Adaptive Parameter Identification of Maritime Autonomous Surface Ships with Exponential Convergence

Author(s):  
Jiawang Yue ◽  
Zhouhua Peng ◽  
Dan Wang
Algorithms ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 167 ◽  
Author(s):  
Jun Zhao ◽  
Xian Wang ◽  
Guanbin Gao ◽  
Jing Na ◽  
Hongping Liu ◽  
...  

The stability and robustness of quadrotors are always influenced by unknown or immeasurable system parameters. This paper proposes a novel adaptive parameter estimation technology to obtain high-accuracy parameter estimation for quadrotors. A typical mathematical model of quadrotors is first obtained, which can be used for parameter estimation. Then, an expression of the parameter estimation error is derived by introducing a set of auxiliary filtered variables. Moreover, an augmented matrix is constructed based on the obtained auxiliary filtered variables, which is then used to design new adaptive laws to achieve exponential convergence under the standard persistent excitation (PE) condition. Finally, a simulation and an experimental verification for a typical quadrotor system are shown to illustrate the effectiveness of the proposed method.


2017 ◽  
Vol 53 (3) ◽  
pp. 2862-2870 ◽  
Author(s):  
Jason Poon ◽  
Palak Jain ◽  
Costas Spanos ◽  
Sanjib Kumar Panda ◽  
Seth R. Sanders

2019 ◽  
Vol 42 (6) ◽  
pp. 1191-1203
Author(s):  
Zhong-qiang Wu ◽  
Zong-kui Xie ◽  
Chong-yang Liu

In this paper, a parameter identification method of photovoltaic cell model based on improved lion swarm optimization is presented. Lion swarm optimization is a novel intelligent algorithm proposed in recent years, but it has problems such as local optimum and slow convergence. To overcome such limitations, we can combine the tent chaotic map, adaptive parameter and chaotic search strategy to further improve the search ability of the algorithm and avoid trapping in local optimum. The simulation of standard test function shows that the performance of improved lion swarm algorithm is superior to the other six algorithms. Then the algorithm is applied to the parameter identification of photovoltaic cells under two kinds of models and different irradiance, the simulation results verify the superiority and effectiveness of the improved lion swarm optimization in the application of photovoltaic cell parameter identification.


2013 ◽  
Vol 46 (20) ◽  
pp. 624-629
Author(s):  
Jing Na ◽  
Juan Yang ◽  
Xing Wu ◽  
Yu Guo

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