Peak-to-Peak Filtering for Networked Nonlinear DC Motor Systems With Quantization

• Published in: IEEE transactions on industrial informatics Vol. 14; no. 12; pp. 5378 - 5388
• Main Authors: Chang, Xiao-Heng, Wang, Yi-Ming
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.12.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computer simulation; Counters; D C motors; DC motors; Filtration; Fuzzy systems; Linear matrix inequalities; Mathematical analysis; Matrix methods; Measurement; Networked systems; nonlinear dc motor systems; Nonlinear systems; peak-to-peak filtering; Performance indices; Product design; quantization; Quantization (signal); Resistors; Takagi–Sugeno (T–S) fuzzy systems; Torque; Uncertainty; Voltage control
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2018.2805707

This paper investigates the peak-to-peak filtering problem for a class of networked nonlinear dc motor systems with quantization. The nonlinear dc motor system is modeled by a Takagi-Sugeno (T-S) fuzzy model. Consider that the measurement output signal and the performance output signal of the system are quantized by two static quantizers before being transmitted by the digital communication channel, respectively. Attention is focused on the design of a peak-to-peak filter such that the filtering error system is asymptotically stable and satisfies the prescribed peak-to-peak filtering performance index. Sufficient conditions for such a peak-to-peak filter are expressed in the form of linear matrix inequalities. Finally, an illustrative simulation is given to show the effectiveness of the proposed approach.