Author(s)

Zhongqiao Zheng ¹

Affiliation(s)

¹ School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou, China

Corresponding Author

Zhongqiao Zheng

ABSTRACT

The control structure and control strategy of CMAC (Cerebellar Model Articulation Controller) and PID parallel control system are designed based on the good nonlinear approximation ability and adaptation of CMAC neural network, combined with the advantages of simple structure and easy operation of common PID controller. The compound control of CMAC and PID is carried out for typical second-order control system and a good GUI (Graphical User Interface) is given. The simulation results show that, compared with the traditional PID control, the rise time of the control system by CMAC and PID composite control strategy is reduced by 0.01s, the adjustment time is reduced by 0.1s, and the overshoot is reduced by 15%. The control system has been significantly improved in the steady-state performance and dynamic performance, and has good control performance.

KEYWORDS

CAMC, PID controller, composite control, GUI, control strategy

CITE THIS PAPER

Zhongqiao Zheng, Research on CMAC and PID Compound Control Based on GUI. Journal of Electronics and Information Science (2023) Vol. 8: 67-75. DOI: http://dx.doi.org/10.23977/10.23977/jeis.2023.080109.

REFERENCES

[1] Albus J S. Data storage in the control cerebellar model articulation control (CMAC). Trans. on Asme J. of Dynamic Systems Measurement &Control, 1975 (97): 228-233.
[2] H Ma, T Ying-Chih, LI Chen. A CMAC-based scheme for determining membership with classification of text strings. Neural Computing and Applications, 2016, 27 (7): 1-9.
[3] Rodríguez F O, Rubio J D J, Gaspar C R M. Hierarchical fuzzy CMAC control for nonlinear systems. Neural Computing & Applications, 2013, 23 (1): 323-331.
[4] Fu Jianjian, Yu Shixian. CMAC neural network and robust H ∞ composite control for flexible systems Mechanical Design and Manufacturing, 2020 (12): 158-166
[5] Zhao Jinsong, Wang Chunfa, Xu Jiaxiang, et al. CMAC-Fuzzy PID Control for Multi-dimensional Force Loading System of Hydraulic Drive Parallel Mechanism, Journal of Central South University (Natural Science Edition) 2020, 51 (10) :2811-2821.
[6] Liao Yuntao, Xiang Jie. Photovoltaic power short-term prediction based on CMAC-BP neural network, information technology and standardization 2020, (09): 54-58.
[7] Wang Ling. Intelligent optimization algorithm and its application Beijing: Tsinghua University Press, 2001
[8] Wang Xiaoping, Cao Liming. Genetic algorithm - theory, application and software implementation Xi'an: Xi'an Jiaotong University Press, 2002.
[9] Feng Dongqing, Xing Guangcheng, etc. Multivariable PID neural network control based on improved PSO algorithm Journal of System Simulation, 2011, 23 (2): 363-366
[10] Zhu Jiaqun, Zou Ling, Sun Yuqiang. Application research of CMAC neural network and PID compound control Microcomputer Information, 2006 (05S): 59-61
[11] Kraft L G, Campagna D P. A comparison between CMAC neural network control and two traditional adaptive control systems. Control Systems Magazine, IEEE, 1990, 10 (3): 36-43.
[12] Hu Jinzhu, Xie Shousheng, Zhai Xusheng. Engine guide vane control system based on CMAC and PID algorithm Journal of Missile and Guidance, 2009, 29 (4): 154-156
[13] Chen Hui, Zhou Ping. CMAC network structure of cerebellar model and determination of relevant parameters Computer Engineering, 2003, 29 (2): 252-254
[14] Li W, Zhang H, Xie F. CMAC and PID Concurrent Control for Aeroengine. Journal of Projectiles, Rockets, Missiles and Guidance, 2006 (3): 23-30.
[15] Yang Jie, Li Zehui, Ma Kai, Xu Chenglin. Optimal dispatching method of temperature control load based on cerebellar model neural network Power System Automation, 2022, 46 (10): 199-208
[16] Liu Dong. Research on brushless DC motor non-inductive control system based on fuzzy CMAC Master's Thesis of Harbin University of Technology, 2020
[17] Zhao Ganlin. Target trajectory prediction based on cerebellar model neural network Master's Thesis of Harbin Engineering University, 2018
[18] Fu Xingjian, Yu Shixian. CMAC neural network and robust H ∞ composite control for flexible systems Mechanical Design and Manufacturing, 2020, (12): 158-160+166
[19] T. Q. Ngo, T. V. Phuong. Robust adaptive self -organizing wavelet fuzzy CMAC tracking control for deicing robot manipulator. International Journal of Computers Communications & Control, 2015, 10 (4): 567-578.
[20] Rodríguez F O, Rubio J D J, Gaspar C R M. Hierarchical fuzzy CMAC control for nonlinear systems. Neural Computing & Applications, 2013, 23 (1): 323-331.

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