Biblio

In this paper, the adaptive event-triggered asymptotic tracking control with guaranteed performance for a single link robot manipulator (SLRM) system driven by the brush DC motor is studied. Fuzzy logic systems (FLS) is used to approximate unknown nonlinear functions. By introducing a finite time performance function (FTPF), the tracking error of the system can converge to the compact set of the origin in finite time. In addition, by introducing the smooth function and some positive integral functions, combined with the boundary estimation method and adaptive backstepping technique, the asymptotic tracking control of the system is realized. Meanwhile, event-triggered mechanism is introduced to reduce the network resources of the system. Finally, a practical example is given to prove the effectiveness of the theoretical research.

This paper is concerned with the problem of adaptive finite-time prescribed performance control for a category of uncertain nonlinear systems subject to fuzzy dead-zone input. Via combining the technologies of command filter and backstepping control, the ``singularity'' and the ``explosion of complexity'' issues within controller design procedure are avoided. Moreover, by designing a state observer and utilizing the center-of-gravity theorem, the unmeasured states of system are estimated and the fuzzy issue result from fuzzy dead-zone input is disposed, respectively. Meanwhile, a finite-time fuzzy controller is constructed via combining with finite-time stability criterion, which guarantees all the signals in closed-loop system are convergent and the trajectory of tracking error also strictly evolves within a predefined range in finite time. At last, some simulation results confirm the viability of presented theoretical results.