore, this improved method not only proposes a way of rapid estimating the domain of attraction, but also provides a feasible tool for selecting the domain of interest and its discretization level.


2016 ◽  
Vol 48 (11) ◽  
pp. 1845-1868 ◽  
Author(s):  
Jesús Fernández ◽  
Oliver Schütze ◽  
Carlos Hernández ◽  
Jian-Qiao Sun ◽  
Fu-Rui Xiong

2017 ◽  
Vol 23 (5) ◽  
pp. 488-492
Author(s):  
Jianqiao Sun ◽  
Wen Zheng ◽  
Furui Xiong ◽  
Zhichang Qin ◽  
Qian Ding

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