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Kewen Li,Yong-Ming Li 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.1
This paper studies the problem of finite-time fuzzy adaptive dynamic surface control (DSC) design fora class of single-input and single-output (SISO) high-order nonlinear systems with output constraint. Fuzzy logicsystems (FLSs) are utilized to identify the unknown smooth functions. By adopting Barrier Lyapunov function(BLF), the problem of output constrain is handled. Combining adding a power integrator and adaptive backsteppingrecursion design technique, a novel fuzzy adaptive finite-time DSC algorithm is proposed. Based on finite-timeLyapunov stable theory, the developed control algorithm means that all the signals of the closed-loop system aresemi-global practical finite-time stable (SGPFS) and the tracking error converges to a small neighborhood of originin finite time. In addition, the output does not violate the given constrain bound. Finally, both numerical and practicalsimulation examples are given to illustrate the effectiveness of the proposed control algorithm.
Mediatory role of K, Cu and Mo over Ru/SiO2 catalysts for glycerol hydrogenolysis
Xiaoyuan Liao,Kewen Li,Xiaomin Xiang,Sheng-Guang Wang,Xichun She,Yulei Zhu,Yongwang Li 한국공업화학회 2012 Journal of Industrial and Engineering Chemistry Vol.18 No.2
SiO2 supported ruthenium catalysts with and without modifiers were prepared, characterized and tested for glycerol hydrogenation. Addition of K, Cu and Mo affects the reducibility and acidity of the Ru/SiO2catalyst. Characterization data shows that Cu and Mo-modified Ru/SiO2 have stronger acidity. On the contrary, K element on a passive effect on the acidity of Ru based catalyst had been observed. A comparison with the pure Ru/SiO2 indicates the Cu-promoted specimen has better selective to the desired products, acetol, 1,2-propanediol and ethyl glycol, although the reactivity is slightly lower.
Neuro-adaptive Event-triggered Optimal Control for Power Battery Systems With State Constraints
Xiaoxuan Pei,Kewen Li,Yongming Li 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.2
This paper investigates an adaptive neural networks (NNs) event-triggered optimal control method for the second-order resistance capacitance (RC) equivalent circuit system with state constraints. The NNs are used to estimate the unknown nonlinear functions. In order to constrain the states within the designed boundary in optimal control strategy, the barrier Lyapunov function (BLF) method is taken into account. Furthermore, to economic the transmission resources, the adaptive NNs event-triggered optimizing control strategy is developed by employing the relative threshold strategy. The proposed optimal control strategy is not only able to satisfy the stability of closedloop system, but also can guarantee the performance index functions minimized when all states remain within the given boundaries. Finally, the effectiveness of the suggested control method is demonstrated by simulation.