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- 저자 : Yongzhi Liu (검색결과 5 건)
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Yongzhi Wang,Mengbo Liu,Shaoming Liao,Qiong Yi,Junzuo He,Linqi Liu,Zhiqun Gong,Kaiying Li 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.5
Press-in open caisson method, which sinks into soil with the aid of mechanical pressure without excavation, is becoming an important method of construction in extremely soft foundations. However, many engineering problems are prone to occur in the construction of caissons, such as sinking and large deformation. In this study, the stratigraphic response model, such as soil migration during the press-in process of open caisson, is focused on. Through model tests of soil and caissons, the migration patterns of each part of the soil were carried out, and the mechanism underlying the stratigraphic response pattern was investigated. The three primary conclusions are as follows: 1) The bottom edge foot of caisson produces lateral extrusion on surrounding soil in the range of 10 cm (20%H) below, resulting in lateral movement of soil. 2) two kinds of plug, i.e., “wedged” and “unwedged” plugs exist, and the driven forces for the soil migration can be divided into three stages, i.e., caused by soil plug with active arch, by soil plug with passive arch and caused by soil squeezing effect. 3) there is a significant linear correlation between the soil plug changes, the horizontal movement of the deep soil body, and the displacement of the surface uplift. The soil plugging effect and squeezing effect are interacted and enhanced with each other. This study provides a new understanding of the stratigraphic response in the construction of press-in open caissons, andguides safety control of open caissons construction.
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Nonsingular Finite-time Second Order Sliding Mode Attitude Control for Reentry Vehicle
Yongzhi Sheng,Jie Geng,Xiangdong Liu,Liang Wang 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.4
This paper presents nonlinear robust flight control strategies for the reentry vehicle which is nonlinear, coupling, and includes parameter uncertainties and external disturbances. Firstly, a finitetime second order sliding mode attitude control strategy is pointed out with the introduction of a nonsingular finite-time sliding mode manifold. By the proposed controller, the attitude tracking errors are mathematically proved to converge to zero within finite time and the chattering of sliding mode controller is alleviated without any deterioration of robustness and accuracy. For further alleviation of chattering, a smooth second order sliding mode attitude control strategy is then designed based on an improved nonsingular finite-time sliding mode manifold. Finally, the proposed strategies are applied to the attitude control of X-33 RLV in the reentry phase to verify the validity and robustness of the proposed strategies.
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A Novel Adaptive High-order Sliding Mode Control based on Integral Sliding Mode
Liang Wang,Yongzhi Sheng,Xiangdong Liu 제어·로봇·시스템학회 2014 International Journal of Control, Automation, and Vol.12 No.3
This paper presents an adaptive high-order sliding mode control scheme targeting for uncertain minimum phase nonlinear single-input-single-output (SISO) systems, which can be equivalently formulated as the finite-time stabilization of high-order input-output dynamics subject to the uncertainties of parameters such as a chain of integrators. The proposed controller is derived from the concept of integral sliding mode and consists of two parts, one part of which achieves the finite-time stabilization of the high-order input-output dynamics without uncertainties by solving a finite-horizon optimal control problem with a free-final-state. The other part adopts the adaptive sliding mode control technique considering the practical bounded uncertainties, by which a modified switching gain adaptation algorithm is developed so that the on-line switching gain selection can be executed and the upper bounds of the uncertainties are not requisite in advance. As a result, a high-order sliding mode is established, ensuring the sliding variables and its high-order derivatives converge to an arbitrarily small vicinity of the origin in finite time. Therefore, the proposed controller achieves fixed convergence time and further improves strong robustness against bounded uncertainties with lower chattering and the easy implementation. Simulation results are presented in detail to verify the effectiveness and feasibility of the proposed algorithm.
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Neural Network Based Adaptive Fuzzy PID-type Sliding Mode Attitude Control for a Reentry Vehicle
Zhen Jin,Jiabin Chen,Yongzhi Sheng,Xiangdong Liu 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.1
This work investigates the attitude control of reentry vehicle under modeling inaccuracies and externaldisturbances. A robust adaptive fuzzy PID-type sliding mode control (AFPID-SMC) is designed with the utilizationof radial basis function (RBF) neural network. In order to improve the transient performance and ensure smallsteady state tracking error, the gain parameters of PID-type sliding mode manifold are adjusted online by usingadaptive fuzzy logic system (FLS). Additionally, the designed new adaptive law can ensure that the closed-loopsystem is asymptotically stable. Meanwhile, the problem of the actuator saturation, caused by integral term ofsliding mode manifold, is avoided even under large initial tracking error. Furthermore, to eliminate the need of apriori knowledge of the disturbance upper bound, RBF neural network observer is used to estimate the disturbanceinformation. The stability of the closed-loop system is proved via Lyapunov direct approach. Finally, the numericalsimulations verify that the proposed controller is better than conventional PID-type SMC in terms of improving thetransient performance and robustness.
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