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Yuwei Yao,Liqun Wang,Guolai Yang,Fengjie Xu,Lei Li 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.3
The interval perturbation method is an effective and successful tool in the uncertainty analysis; however, it suffers from the deficiency in the required differential information, which limits its application in complex engineering problems. To end this, this paper uses the radial basis neural network to formulate the derivative information, and its fine accuracy is demonstrated by a mathematical example. Moreover, a new interval analysis method combining interval perturbation and radial basis neural network differentiation, abbreviated as RBNNIPM is proposed. Furthermore, RBNNIPM is applied to calculate the boundaries of yield stress in a three-bar truss, and the detailed assessment proves that RBNNIPM has both high efficiency and high precision. Finally, an electromagnetic buffer model is established to certificate the practicability of RBNNIPM in practical engineering.
Electromagnetic Counter-recoil Mechanism Based on Adaptive Sliding Mode Control
Wenbin Yu,Guolai Yang,Liqun Wang,Lei Li,Hongyi Zhang 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.9
Traditional counter-recoil machines always have problems of difficulty in adjusting the movement process flexibly, maintenance difficulties, and so on. To end these, this paper proposes a new electromagnetic counterrecoil scheme using cylindrical linear motors. Firstly, the mathematical expression of counter-recoil movement under the linear motor is formulated, and the ideal movement trajectory is designed using the piecewise polynomial of velocity based on acceleration. To obtain a better performance, of the motor controller, a composed approach of an adaptive sliding mode control based on barrier function (BFASMC) and the finite-time disturbance observer (FTDO) is introduced into the modeling and computation. The stability of the controller is proved by establishing the Lyapunov function. The new adaptive laws based on the barrier function effectively make up for the shortcomings of the exponential function and improves control chattering. At last, the new scheme is simulated. The results show that it has a strong robustness and anti-interference ability.
Adaptive robust target tracking control of marching tank under high-speed maneuvering condition
Cong Li,Guolai Yang,Xiuye Wang,Yuze Ma,Liqun Wang,Quanzhao Sun 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.6
This paper focuses on the problem of target tracking control of marching tanks under the condition of high-speed maneuver based on sliding mode disturbance observer. First, the dynamic model of marching tank is established by using multi-body dynamics software. The nonlinear factors such as barrel flexibility, clearance between barrel and bushing, and uncertainty sources such as road excitation are considered. Second, the mechatronics model of tank bidirectional stabilization system considering transmission clearance and friction is established in numerical simulation software. Aiming at the tank bidirectional stabilization system, an adaptive robust controller based on sliding mode disturbance observer is designed. Finally, the real-time control and target tracking of the tank bidirectional stabilization system are realized by co-simulation. The results show that the sliding mode disturbance observer improves the stability accuracy of the system by 43.22 %. Comparing the simulation results with the PID control, the controller designed in this paper has the characteristics of rapid tracking speed and high robustness, and the advantage is more obvious under the condition of highspeed maneuver.
A Novel Design of Permanent Magnet Linear Synchronous Motor with Reduced End Effect
Wu Qingle,Wang Liqun,Yang Guolai,Tang Enling,Li Lei,Al-Zahrani Ahmed 한국전자파학회 2023 Journal of Electromagnetic Engineering and Science Vol.23 No.2
In response to the end effect of the permanent magnet linear synchronous motor, this paper proposes an improved modular motor structure. To compute its electromagnetic characteristics, a subdomain model that converts the Cartesian coordinate system into a polar coordinate system through coordinate transformation is further formulated, thus significantly reducing programming difficulty. The analytical results are compared with those of the finite element method and indicate that the subdomain model can accurately consider the effects of end and flux barriers. Moreover, the magnetic field distribution inside the motor is applied to explain the end force abatement, and the suggested flux barrier width is obtained. Finally, the modular structure is applied to a 9-slot, 10-pole permanent magnet linear synchronous motor. The simulation results show that the modular structure can effectively suppress the end effect of the linear motor, and the proposed subdomain model applies to the design of the modular motor.
Jiang, Ting,Shen, Zhenzhong,Yang, Meng,Xu, Liqun,Gan, Lei,Cui, Xinbo Techno-Press 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.67 No.2
To improve the prediction accuracy of the strong-unloading rock slope performance and obtain the range of variation in the slope displacement, a new displacement time-series prediction model is proposed, called the fuzzy information granulation (FIG)-genetic algorithm (GA)-back propagation neural network (BPNN) model. Initially, a displacement time series is selected as the training samples of the prediction model on the basis of an analysis of the causes of the change in the slope behavior. Then, FIG is executed to partition the series and obtain the characteristic parameters of every partition. Furthermore, the later characteristic parameters are predicted by inputting the earlier characteristic parameters into the GA-BPNN model, where a GA is used to optimize the initial weights and thresholds of the BPNN; in the process, the numbers of input layer nodes, hidden layer nodes, and output layer nodes are determined by a trial method. Finally, the prediction model is evaluated by comparing the measured and predicted values. The model is applied to predict the displacement time series of a strong-unloading rock slope in a hydropower station. The engineering case shows that the FIG-GA-BPNN model can obtain more accurate predicted results and has high engineering application value.
Artillery structural dynamic responses uncertain optimization based on robust Nash game method
Fengjie Xu,Guolai Yang,Liqun Wang 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.9
To coordinate the contradiction between artillery launching performance indexes under parameter uncertainty, this paper proposes an artillery structural dynamic responses optimization method based on robust Nash game theory. First, a multi-flexible body dynamic model for a 155 mm caliber artillery is established, which coupling the interior ballistic model, recoil force model, and balance mechanism model. Secondly, the live firing experiment is carried out to verify the accuracy of the established multi-flexible model. Then the muzzle vibration and maximum chamber pressure are selected as the players in the game. Because these two indexes can represent the most critical contradictory indexes of artillery, namely the firing accuracy and power. Afterward, to reduce the computational time, the BP neural network surrogate model is constructed to replace the original multi-flexible body dynamic model. Finally, the double-loop approach is adopted to search for the robust Nash equilibrium. The inner loop optimization is used to determine the worst-case scenario caused by the parameter uncertainty. The outer loop optimization is referred to as the robust Nash equilibrium solution process. The results show that the artillery structural dynamics responses have been significantly improved.