This paper investigates a consensus problem for a class of T-S fuzzy multiple-agent systems (MASs) with unknown input (UI). To begin with, an unknown input observer (UIO) is able to asymptotically estimate the system state and the UI is designed for each agent. In order to construct the UIO, the state interval estimation is obtained by first using zonotope theory. Next, using the interval estimation of the state, a correlation of the state and the UI is built. Subsequently, a UIO is constructed, which is proposed by building upon the algebraic relationship. Moreover, by using the estimations of the state and the UI, a distributed control protocol is developed based on the proposed UIO. And, with the proposed distributed control protocol, the T-S fuzzy MAS can achieve consensus, in that all the states of the agents can converge to the leader's state asymptotically. Finally, the effectiveness of the proposed method is demonstrated through two simulation examples.
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http://dx.doi.org/10.3390/s24248149 | DOI Listing |
Sensors (Basel)
December 2024
School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China.
This paper investigates a consensus problem for a class of T-S fuzzy multiple-agent systems (MASs) with unknown input (UI). To begin with, an unknown input observer (UIO) is able to asymptotically estimate the system state and the UI is designed for each agent. In order to construct the UIO, the state interval estimation is obtained by first using zonotope theory.
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December 2024
School of Electrical Engineering, Yanshan University, Qinghuangdao, Hebei 066004, China. Electronic address:
In this paper, the sampled-data-based event-triggered tracking control for the positive nonlinear system is discussed. The event-triggered mechanism naturally causes a mismatch between the membership functions of the system model and the fuzzy controller. Meanwhile, the positive constraint and tracking behavior increase the complexity of system analysis and bring conservative analysis results.
View Article and Find Full Text PDFOne of the key areas of research in ambiguous and inconsistent problems with decision-making is T-spherical multiple-attribute decision making (TP-FMADM). The TP-F number (TP-FN), which is an extension of the fuzzy number, an intuitionistic fuzzy number, and other fuzzy structures, may deal with problems involving a significant amount of incorrect, incomplete, and inconsistent data. Being an extension of various fuzzy structures, the TP-F sets (TP-FSs) provide decision-makers greater freedom to voice their actual opinions and offer a broader range of acceptable membership grades.
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November 2024
School of Electrical Engineering, University of Jinan, Jinan 250022, China. Electronic address:
This study presents an H fault-tolerant fuzzy intermittent control approach for the nonlinear hyperbolic partial differential equation (PDE) systems with multiple delays and actuator failures (MDAFs). Firstly, the nonlinear hyperbolic PDE systems with MDAFs are characterized by the Takagi-Sugeno (T-S) fuzzy delayed hyperbolic PDE model. Next, by employing the Lyapunov direct method, this paper demonstrates the robust exponential stability using spatial linear matrix inequalities (SLMIs) based on a new switching Lyapunov functional (LF).
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December 2024
Institute of Carbon Neutral Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China. Electronic address:
This paper studies input-to-state stabilization of delayed discrete-time Takagi-Sugeno (T-S) fuzzy systems via aperiodically intermittent control. We first consider aperiodically intermittent time-triggered control, where we present sufficient conditions via the mathematical induction under the hypotheses of the quasiperiodicity condition. Based on the derived sufficient conditions, we apply a Lyapunov-Krasovskii (L-K) method together with the descriptor method to derive the explicit linear matrix inequalities (LMIs) that ensure the exponential stability and input-to-state stability (ISS), and show the existence of the aperiodically intermittent time-triggered controller that leads to efficient results with much less numerical complexity.
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