Profoundly Robust Controlling Strategy for Uncertain Nonlinear Mimo System Using T–S Fuzzy System

Profoundly Robust Controlling Strategy for Uncertain Nonlinear Mimo System Using T–S Fuzzy System In this paper, we addressed the problem of developing a robust control scheme for the MIMO nonlinear system; to achieve this, we adopt nonlinear systems with plant uncertainties, time-delayed uncertainties, and external disturbances. A fuzzy logic system is used to approximate the unknown nonlinear functions, and a Takagi–Sugeno (T–S) fuzzy observer is presented for state estimations. The designed control law works on basis of indirect T–S fuzzy control and utilizes two online approximations which allowed instantaneous insertion of finding gains of delayed state uncertainties. The benefit of employing a T–S fuzzy system is utilize of analytical results which are linear instead of approximating functions of nonlinear system with online update laws. The T–S fuzzy tracking control utilizes variable structure control method to resolve the system uncertainties, time-delayed uncertainty, and the external disturbances such that H ∞ tracking performance is achieved. The control rules are derived based on a Lyapunov criterion and the Riccati inequality such that all states of the system are uniformly ultimately limited. Therefore, the effect can be reduced to any prescribed level to achieve H ∞ tracking performance. A two-connected inverted pendulums system on carts used to validate the performance of the proposed fuzzy technique for the control of MIMO nonlinear systems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Fuzzy Systems Springer Journals

Profoundly Robust Controlling Strategy for Uncertain Nonlinear Mimo System Using T–S Fuzzy System

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Taiwan Fuzzy Systems Association and Springer-Verlag Berlin Heidelberg
Subject
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Operations Research, Management Science
ISSN
1562-2479
eISSN
2199-3211
D.O.I.
10.1007/s40815-016-0225-6
Publisher site
See Article on Publisher Site

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