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Zhenghong Xu,Xiaohui Yang,Wenjie Zhang,Wei Zhang,Shuang Yang,Siyi Zhou,Peter Xiaoping Liu 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.9
This paper proposes a novel robust finite-time tracking control scheme for robotic manipulators with uncertainties and external disturbances. In order to reduce the chattering phenomenon and enhance the robustness of the system, we design a novel extended state observer with filter function for estimating the lumped term of system uncertainties and external disturbances. We adopt the backstepping mechanism to design an adaptive backstepping nonsingular fast terminal sliding mode controller, achieve finite time convergence of the tracking errors while avoiding the singularity problem. An adaptive update law is designed for the switching gain, which further weakens the chattering problem. The finite-time convergence of tracking errors and the stability of the closed-loop system are ensured by the Lyapunov criterion. In comparison with other control methods, numerical simulation on a two-link rigid robot manipulator demonstrates the effectiveness and superiority of the proposed method.
Zhenghong Xu,Xiaohui Yang,Wenjie Zhang,Wei Zhang,Liufang Zhang,Peter Xiaoping Liu 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.6
In this paper, we propose a backstepping integral nonsingular fast terminal sliding mode control approach based on an extended state observer to the trajectory tracking control of robotic manipulators with LuGre friction. In order to improve convergence speed and tracking precision, an integral fast terminal sliding surface is introduced. An appropriate saturation function is designed in the control input to avoid singularity. An extended state observer is employed to estimate the uncertainties and disturbances, and they are compensated by the control laws, for which the chattering can be effectively eliminated. The backstepping method is used to design the control input of the system to ensure the globally asymptotic stability based on the Lyapunov criterion. In comparison with other control methods, simulation results show effectiveness and superiority of this proposed control scheme.
An Adaptive Fault-tolerant Control Method for Robot Manipulators
Wenjie Zhang,Xiaohui Yang,Zhenghong Xu,Wei Zhang,Li Yang,Xiaoping Liu 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.12
This paper presents a new method for adaptive continuous nonsingular fast terminal sliding mode control (ACNFTSMC) based on a novel structure-improved extended state observer (SIESO) for fault-tolerant control (FTC). In response to the initial peaking phenomenon in traditional ESO (TESO), which can severely degrade the accuracy and stability of the control system, The SIESO is designed to replace TESO to estimate the lump disturbances/faults. Besides, to address the problem of the unknown estimation error of ESO, an adaptive technique is applied to compensate for the observation error in real-time. To guarantee fast convergence and chattering-free, the CNFTSMC method is employed. Afterward, the stability and rapid convergence of the control system is demonstrated using Lyapunov theory. Finally, the simulation results verify the superiority of the proposed control strategy compared to the other existing advanced control techniques.
Expression, Purification, and Bioactivity of (GLP-1A2G)2-HSA Analogs in Pichia pastoris GS115
Wenfang Dou,Junshang Feng,Xiaomei Zhang,Hongyu Xu,Jinsong Shi,Zhenghong Xu 한국생물공학회 2013 Biotechnology and Bioprocess Engineering Vol.18 No.6
We developed (GLP-1A2G)2-HSA (GGH) analogsthat are resistant to degradation and also show high serumglucose-reducing activity in vivo. Five analogs with Nterminalextensions were designed based on the proteinGGH. Next, we constructed recombinant plasmids capableof expressing the five analogs in methylotrophic yeastPichia pastoris GS115. Expression reached 150 mg/L in asmall-scale incubation. Fusion proteins were successfullypurified from the supernatant using ultrafiltration concentration,affinity absorption chromatography, hydrophobicchromatography, ion exchange chromatography and gelfiltration. A single band was observed on SDS-PAGE andthe purity was 97%. Activity test results suggested thatboth A-GGH and G-GGH showed better activity in vitroand that their cAMP levels were significantly increased by10-fold compared to GGH without N-terminal extension. Additionally, A-GGH efficiently enhanced the glucoseloweringeffect, which was maintained after the administrationfor 24 h. A-GGH is a potential drug for treating type 2diabetes.
Hui Li,Zhenzhen Fu,Heng Li,Wenfang Dou,Jinsong Shi,Zhenghong Xu 한국생물공학회 2013 Biotechnology and Bioprocess Engineering Vol.18 No.3
This study investigated the effects of hydroxylase cyptochrome P450 inducers on the efficiency of the biotransformation of dehydroepiandrosterone (DHEA) to 3β, 7α, 15α-trihydroxy-5-androsten-17-one (7α,15α-diOHDHEA)by Colletotrichum lini ST-1. Special attention was given to the substrate DHEA being the best inducer and the fact that it could improve the yield of 7α, 15α-diOHDHEA. Based on the effects of the DHEA pre-induction phases and additional concentrations on 7α, 15α-diOHDHEA production, a substrate pre-induction process was established as follows: 2 g/L DHEA was added for the first time after 12 h of inoculation, followed by the second addition of 6 g/L DHEA after 12 h later. The results showed that this substrate pre-induction process improved the content of cytochrome P450 and that the 7α, 15α-diOH-DHEA yield reached 90.1%, which was 26.9%higher than that obtained in the original process.
Combining a HMM with a Genetic Algorithm for the Fault Diagnosis of Photovoltaic Inverters
Zheng, Hong,Wang, Ruoyin,Xu, Wencheng,Wang, Yifan,Zhu, Wen The Korean Institute of Power Electronics 2017 JOURNAL OF POWER ELECTRONICS Vol.17 No.4
The traditional fault diagnosis method for photovoltaic (PV) inverters has a difficult time meeting the requirements of the current complex systems. Its main weakness lies in the study of nonlinear systems. In addition, its diagnosis time is long and its accuracy is low. To solve these problems, a hidden Markov model (HMM) is used that has unique advantages in terms of its training model and its recognition for diagnosing faults. However, the initial value of the HMM has a great influence on the model, and it is possible to achieve a local minimum in the training process. Therefore, a genetic algorithm is used to optimize the initial value and to achieve global optimization. In this paper, the HMM is combined with a genetic algorithm (GHMM) for PV inverter fault diagnosis. First Matlab is used to implement the genetic algorithm and to determine the optimal HMM initial value. Then a Baum-Welch algorithm is used for iterative training. Finally, a Viterbi algorithm is used for fault identification. Experimental results show that the correct PV inverter fault recognition rate by the HMM is about 10% higher than that of traditional methods. Using the GHMM, the correct recognition rate is further increased by approximately 13%, and the diagnosis time is greatly reduced. Therefore, the GHMM is faster and more accurate in diagnosing PV inverter faults.