Hongda Wu

Mr. Hongda Wu


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 February 2023 in Machines
Verified
Journal Article
Open access
PDF file
HWHongda Wu
Hongda Wu
FZFuxing Zhang
Fuxing Zhang
TGTeng Gao
Teng Gao
An improved chimpanzee optimization algorithm incorporating multiple strategies (IMSChoA) is proposed to address the problems of initialized population boundary aggregation distribution, slow convergence speed, low precision, and proneness to fall into local optimality of the chimpanzee search algorithm. Firstly, the improved sine chaotic mapping is used to initialize the population to solve the population boundary aggregation distribution problem. Secondly, a linear weighting factor and an adaptive acceleration factor are added to join the particle swarm idea and cooperate with the improved nonlinear convergence factor to balance the global search ability of the algorithm, accelerate the convergence of the algorithm, and improve the convergence accuracy. Finally, the sparrow elite mutation and Bernoulli chaos mapping strategy improved by adaptive change water wave factor are added to improve the ability of individuals to jump out of the local optimum. Through the comparative analysis of benchmark functions seeking optimization and the comparison of Wilcoxon rank sum statistical test seeking results, it can be seen that the IMSChoA optimization algorithm has stronger robustness and applicability. Further, the IMSChoA optimization algorithm is applied to two engineering examples to verify the superiority of the IMSChoA optimization algorithm in dealing with mechanical structure optimization design problems.

6 July 2023 in Actuators
Verified
Journal Article
Open access
PDF file
HWHongda Wu
Hongda Wu
XZXianyi ZHAI
Xianyi ZHAI
TGTeng Gao
Teng Gao
NWNan Wang
Nan Wang
ZZZongsheng Zhao
Zongsheng Zhao
GPguibing Pang
guibing Pang
As an international standard pressure-measuring instrument, the absolute pressure piston manometer’s working medium is gas, so the actual working process will be affected by many internal uncertainties and external disturbances, leading to its long stability time and poor performance. In this paper, a fuzzy linear active disturbance rejection control strategy (FLADRC) for absolute pressure piston manometers is proposed to address these problems. First, the characteristics of the main components are analyzed according to the actual working principle of the system to establish a theoretical model of the controlled system. Second, the corresponding linear active disturbance rejection controller (LADRC) is designed according to the model. The principle of fuzzy control is introduced to adaptively adjust the controller parameters of the LADRC in real time, which improves the disadvantages of the LADRC parameters, which are difficult to rectify and have poor immunity to disturbances due to fixed parameters, and the stability of the control method is subsequently demonstrated. Finally, a simulation model is built in the Simulink environment in MATLAB, and three different pressure operating points are selected for the corresponding experiments to make a comparative analysis with Kp, PID, and LADRC. The results show that FLADRC enables the absolute pressure piston manometer to achieve better stability and greater immunity to disturbances. This also verifies the effectiveness and feasibility of the control strategy in practical engineering applications.