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Huafeng Xia,Yongqing Yang,Feng Ding 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.2
This paper studies the identification problem of multivariable controlled autoregressive moving average systems. For the case with a parameter matrix and an unmeasurable vector in the system identification model, we transform the model into several submodels based on the number of the outputs. A maximum likelihood-based recursive least-squares algorithm is derived to identify the parameters of each submodel. A multivariable recursive extended least-squares algorithm is provided as a comparison. The effectiveness of the proposed identification algorithm is verified by simulation examples.
Menghu Hua,Huafeng Ding,Xiang-Yu Yao,Xinxin Zhang 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2
In this paper, the distributed fixed-time formation-containment (DFTFC) problem of multiple EulerLagrange systems with parametric uncertainties and input disturbances is studied under directed graphs. First, a distributed fixed-time sliding-mode estimator is constructed to estimate the desired states of each robot with that only parts of followers can access the information of leaders. Next, based on the estimator, a distributed fixed-time formation control algorithm is developed to drive leaders to achieve a specified formation. Then, the distributed fixed-time containment control algorithm is proposed for followers with its estimated states being tracked in a fixed time. Note that an explicit upper bound of the convergence time of DFTFC control algorithm is obtained independent of initial conditions. Finally, numerical simulations are performed to show the effectiveness of the obtained theoretical results.