Regular Papers

International Journal of Control, Automation and Systems 2021; 19(11): 3801-3811

Published online September 2, 2021

https://doi.org/10.1007/s12555-020-0114-5

© The International Journal of Control, Automation, and Systems

Adaptive Tracking Design of NCS with Time-varying Signals Using Fuzzy Inverse Model

Shiwen Tong*, Dianwei Qian, Na Huang, Guo-ping Liu, Jiancheng Zhang, and Guang Cheng

Beijing Union University

Abstract

Tracking control of time-varying signal is a very challenging problem for the network environment applications. An adaptive control strategy based on the inverse of fuzzy singleton model is proposed in the paper. The fuzzy singleton model is a designed equivalent system instead of the fuzzy clustering model of the controlled process. Following an invertibility condition, a collection of predicted control actions are derived from the iterated inverse fuzzy singleton model. Thus, the data dropout and time delays in the network are compensated by means of these predicted values. To enhance control performance, the adaptive control strategy is adopted. Since the method is started from the inputs and outputs of the process, it is actually a data-based solution which is very suitable to the processes with blurred mechanism. Compared with other two control algorithms, the proposed control algorithm exhibits good accuracy, high efficiency, and fast tracking features. Simulations in the data dropout and time-delay cases have verified the effectiveness of the method.

Keywords Adaptive control, fuzzy clustering, fuzzy inversion, fuzzy singleton model, networked tracking control.

Article

Regular Papers

International Journal of Control, Automation and Systems 2021; 19(11): 3801-3811

Published online November 1, 2021 https://doi.org/10.1007/s12555-020-0114-5

Copyright © The International Journal of Control, Automation, and Systems.

Adaptive Tracking Design of NCS with Time-varying Signals Using Fuzzy Inverse Model

Shiwen Tong*, Dianwei Qian, Na Huang, Guo-ping Liu, Jiancheng Zhang, and Guang Cheng

Beijing Union University

Abstract

Tracking control of time-varying signal is a very challenging problem for the network environment applications. An adaptive control strategy based on the inverse of fuzzy singleton model is proposed in the paper. The fuzzy singleton model is a designed equivalent system instead of the fuzzy clustering model of the controlled process. Following an invertibility condition, a collection of predicted control actions are derived from the iterated inverse fuzzy singleton model. Thus, the data dropout and time delays in the network are compensated by means of these predicted values. To enhance control performance, the adaptive control strategy is adopted. Since the method is started from the inputs and outputs of the process, it is actually a data-based solution which is very suitable to the processes with blurred mechanism. Compared with other two control algorithms, the proposed control algorithm exhibits good accuracy, high efficiency, and fast tracking features. Simulations in the data dropout and time-delay cases have verified the effectiveness of the method.

Keywords: Adaptive control, fuzzy clustering, fuzzy inversion, fuzzy singleton model, networked tracking control.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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