Observer-Based Fuzzy PID Tracking Control Under Try-Once-Discard Communication Protocol: An Affine Fuzzy Model Approach

• Published in: IEEE transactions on fuzzy systems Vol. 32; no. 4; pp. 2352 - 2365
• Main Authors: Wang, Yezheng, Wang, Zidong, Zou, Lei, Dong, Hongli
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Affine Takagi–Sugeno (T-S) fuzzy system; Control systems design; Controllers; Convexity; Data exchange; Data transmission; Fuzzy control; Matrix theory; Nonlinear systems; Optimization techniques; PD control; PI control; Proportional integral derivative; proportional–integral–derivative (PID) control; Protocols; Sensors; System performance; Takagi-Sugeno model; Tracking control; Tracking errors; Trajectory analysis; try-once-discard protocol (TODP); Vehicle dynamics
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2024.3350341

In this article, the problem of observer-based fuzzy proportional-integral-derivative (PID) tracking control is studied for networked nonlinear systems subject to protocol constraints and norm-bounded noises. The nonlinear plant under consideration is represented by an affine fuzzy model with immeasurable premise variables. The utilization of the try-once-discard protocol is proposed for information exchange between sensors and the controller, in order to mitigate the data transmission burden. An observer-based PID controller is put forward to achieve the desired tracking task and handle immeasurable premise variables, with sufficient consideration given to both available measurements and the reference trajectory. By analyzing the dynamics of the controlled tracking error system through the construction of a piecewise Lyapunov-like functional, the exponential ultimate boundedness of the tracking error dynamics is ensured. The controller parameters are designed using convex optimization technique and matrix theory, such that the tracking error dynamics is exponentially ultimately bounded. Finally, the validity and merits of the developed controller design method are verified through a simulation example.