An observer‐based controller for a class of polynomial fuzzy systems with disturbance

Han, Hugang

doi:10.1002/tee.22211

Cited by 15 publications

(6 citation statements)

References 10 publications

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“…Refs. [18][19][20][21], and the references therein), it is not difficult to obtain (4). Therefore, Assumption 2.3 is rather a standard assumption.…”

Section: Assumption 22mentioning

confidence: 99%

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Further results on adaptive robust state observers of a class of dynamical systems with nonlinear uncertainties and external disturbances

Wang

et al. 2017

IEEJ Transactions Elec Engng

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The problem of adaptive robust observer design is considered for a class of nonlinear systems with completely unknown nonlinear uncertainties and external disturbances. It is assumed that the external disturbances are continuous and have unknown upper bounds, and that the completely unknown nonlinear uncertainty can be approximated by neural networks or fuzzy logic. Particularly, in the actual observation process, approximation will not be used. For such a class of uncertain dynamical systems, a new adaptive robust state observer with a rather simpler structure is proposed. It is shown that the observation error between the state estimate and the true state can be guaranteed to converge asymptotically to zero. Finally, as a numerical example, a Chua circuit is given to demonstrate the validity of the results.

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“…Refs. [18][19][20][21], and the references therein), it is not difficult to obtain (4). Therefore, Assumption 2.3 is rather a standard assumption.…”

Section: Assumption 22mentioning

confidence: 99%

“…Refs. [18][19][20][21] and the references therein). It should be pointed out that, if the neural networks or fuzzy logic has a complicated structure, this may lead to a heavy computational burden and longer learning time Refs.…”

Section: Introductionmentioning

confidence: 99%

Further results on adaptive robust state observers of a class of dynamical systems with nonlinear uncertainties and external disturbances

Wang

et al. 2017

IEEJ Transactions Elec Engng

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“…Hence, when designing a model‐based controller in the presence of an unknown input, the influence of the unknown input on the real state must be considered again, though the influence to the state observer was canceled by multiplying the gain of the disturbance with an elaborately designed matrix. Recently, disturbance‐observer‐based control provides a promising approach to handle the disturbance and improve robustness . However, the observer involved is designed on the basis of the assumption that the disturbance is constant, though the assumption can be extended to cases such as a slowly changing or piecewise constant.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, disturbance-observer-based control provides a promising approach to handle the disturbance and improve robustness [11,12]. However, the observer involved is designed on the basis of the assumption that the disturbance is constant, though the assumption can be extended to cases such as a slowly changing or piecewise constant.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy‐approximator‐based adaptive controller design using Nussbaum‐type function

Han

2018

IEEJ Transactions Elec Engng

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While the Takagi–Sugeno (T‐S) fuzzy model is widely used as a model to design a controller for a system to be controlled, there is a gap, which in this paper is referred to as uncertainty, between the T‐S fuzzy model and the system. The uncertainty is considered here in an effort to improve the control system performance. Though the basic idea to address the uncertainty in this paper is to employ a frequently used approach that utilizes a fuzzy approximator, the relevant parameters are tuned by novel adaptive laws with the help of the Nussbaum‐type function. Consequently, the closed‐loop control system is able to be asymptotically stable. In addition, simulations are provided to demonstrate the effectiveness of the approaches proposed. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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“…Uncertainty observer-based control provides a promising approach to handle system uncertainty and improve robustness [18][19][20][21]. In this framework, a baseline controller is first designed under the assumption that the uncertainty is not considered, and then, a compensation part is added to the baseline controller in order to counteract the influence of the uncertainty that is estimated by an observer.…”

Section: Introductionmentioning

confidence: 99%

A Controller Design Based on Takagi-Sugeno Fuzzy Model Employing Trajectory of Partial Uncertainty

Han

Hamasaki

2018

Designs

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When the Takagi-Sugeno (T-S) fuzzy model is used to design controllers for a concerned system, the discrepancy between the system and its T-S fuzzy model becomes crucial sometimes in terms of control performance, particularly in cases when the magnitude of the discrepancy is relatively large. While most existing works have focused on approaches to restrain the influence of the discrepancy, the idea used in this paper is to extract as much information from the discrepancy as possible at first and then use it in the controller design before restraining its influence. By doing so, the magnitude of the discrepancy is reduced accordingly, and thus, better control performance can be expected. Including the discrepancy and other uncertain elements like the inner parameters' perturbation, a term called uncertainty is considered in this paper. Assuming that the uncertainty influences the system behavior through the state and control input, an observer able to catch the trajectory of the partial uncertainty related to the control input is proposed. Then, a controller employing the trajectory is suggested. All design parameters are obtained by solving certain linear matrix inequalities, which guarantees the system stability. Finally, simulations are provided to illustrate the effectiveness of the proposed approach.

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An observer‐based controller for a class of polynomial fuzzy systems with disturbance

Cited by 15 publications

References 10 publications

Further results on adaptive robust state observers of a class of dynamical systems with nonlinear uncertainties and external disturbances

Further results on adaptive robust state observers of a class of dynamical systems with nonlinear uncertainties and external disturbances

Fuzzy‐approximator‐based adaptive controller design using Nussbaum‐type function

A Controller Design Based on Takagi-Sugeno Fuzzy Model Employing Trajectory of Partial Uncertainty

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