72 research outputs found
Observer-based controller design for Takagi-Sugeno fuzzy systems with local nonlinearities
No full textExperimental application of Takagi-Sugeno observers and controllers in a nonlinear electromechanical system
No full text[EN] In this paper, a systematic methodology to design fuzzy Takagi-Sugeno observers and controllers will be used to estimate the angular positions and speeds, as well as to stabilise an experimental mechanical system with 3 degrees of freedom (fixed quadrotor). Takagi-Sugeno observers and controllers are compared to observers and controllers based on the linearized model, both designed with the same optimization criteria and design parameters. Experimental results confirm that Takagi-Sugeno models and observers behave similarly to linear ones around the linearization point, but have a better performance over a larger operating range, as intuitively expected.The work of Zs. Lendek was supported by a grant of the Romanian National Authority for Scientific Research, CNCS UEFISCDI, project number PN-II-RU-TE-2011-3-0043, contract number 74/05.10.2011. Spanish authors are grateful to grants DPI2011-27845-C02-01 (A. Sala), DPI2011-27845-C02-02 (R. Sanchis), DPI2011-28507-C02-01 (P. Garcia) from Spanish Government, and PROMETEOII/2013/004 (A. Sala, P. Garcia) from Generalitat Valenciana.Lendek, Z.; Sala, A.; García Gil, PJ.; Sanchis Llopis, R. (2013). Experimental application of Takagi-Sugeno observers and controllers in a nonlinear electromechanical system. Control Engineering and Applied Informatics. 15(4):3-14. https://riunet.upv.es/handle/10251/150453S31415
Output feedback control for T-S discrete-time nonlinear descriptor models
No full textInternational audienceThis paper presents a static output feedback controller design for discrete-time nonlinear descriptor models. The conditions are given in terms of linear matrix inequalities (LMIs). The approach is based on the Takagi-Sugeno (T-S) representation of the nonlinear system and Finsler's Lemma. The proposed method exploits the discrete-time nature of the T-S model by the use of delayed Lyapunov functions, which provide more degrees of freedom without increasing the number of LMIs. It is also extended for robust control. The benefits of the proposed approaches are illustrated via numerical examples
Takagi–Sugeno fuzzy payload estimation and adaptive control
No full textIn this paper, a novel adaptive Takagi-Sugeno (TS) fuzzy observer-based controller is proposed. The closed-loop stability and the boundedness of all the signals are proven by Lyapunov stability analysis. The proposed controller is applied to a flexible-transmission experimental setup. The performance for constant payload in the presence of noisy measurements is compared to a controller based on a classical extended Luenberger observer. Simulation and real-time results show that the proposed observer-based feedback controller provides accurate position tracking under constant and varying payloads.Support Delft Center for Systems and ControlLearning & Autonomous Contro
Static output feedback control for continuous-time TS descriptor models: Decoupling the Lyapunov function
No full textInternational audienceThe paper deals with static output feedback controller design for continuous-time Takagi-Sugeno descriptor models. Via the well-known Finsler's Lemma and the descriptor-redundancy approach a set of linear matrix inequalities are derived to solve this design problem. A numerical example shows the effectiveness of the proposed approaches
Proceedings of the 4th IFAC Conference on Intelligent Control and Automation Sciences ICONS 2016
No full textInternational audienc
Controller Design for TS Models Using Delayed Nonquadratic Lyapunov Functions
No full textIF=3.236International audienceIn the last few years, nonquadratic Lyapunov functions have been more and more frequently used in the analysis and controller design for Takagi-Sugeno fuzzy models. In this paper, we developed relaxed conditions for controller design using nonquadratic Lyapunov functions and delayed controllers and give a general framework for the use of such Lyapunov functions. The two controller design methods developed in this framework outperform and generalize current state-of-the-art methods. The proposed methods are extended to robust and H ∞ control and α-sample variation
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