Estimation and disturbance rejection performance for fractional order fuzzy systems

Sakthivel, R.; K, Raajananthini; Kwon, Oh‐Min; Mohanapriya, S.

doi:10.1016/j.isatra.2019.02.005

Cited by 27 publications

(17 citation statements)

References 33 publications

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“…The genetic characteristics in microbial fermentation process can be better depicted by employing fractional-order system [3]. In recent years, the theory of fractional-order control systems has captured many scholars' attention and achieved fruitful results [4][5][6]. [4] solved the robust fault estimation-based synchronization problem for a class of fractional-order multi-weighted complex dynamic networks subject to external disturbances.…”

Section: Introductionmentioning

confidence: 99%

“…[4] solved the robust fault estimation-based synchronization problem for a class of fractional-order multi-weighted complex dynamic networks subject to external disturbances. [5] considered the output tracking control problem and disturbance rejection performance for a class of fractional-order T-S fuzzy systems with timevarying delay and external disturbances. More interesting results in this field can be found in [6].…”

Section: Introductionmentioning

confidence: 99%

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Finite-Time Bounded Tracking Control for Fractional-Order Systems

et al. 2021

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This paper solves the finite-time bounded tracking control problem for fractional-order systems. Firstly, by taking the fractional derivative on state equations and error signals, a fractional-order error system is constructed, and the error signal is taken as the output vector of the error system. Secondly, a state feedback controller is introduced into the error system, and the fractional derivative of disturbance signals and desired tracking signals are combined as the disturbance signal of the error system. Thus, the original problem is converted into the input-output finite time stability problem of the closed-loop error systems. Thirdly, based on the linear matrix inequalities (LMIs), the sufficient conditions which ensure the finite-time bounded tracking for the desired tracking signals are derived. Therefore, the finite-time bounded tracking controller of the original system is obtained. Finally, simulation results elucidate the effectiveness of the controller. INDEX TERMS Finite-time bounded tracking, fractional-order systems, error systems, linear matrix inequalities.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Finite-Time Bounded Tracking Control for Fractional-Order Systems

et al. 2021

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“…Due to its simple configuration and few requirements on prior information of disturbances or uncertainties, the EID approach is widely applied to various systems, such as uncertain multiagent systems, 17 singular Markovian jump systems, 18 and fractional‐order fuzzy systems 19 for robust disturbance estimation and rejection. However, the property of EID‐based control systems is still not well investigated, for example, the characteristics of the system configuration, the analysis of control performance, the bandwidth limitations imposed by the open right‐half plane (ORHP) zeros and poles in the open‐loop transfer function.…”

Section: Introductionmentioning

confidence: 99%

Analysis of equivalent‐input‐disturbance‐based control systems and a coordinated design algorithm for uncertain systems

Liu

et al. 2021

Intl J Robust & Nonlinear

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The control method based on the equivalent‐input‐disturbance (EID) estimator and the Luenberger state observer has received much attention in recent years. However, the property of EID‐based control systems is still not well investigated. A number of design procedures were proposed but lacked sufficient theoretic justification. In this article, the two‐degree‐of‐freedom nature of an EID‐based control system is revealed. Specifically, the reference‐tracking is determined by an outer loop, while the disturbance rejection and robustness is determined by an inner loop consisting of the EID estimator and state observer. The bandwidth constraints on the inner loop are analyzed for plants having zeros or poles in the open right‐half plane by using the Bode and the Poisson integral formulas. These analyses provide a theoretic justification for conventional design procedures. Further, a coordinated design algorithm is provided for the EID‐based uncertain control systems. In addition, a comprehensive comparison of the EID‐based and the disturbance observer (DOB) based control systems is conducted in the system design aspect. Lastly, comparative studies of the EID‐based and DOB‐based control methods are given for various types of plants to validate the developed design algorithm.

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“…The method plays the role of a nonlinear system in mathematical modeling by if-then fuzzy rules and sublinear systems. Due to the rapid development of computer speed, the T-S method has been studied by many papers [19][20][21][22][23][24][25][26][27]. To take advantage of the T-S fuzzy system, the synchronization of the chaotic system has been reconstructed in the form of a T-S system [28][29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%